Dissertations / Theses on the topic 'Multi-objective decision making techniques'

This thesis attempts to model homeostatic regulation, a behavioural phenomenon ubiquitousin animals, in the domain of reinforcement learning. We specifically look at multi-objectivereinforcement learning that can facilitate multi-variate regulation. When multiple objectivesare to be handled, the current framework of Multi-objective Reinforcement Learning provesto be unsuitable without information on some preference over the objectives. We thereforemodel homeostatic regulation as a motivational process, that selectively activates some ob-jectives over others, and implements cognitive control. In doing so, we utilize cognitive con-trol not as behavioural principle, but as a control mechanism that arises as a natural necessityfor homeostatic regulation. We utilize a recent framework for drive reduction theory of reinforcement learning, andattempt to provide a normative account of arbitration of objectives from drives. We showthat a purely reactive agent can face difficulties in achieving this regulation, and would re-quire a persistence-flexibility mechanism. This could be handled effectively in our model byincorporating a progress metric. We attempt to build this model with the intention of actingas a natural extension to the current reinforcement learning framework, while also showingappropriate behavioural properties.<br>Homeostatisk reglering är ett universellt beteendemässigt fenomen hos djur, ett fenomen som har att göra med förstärkt inlärning. Här modelleras homeostatisk reglering speciellt med avseende på inlärning av multipla lärandemål med multivariat reglering. Det konventionella ramverket för flermåls förstärkt inlärning visar sig vara olämpligt, när fler än ett mål ska hanteras och målen inte är inbördes prioriterade. Vår modellering innefattar därför en motivationsbaserad process, som förordar vissa mål över andra, och inför en viss kognitiv kontroll. Därvid använder vi kognitiv kontroll inte som en beteendemässig princip, utan som en kontrollmekanism som uppkommer därför att den är naturligt nödvändig för homeostatisk reglering. Vi använder ett nytt ramverk för driftreduceringsteori för förstärkt inlärning, och försöker att beskriva hur mål ska hållas åtskilda från drifter. Vi visar att en renodlat reaktiv agent får svårt att åstadkomma den önskade regleringen; det skulle erfordra en mekanism för varaktighet och flexibilitet. Detta åstadkoms på ett effektivt sätt i vår modell genom att införa ett framstegsmått. Den föreslagna modellen avses som en naturlig utökning av det gängse ramverket, som tillför lämpliga beteendemässiga egenskaper.

In this thesis the problem of conceptual engineering design and the possible use of adaptive search techniques and other machine based methods therein are explored. For the multi-objective optimisation (MOO) within conceptual design problem, genetic algorithms (GA) adapted to MOO are used and various techniques explored: weighted sums, lexicographic order, Pareto method with and without ranking, VEGA-like approaches etc. Large number of runs are performed for findingZ Dth e optimal configuration and setting of the GA parameters. A novel method, weighted Pareto method is introduced and applied to a real-world optimisation problem. Decision support methods within conceptual engineering design framework are discussed and a new preference method developed. The preference method for translating vague qualitative categories (such as &quot;more important 91 , 4m.9u ch less important' 'etc. ) into quantitative values (numbers) is based on fuzzy preferences and graph theory methods. Several applications of preferences are presented and discussed: * in weighted sum based optimisation methods; s in weighted Pareto method; * for ordering and manipulating constraints and scenarios; e for a co-evolutionary, distributive GA-based MOO method; The issue of complexity and sensitivity is addressed as well as potential generalisations of presented preference methods. Interactive dynamical constraints in the form of design scenarios are introduced. These are based on a propositional logic and a fairly rich mathematical language. They can be added, deleted and modified on-line during the design session without need for recompiling the code. The use of machine-based agents in conceptual design process is investigated. They are classified into several different categories (e. g. interface agents, search agents, information agents). Several different categories of agents performing various specialised task are developed (mostly dealing with preferences, but also some filtering ones). They are integrated with the conceptual engineering design system to form a closed loop system that includes both computer and designer. All thesed ifferent aspectso f conceptuale ngineeringd esigna re applied within Plymouth Engineering Design Centre / British Aerospace conceptual airframe design project.

Open pit mine operations are complex businesses that demand a constant assessment of risk. This is because the value of a mine project is typically influenced by many underlying economic and physical uncertainties, such as metal prices, metal grades, costs, schedules, quantities, and environmental issues, among others, which are not known with much certainty at the beginning of the project. Hence, mining projects present a considerable challenge to those involved in associated investment decisions, such as the owners of the mine and other stakeholders. In general terms, when an option exists to acquire a new or operating mining project, , the owners and stock holders of the mine project need to know the value of the mining project, which is the fundamental criterion for making final decisions about going ahead with the venture capital. However, obtaining the mine project’s value is not an easy task. The reason for this is that sophisticated valuation and mine optimisation techniques, which combine advanced theories in geostatistics, statistics, engineering, economics and finance, among others, need to be used by the mine analyst or mine planner in order to assess and quantify the existing uncertainty and, consequently, the risk involved in the project investment. Furthermore, current valuation and mine optimisation techniques do not complement each other. That is valuation techniques based on real options (RO) analysis assume an expected (constant) metal grade and ore tonnage during a specified period, while mine optimisation (MO) techniques assume expected (constant) metal prices and mining costs. These assumptions are not totally correct since both sources of uncertainty—that of the orebody (metal grade and reserves of mineral), and that about the future behaviour of metal prices and mining costs—are the ones that have great impact on the value of any mining project. Consequently, the key objective of this thesis is twofold. The first objective consists of analysing and understanding the main sources of uncertainty in an open pit mining project, such as the orebody (in situ metal grade), mining costs and metal price uncertainties, and their effect on the final project value. The second objective consists of breaking down the wall of isolation between economic valuation and mine optimisation techniques in order to generate a novel open pit mine evaluation framework called the ―Integrated Valuation / Optimisation Framework (IVOF)‖. One important characteristic of this new framework is that it incorporates the RO and MO valuation techniques into a single integrated process that quantifies and describes uncertainty and risk in a mine project evaluation process, giving a more realistic estimate of the project’s value. To achieve this, novel and advanced engineering and econometric methods are used to integrate financial and geological uncertainty into dynamic risk forecasting measures. The proposed mine valuation/optimisation technique is then applied to a real gold disseminated open pit mine deposit to estimate its value in the face of orebody, mining costs and metal price uncertainties.

In this thesis, we address the route selection problem for Unmanned Air Vehicles (UAV) under multiple objectives. We consider a general case for this problem where the UAV has to visit several targets and return to the base. For this case, there are multiple combinatorial problems to be considered. First, the paths to be followed between any pairs of targets should be determined. This part can be considered as a multi-objective shortest path problem. Additionally, we need to determine the order of the targets to be visited. This in turn, is a multi-objective traveling salesperson problem. The overall problem is a combination of these two combinatorial problems. The route selection for UAVs has been studied by several researchers, mainly in the military context. They considered a linear combination of the two objectives<br>minimizing distance traveled and minimizing radar detection threat<br>and proposed heuristics for the minimization of the composite single objective problem. We treat these two objectives separately. We develop an evolutionary algorithm to determine the efficient tours. We also consider an exact interactive approach to identify the best paths and tours of a decision maker. We tested the two solution approaches on both small-sized and large-sized problem instances.

Thesis (S.M.)--Massachusetts Institute of Technology, Computation for Design and Optimization Program, 2010.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (p. 171-174).<br>This thesis proposes new methods to solve three problems: 1) how to model and solve decision-making problems, 2) how to translate between a graphical representation of systems and a matrix representation of systems, and 3) how to cluster single and multiple Design Structure Matrices (DSM). To solve the first problem, the thesis provides an approach to model decisionmaking problems as multi-objective Constraint Optimization Problems (COP) based on their common structures. A set of new algorithms to find Pareto front of multi objective COP is developed by generalizing upon the Conflict-directed A* (CDA*) algorithm for single-objective COPs. Two case studies - Apollo mission mode study and earth science decadal survey study - are provided to demonstrate the effectiveness of the modelling approach and the set of algorithms when they are applied to real world problems. For the second problem, the thesis first extends classical DSMs to incorporate different relations between components in a system. The Markov property of the extended DSM is then revealed. Furthermore, the thesis introduces the concept of "projection", which maps and condenses a system graph to a DSM based on the Markov property of DSM. For the last problem, an integer programming model is developed to encode the single DSM clustering problem. The thesis tests the effectiveness of the model by applying it to a part of a real-world jet engine design project. The model is further extended to solve the multiple DSM clustering problems.<br>by Maokai Lin.<br>S.M.

This study is conducted with the aims to develop a new ranking method for multi-criteria decision making problem with conflicting criteria. Such a problem has a set of Pareto solutions, where the act of improving a value of one solution will result in depreciating some of the others. Thus, in this type of problem, there is no unique solution. However, out of many available options, the Decision Maker eventually has to choose only one solution. With this problem as the motivation, the current study develops a compromise ranking algorithm, namely a trade-off ranking method. The trade-off ranking method able to give a trade-off solution with the least compromise compared to other choices as the best solution. The properties of the algorithm are studied in the thesis on several test cases. The proposed method is compared against several multi-criteria decision making methods with ranking based on the distance measure, which are the TOPSIS, relative distance and VIKOR. The sensitivity analysis and uncertainty test are carried out to examine the methods robustness. A critical criteria analysis is also done to test for the most critical criterion in a multi-criteria problem. The decision making method is considered further in a fuzzy environment problem where the fuzzy trade-off ranking is developed and compared against existing fuzzy decision making methods.

This dissertation presents the theory, design, implementation and successful deployment of a cognitive engine decision algorithm by which a cognitive radio-equipped mobile robot may adapt its motion and radio parameters through multi-objective optimization. This provides a proof-of-concept prototype cognitive system that is aware of its envirionment, its userâ •s needs, and the rules governing its operation. It is to take intelligent action based on this awareness to optimize its performance across both the mobility and radio domains while learning from experience and responding intelligently to ongoing environmental mission changes. The prototype combines the key features of cognitive radios and autonomous vehicles into a single package whose behavior integrates the essential features of both.<br /><br />The use case for this research is a scenario where a small unmanned aerial vehicle (UAV) is traversing a nominally cyclic or repeating flight path (an â •orbitâ •) seeking to observe targets and where possible avoid hostile agents. As the UAV traverses the path, it experiences varying RF effects, including multipath propagation and terrain shadowing. The goal is to provide the capability for the UAV to learn the flight path with respect both to motion and RF characteristics and modify radio parameters and flight characteristics proactively to optimize performance. Using sensor fusion techniques to develop situaitonal awareness, the UAV should be able to adapt its motion or communication based on knolwedge of (but not limited to) physical location, radio performance, and channel conditions. Using sensor information from RF and mobility domains, the UAV uses the mission objectives and its knowledge of the world to decide on a course of action. The UAV develops and executes a multi-domain action; action that crosses domains, such as changing RF power and increasing its speed.<br /><br />This research is based on a simple observation, namely that cognitive radios and autonomous vehicles perform similar tasks, albeit in different domains. Both analyze their environment, make and execute a decision, evaluate the result (learn from experience), and repeat as required. This observation led directly to the creation of a single intelligent agent combining cognitive radio and autonomous vehicle intelligence with the ability to leverage flexibility in the radio frequency (RF) and motion domains. Using a single intelligent agent to optimize decision making across both mobility and radio domains is unified multi-domain decision making (UMDDM).<br>Ph. D.

Energy consumption rates have been dramatically increasing on a global scale within the last few decades. A significant role in this increase is subjected by the recent high temperature levels especially at summer time which caused a rapid increase in the air conditioning demands. Such phenomena can be clearly observed in developing countries, especially those in hot climate regions, where people depend mainly on conventional air conditioning systems. These systems often show poor performance and thus negatively impact the environment which in turn contributes to global warming phenomena. In recent years, the demand for urban or district cooling technologies and networks has been increasing significantly as an alternative to conventional systems due to their higher efficiency and improved ecological impact. However, to obtain an efficient design for district cooling systems is a complex task that requires considering a wide range of cooling technologies, various network layout configuration possibilities, and several energy resources to be integrated. Thus, critical decisions have to be made regarding a variety of opportunities, options and technologies. The main objective of this thesis is to develop a tool to obtain preliminary design configurations and operation patterns for district cooling energy systems by performing roughly detailed optimizations and further, to introduce a decision-making approach to help decision makers in evaluating the economic aspects and environmental performance of urban cooling systems at an early design stage. Different aspects of the subject have been investigated in the literature by several researchers. A brief survey of the state of the art was carried out and revealed that mathematical programming models were the most common and successful technique for configuring and designing cooling systems for urban areas. As an outcome of the survey, multi objective optimization models were decided to be utilized to support the decision-making process. Hence, a multi objective optimization model has been developed to address the complicated issue of decision-making when designing a cooling system for an urban area or district. The model aims to optimize several elements of a cooling system such as: cooling network, cooling technologies, capacity and location of system equipment. In addition, various energy resources have been taken into consideration as well as different solar technologies such as: trough solar concentrators, vacuum solar collectors and PV panels. The model was developed based on the mixed integer linear programming method (MILP) and implemented using GAMS language. Two case studies were investigated using the developed model. The first case study consists of seven buildings representing a residential district while the second case study was a university campus district dominated by non-residential buildings. The study was carried out for several groups of scenarios investigating certain design parameters and operation conditions such as: Available area, production plant location, cold storage location constraints, piping prices, investment cost, constant and variable electricity tariffs, solar energy integration policy, waste heat availability, load shifting strategies, and the effect of outdoor temperature in hot regions on the district cooling system performance. The investigation consisted of three stages, with total annual cost and CO2 emissions being the first and second single objective optimization stages. The third stage was a multi objective optimization combining the earlier two single objectives. Later on, non-dominated solutions, i.e. Pareto solutions, were generated by obtaining several multi objective optimization scenarios based on the decision-makers’ preferences. Eventually, a decision-making approach was developed to help decision-makers in selecting a specific solution that best fits the designers’ or decision makers’ desires, based on the difference between the Utopia and Nadir values, i.e. total annual cost and CO2 emissions obtained at the single optimization stages<br>Die Energieverbrauchsraten haben in den letzten Jahrzehnten auf globaler Ebene dramatisch zugenommen. Diese Erhöhung ist zu einem großen Teil in den jüngst hohen Temperaturniveaus, vor allem in der Sommerzeit, begründet, die einen starken Anstieg der Nachfrage nach Klimaanlagen verursachen. Solche Ereignisse sind deutlich in Entwicklungsländern zu beobachten, vor allem in heißen Klimaregionen, wo Menschen vor allem konventionelle Klimaanlagensysteme benutzen. Diese Systeme verfügen meist über eine ineffiziente Leistungsfähigkeit und wirken sich somit negativ auf die Umwelt aus, was wiederum zur globalen Erwärmung beiträgt. In den letzten Jahren ist die Nachfrage nach Stadt- oder Fernkältetechnologien und -Netzwerken als Alternative zu konventionellen Systemen aufgrund ihrer höheren Effizienz und besseren ökologischen Verträglichkeit satrk gestiegen. Ein effizientes Design für Fernkühlsysteme zu erhalten, ist allerdings eine komplexe Aufgabe, die die Integration einer breite Palette von Kühltechnologien, verschiedener Konfigurationsmöglichkeiten von Netzwerk-Layouts und unterschiedlicher Energiequellen erfordert. Hierfür ist das Treffen kritischer Entscheidungen hinsichtlich einer Vielzahl von Möglichkeiten, Optionen und Technologien unabdingbar. Das Hauptziel dieser Arbeit ist es, ein Werkzeug zu entwickeln, das vorläufige Design-Konfigurationen und Betriebsmuster für Fernkälteenergiesysteme liefert, indem aureichend detaillierte Optimierungen durchgeführt werden. Zudem soll auch ein Ansatz zur Entscheidungsfindung vorgestellt werden, der Entscheidungsträger in einem frühen Planungsstadium bei der Bewertung städtischer Kühlungssysteme hinsichtlich der wirtschaftlichen Aspekte und Umweltleistung unterstützen soll. Unterschiedliche Aspekte dieser Problemstellung wurden in der Literatur von verschiedenen Forschern untersucht. Eine kurze Analyse des derzeitigen Stands der Technik ergab, dass mathematische Programmiermodelle die am weitesten verbreitete und erfolgreichste Methode für die Konfiguration und Gestaltung von Kühlsystemen für städtische Gebiete sind. Ein weiteres Ergebnis der Analyse war die Festlegung von Mehrzieloptimierungs-Modelles für die Unterstützung des Entscheidungsprozesses. Darauf basierend wurde im Rahmen der vorliegenden Arbeit ein Mehrzieloptimierungs-Modell für die Lösung des komplexen Entscheidungsfindungsprozesses bei der Gestaltung eines Kühlsystems für ein Stadtgebiet oder einen Bezirk entwickelt. Das Modell zielt darauf ab, mehrere Elemente des Kühlsystems zu optimieren, wie beispielsweise Kühlnetzwerke, Kühltechnologien sowie Kapazität und Lage der Systemtechnik. Zusätzlich werden verschiedene Energiequellen, auch solare wie Solarkonzentratoren, Vakuum-Solarkollektoren und PV-Module, berücksichtigt. Das Modell wurde auf Basis der gemischt-ganzzahlig linearen Optimierung (MILP) entwickelt und in GAMS Sprache implementiert. Zwei Fallstudien wurden mit dem entwickelten Modell untersucht. Die erste Fallstudie besteht aus sieben Gebäuden, die ein Wohnviertel darstellen, während die zweite Fallstudie einen Universitätscampus dominiert von Nichtwohngebäuden repräsentiert. Die Untersuchung wurde für mehrere Gruppen von Szenarien durchgeführt, wobei bestimmte Designparameter und Betriebsbedingungen überprüft werden, wie zum Beispiel die zur Verfügung stehende Fläche, Lage der Kühlanlage, örtliche Restriktionen der Kältespeicherung, Rohrpreise, Investitionskosten, konstante und variable Stromtarife, Strategie zur Einbindung der Solarenergie, Verfügbarkeit von Abwärme, Strategien der Lastenverschiebung, und die Wirkung der Außentemperatur in heißen Regionen auf die Leistung des Kühlsystems. Die Untersuchung bestand aus drei Stufen, wobei die jährlichen Gesamtkosten und die CO2-Emissionen die erste und zweite Einzelzieloptimierungsstufe darstellen. Die dritte Stufe war ein Pareto-Optimierung, die die beiden ersten Ziele kombiniert. Im Anschluss wurden nicht-dominante Lösungen, also Pareto-Lösungen, erzeugt, indem mehrere Pareto-Optimierungs-Szenarien basierend auf den Präferenzen der Entscheidungsträger abgebildet wurden. Schließlich wurde ein Ansatz zur Entscheidungsfindung entwickelt, um Entscheidungsträger bei der Auswahl einer bestimmten Lösung zu unterstützen, die am besten den Präferenzen des Planers oder des Entscheidungsträgers enstpricht, basierend auf der Differenz der Utopia und Nadir Werte, d.h. der jährlichen Gesamtkosten und CO2-Emissionen, die Ergebnis der einzelnen Optimierungsstufen sind

The implementation of RFID technology has been subject to ever-increasing popularity in relation to the traceability of items as one of the most advance technologies. Implementing such a technology leads to an increase in the visibility management of products. Notwithstanding this, RFID communication performance is potentially greatly affected by interference between the RFID devices. It is also subject to auxiliary costs in investment that should be considered. Hence, seeking a cost-effective design with a desired communication performance for RFID-enabled systems has become a key factor in order to be competitive in today‟s markets. This study introduce a cost and performance-effective design for a proposed RFID-enabled passport tracking system through the development of a multi-objective model that takes in account economic, operation and social criteria. The developed model is aimed at solving the design problem by (i) allocating the optimal numbers of related facilities that should be established and (ii) obtaining trade-offs among three objectives: minimising implementation and operational costs; minimising RFID reader interference; and maximising the social impact measured in the number of created jobs. To come closer to the actual design in terms of considering the uncertain parameters, a fuzzy multi-objective model was developed. To solve the multi-objective optimization problem model, two solution methods were used respectively (epsilon constrain and linear programming) to select the best Pareto solution and a decision-making method was developed to select the final trade-off solution. Moreover, this research aims to provide a user-friendly decision making tool for selecting the best vendor from a group which submitted their tenders for implementing a proposed RFID- based passport tracking system. In addition to that a real case study was applied to examine the applicability of the developed model and the proposed solution methods. The research findings indicate that the developed model is capable of presenting a design for an RFID- enabled passport tracking system. Also, the developed decision-making tool can easily be used to solve similar vendor selection problem. Research findings demonstrate that the proposed RFID-enabled monitoring system for the passport tracking system is economically feasible. The study concludes that the developed mathematical models and optimization approaches can be a useful decision-maker for tackling a number of design and optimization problems for RFID system using artificial intelligence mathematical algorithm based techniques.

For many decisions validation of their outcomes is invariably problematic to objectively assess. Therefore to aid analysis and validation of decision outcomes, approaches which provide improved traceability and more semantically meaningful measurements of the decision process are required. Hence, this research investigates traceability, transparency, interactivity and auditability to improve the decision making process. Approaches and evaluation measures are proposed to facilitate a richer decision making experience. Multi-Criteria Decision Analysis (MCDA) seeks to determine the suitability of alternatives of a goal with respect to multiple criteria. A key component of prominent MCDA methods is the concept of pairwise comparison. For a set of elements, pairwise comparison enables an accurate and transparent extraction and codification of a decision maker’s preferences, though facilitating a separation of concerns. From a set of pairwise comparisons, a ranking of the elements under consideration can be calculated. There are scenarios when a set of pairwise comparisons undergo alteration, both for individual and multiple decision makers. A set of measures of compromise are proposed to quantify the alteration that a set of pairwise comparisons undergo in such scenarios. The measures seek to provide a decision maker with meaningful knowledge regarding how their views have altered. A set of pairwise comparisons may be inconsistent. When inconsistency is present it adversely affects a ranking of the elements derived from the comparisons. Moreover inconsistency within pairwise comparisons used for consideration of more than a handful of elements is almost inevitable. Existing approaches that seek to alter a set of comparisons to reduce inconsistency lack traceability, flexibility, and specific consideration of alteration to the judgments in a way that is meaningful to a decision maker. An approach to inconsistency reduction is proposed that seeks to address these issues. For many decisions the opinions of multiple decision makers are utilized, either to avail of their combined expertise or to incorporate conflicting views. Aggregation of multiple decision makers’ pairwise companions seek to combine the views of the group into a single representation of views. An approach to group aggregation of pairwise comparisons is proposed that models compromise between the decision makers, facilitates decision maker constraints, considers inconsistency reduction during aggregation and dynamically incorporates decision maker weights of importance. With internet access becoming widespread being able to garner the views of a large group of decision makers’ views has become feasible. An approach to the aggregation of a large group of decision makers’ preferences is proposed. The approach facilitates understanding regarding both the agreement and conflict within the group during calculation of an overall group consensus. A Multi-Objective Optimisation Decision Software (MOODS) prototype tool has been developed that implements both the new measures of compromise and the proposed approaches to inconsistency reduction and group aggregation.

The present work explores improvements in group decision-making. It begins with a practical example using state-of-the-art techniques for a complex, high-risk decision. We show how these techniques can reveal a better alternative. Although we created an improved decision process, decision-makers were apt to protect their own organizations instead of the project. This tendency was reduced over the course of the decision-making process but inspired the first conceptual component of this work. The first concept describes the “Cost of Conflict” that can arise in a group decision, using game theory to represent the non-cooperative approach and comparing the outcome to the cooperative approach. We demonstrate that it is possible for the group to settle on a non-Paretto Nash equilibrium. The sensitivity of the decision-maker weights is revealed which led to the second conceptual portion of this work. The second concept applies social network theory to study the influence between decision-makers in a group decision. By examining the number and strength of connections between decision-makers, we build from intrinsically derived weights to extrinsically derived weights by adding the network influences from other decision-makers. The two conceptual approaches provide a descriptive view of non-cooperative decisions where decision-makers still influence each other. These concepts suggest a prescriptive approach to achieving a higher group utility.

The development of a multi-objective decision making and learning model for the use in unmanned systems is the focus of this project. Starting with traditional game theory and psychological learning theories developed in the past, a new model for machine learning is developed. This model incorporates a no-regret decision making model with a Bayesian learning process which has the ability to adapt to errors found in preconceived costs associated with each objective. This learning ability is what sets this model apart from many others. By creating a model based on previously developed human learning models, hundreds of years of experience in these fields can be applied to the recently developing field of machine learning. This also allows for operators to more comfortably adapt to the machine's learning process in order to better understand how to take advantage of its features. One of the main purposes of this system is to incorporate multiple objectives into a decision making process. This feature can better allow its users to clearly define objectives and prioritize these objectives allowing the system to calculate the best approach for completing the mission. For instance, if an operator is given objectives such as obstacle avoidance, safety, and limiting resource usage, the operator would traditionally be required to decide how to meet all of these objectives. The use of a multi-objective decision making process such as the one designed in this project, allows the operator to input the objectives and their priorities and receive an output of the calculated optimal compromise.<br>M.S.E.E.<br>School of Electrical Engineering and Computer Science<br>Engineering and Computer Science<br>Electrical Engineering MSEE

In developing natural resources, decision makers are seeking to achieve different objectives, which cannot be reduced to a single objective such as economic efficiency, this covers only part of the problem. Tradeoffs between multiple objective of unequal importance is unavoidable in the process of selection or ranking of alternative developmental projects or plans. Multiobjective technique has the ability to deal with qualitative and quantitative objectives, also it enhances the planning process by involving broader segments of the society in the process of decision making. Compromise programming (CP) and utility worth analysis (UWA), two multiobjective methods were applied on Zarqa River Basin Project (ZRBP) in Jordan. Their appropriateness and suitability as decision aiding tools was examined in this study. For the purpose of the study, five criteria were developed to serve as a basis for the evaluation and 61 farmers and 15 technicians, planners and decision makers were interviewed. High consistency was observed among the results of ranking the six alternatives when both methods were applied, at the same time the ranking of the alternatives according to benefit/cost ratio and the internal rates of return as economic efficiency measures showed no agreement with the multiobjective ranking.

In the UK, buildings contribute around one third of the energy-related greenhouse gas emissions. Space heating and cooling systems are among the biggest power consumers in buildings. Thus, improvement of energy efficient of HVAC systems will play a significant role in achieving the UK carbon reduction target. This research aims to develop a novel Building Energy Management System (BEMS) to reduce the energy consumption of the HVAC system while fulfilling occupants’ thermal comfort requirements. The proposed system not only considers the occupants’ adaptations when making decisions on the set temperature, but also influences occupants’ behaviours by providing them with suggestions that help eliminate unnecessary heating and cooling. Multi-agent technologies are applied to design the BEMS’s architecture. The Epistemic-Deontic-Axiologic (EDA) agent model is applied to develop the structure of the agents inside the system. The EDA-based agents select their optimal action plan by considering the occupants’ thermal sensations, their behavioural adaptations and the energy consumption of the HVAC system. Each aspect is represented by its relevant objective function. Newly-developed personal thermal sensation models and group-of-people-based thermal sensation models generated by support vector machine based algorithms are applied as objective functions to evaluate the occupants’ thermal sensations. Equations calculating heating and cooling loads are used to represent energy consumption objectives. Complexities of adaptive behaviours and confidence of association rules between behaviours and thermal sensations are used to build objective functions of behavioural adaptations. In order to make decisions by considering the above objectives, novel multi-objective decision-making algorithms are developed to help the BEMS system make optimal decisions on HVAC set temperature and suggestions to the occupants. Simulation results prove that the newly-developed BEMS can help the HVAC system reduce energy consumption by up to 10% while fulfilling the occupants’ thermal comfort requirements.

Detailed holistic patient data is critical for healthcare organizations to better serve their patient populations. This information allows healthcare organizations to create a detailed and holistic record of a patient’s health. However, this large aggregation of personally identifiable patient data raises serious privacy and security concerns amongst patients. For this reason, patient concerns around the privacy and security of information retained by healthcare organizations must be addressed through the development of effective public policy. This research, therefore argues that any decision making process aimed at developing public policy dealing with patient data privacy and security concerns should not only address regulatory concerns, but also patient-centric values. To accomplish this task, multi-objective decision analytic techniques, with Nissenbaum’s (2004) contextual integrity as a normative framework are used. This is done to elicit patient-centric preferences to assist organizations and governmental institutions alike in dealing with their privacy and security concerns around patient data stored by Healthcare Systems.

Unmanned Aerial Vehicles (UAVs) are emerging as an ideal platform for a wide range of civil applications such as disaster monitoring, atmospheric observation and outback delivery. However, the operation of UAVs is currently restricted to specially segregated regions of airspace outside of the National Airspace System (NAS). Mission Flight Planning (MFP) is an integral part of UAV operation that addresses some of the requirements (such as safety and the rules of the air) of integrating UAVs in the NAS. Automated MFP is a key enabler for a number of UAV operating scenarios as it aids in increasing the level of onboard autonomy. For example, onboard MFP is required to ensure continued conformance with the NAS integration requirements when there is an outage in the communications link. MFP is a motion planning task concerned with finding a path between a designated start waypoint and goal waypoint. This path is described with a sequence of 4 Dimensional (4D) waypoints (three spatial and one time dimension) or equivalently with a sequence of trajectory segments (or tracks). It is necessary to consider the time dimension as the UAV operates in a dynamic environment. Existing methods for generic motion planning, UAV motion planning and general vehicle motion planning cannot adequately address the requirements of MFP. The flight plan needs to optimise for multiple decision objectives including mission safety objectives, the rules of the air and mission efficiency objectives. Online (in-flight) replanning capability is needed as the UAV operates in a large, dynamic and uncertain outdoor environment. This thesis derives a multi-objective 4D search algorithm entitled Multi- Step A* (MSA*) based on the seminal A* search algorithm. MSA* is proven to find the optimal (least cost) path given a variable successor operator (which enables arbitrary track angle and track velocity resolution). Furthermore, it is shown to be of comparable complexity to multi-objective, vector neighbourhood based A* (Vector A*, an extension of A*). A variable successor operator enables the imposition of a multi-resolution lattice structure on the search space (which results in fewer search nodes). Unlike cell decomposition based methods, soundness is guaranteed with multi-resolution MSA*. MSA* is demonstrated through Monte Carlo simulations to be computationally efficient. It is shown that multi-resolution, lattice based MSA* finds paths of equivalent cost (less than 0.5% difference) to Vector A* (the benchmark) in a third of the computation time (on average). This is the first contribution of the research. The second contribution is the discovery of the additive consistency property for planning with multiple decision objectives. Additive consistency ensures that the planner is not biased (which results in a suboptimal path) by ensuring that the cost of traversing a track using one step equals that of traversing the same track using multiple steps. MSA* mitigates uncertainty through online replanning, Multi-Criteria Decision Making (MCDM) and tolerance. Each trajectory segment is modeled with a cell sequence that completely encloses the trajectory segment. The tolerance, measured as the minimum distance between the track and cell boundaries, is the third major contribution. Even though MSA* is demonstrated for UAV MFP, it is extensible to other 4D vehicle motion planning applications. Finally, the research proposes a self-scheduling replanning architecture for MFP. This architecture replicates the decision strategies of human experts to meet the time constraints of online replanning. Based on a feedback loop, the proposed architecture switches between fast, near-optimal planning and optimal planning to minimise the need for hold manoeuvres. The derived MFP framework is original and shown, through extensive verification and validation, to satisfy the requirements of UAV MFP. As MFP is an enabling factor for operation of UAVs in the NAS, the presented work is both original and significant.

The development of suitable long term flood risk intervention strategies is a challenge. Climate change alone is a significant complication but in addition complexities exist trying to identify the most appropriate set of interventions, the area with the highest economical benefit and the most opportune time for implementation. All of these elements pose difficulties to decision makers. Recently, there has been a shift in the current practice for appraising potential strategies and consideration is now being given to ensure flexible, adaptive strategies to account for the uncertain climatic conditions. Real Options in particular is becoming an acknowledged approach to account for the future uncertainties inherent in a flood risk investment decision. Real Options facilitates adaptive strategies as it enables the value of flexibility to be explicitly included within the decision making process. Opportunities are provided for the decision maker to modify and update investments when knowledge of the future state comes to light. In this thesis the use of Real Options in flood risk management is investigated as a method to account for the uncertainties of climate change. Each Intervention strategy is purposely designed to capture a level of flexibility and have the ability to adapt in the future if required. A state of the art flood risk analysis tool is employed to evaluate the risk associated to each strategy over future points in time. In addition to Real Options, this thesis also explores the use of evolutionary optimisation algorithms to aid the decision making process when identifying the most appropriate long term strategies. Although the risk analysis tool is capable of quantifying the potential benefits attributed to a strategy, it is not necessarily able to identify the most appropriate. Methods are required which can search for the optimal solutions according to a range of performance metrics. Single and multi-objective genetic algorithms are investigated in this thesis as a method to search for the most appropriate long term intervention strategies. The Real Options concepts are combined with the evolutionary multiobjective optimisation algorithm to create a decision support methodology which is capable of searching for the most appropriate long term economical yet robust intervention strategies which are flexible to future change. The methodology is applied to two individual case studies, a section of the Thames Estuary and an area on the River Dodder. The results show the inclusion of flexibility is advantageous while the outputs provide decision makers with supplementary knowledge which previously has not been considered.

The use of goal programming in various real-world areas - including resource allocation, engineering, agriculture and other applications - has increased a lot in the past few years. The aim of this dissertation is to investigate goal programming approaches in determining prices. Various aspects of price determination - such as cosls, existing prices, competitors' prices, volume change due to price change and other aspects are incorporated in the model in order to suggest reasonable and realistic prices. Taking just these factors into account will not completely solve the problem, as there are usually certain goals that the decision maker would like to achieve. For example, the decision maker would probably like to attain an acceptable pre-specified minimum profit level without adjusting current prices too much whilst keeping prices competitive to insure that customers are not lost in the process of change. In this study, a goal programming model is developed for the determining of products' prices with consideration of these goals. The model makes provision for the change in demand due to the change in prices.<br>Mini-dissertation (M.Com. (Computer Science))--North-West University, Potchefstroom Campus, 2007.

Hoy en día, los controladores proporcionales integrales y proporcionales integrales derivativos son los algoritmos de control más utilizado en la industria. Por otra parte, los controladores fraccionarios han recibido atención recientemente, por parte de la comunidad científica y desde el punto de vista industrial. Debido a esto, en esta tesis algunos de los escenarios implican la sintonización de estos controladores mediante el procedimiento de diseño mediante la optimización multi-objetivo. Este procedimiento se centra en proporcionar un equilibrio razonable entre los objetivos en conflicto y brinda al diseñador la posibilidad de apreciar la comparación de los objetivos de diseño. Esta tesis se divide en tres partes. La primera parte, presenta los fundamentos del sistema de control y discusión de los diferentes compromisos: entre los modos de operación servo / regulación y del rendimiento / robustez. Por otro lado, se ha proporcionado un marco conceptual acerca de la optimización multi-objetivo. La segunda parte, introduce la solución de Nash como una técnica de selección multi-criterio, para seleccionar un punto del frente de Pareto, que represente el mejor compromiso entre los objetivos de diseño. Esta solución es una selección semi-automática escogida en la aproximación del frente de Pareto y ofrece un buen compromiso entre los objetivos de diseño. Luego, se presenta el Multi-stage approach para el proceso de optimización multi-objetivo. Este enfoque implica dos algoritmos: un algoritmo determinista y algoritmo evolutivo. En el cual ambos algoritmos se complementen entre sí a pesar de sus desventajas y mejoran los resultados de la optimización en términos de convergencia y precisión. Además, se introduce el objetivo basado en la fiabilidad, en la descripción del problema multi-objetivo, este se utiliza para medir la degradación del rendimiento. Vale la pena mencionar que, debido a la existencia de incertidumbres en el diseño y fabricación, teniendo este objetivo de diseño le dará otra perspectiva al diseñador en el mundo real. Con el fin de validar el método, dos casos de estudios se ha considerado, el problema de control de la caldera (The Boiler Control Benchmark) para la sintonización de controladores y como segundo caso, una pila Peltier nolineal. Por último, la tercera parte de esta tesis, presentan las contribuciones a la sintonización de controladores. En primer lugar, se propone un conjunto de reglas de sintonía basado en la solución de Nash para un controlador proporcional-integral, en donde la robustez / rendimiento han sido considerados. Por otra parte, como un segundo caso se presenta las reglas de sintonía para un controlador proporcional-integral-derivativo, donde se han considerado el compromiso de robustez/rendimiento y los modos de operación servo / regulación. Además, se proponen reglas de sintonía para el controlador proporcional-integral-derivativo-fraccional-orden implementado el Multi-stage approach para la optimización multi-objetivo.<br>Nowadays, the proportional integral and proportional integral derivatives are the most used control algorithm in the industry. Moreover, the fractional controllers have received attention recently for both, the research community and from the industrial point of view. Owing to this, in this thesis some of the scenarios involve the tuning of these controllers by using the Multiobjective Optimization Design procedure. This procedure focuses on providing reasonable trade-off among the conflictive objectives and brings the designer the possibility to appreciate the comparison of the design objectives. This thesis is divided in three parts. The first part, presented the fundamentals of the control system showing and discussing the different trade-offs between performance/robustness and servo/regulation operation modes. On the other hand a background on multi-objective optimization has been provided. The second part, introduces the Nash solution as a multi-criteria decision making technique, to select a point from the Pareto front that represent the best compromise among the design objective. This solution provides a semi-automatic selection from the Pareto front approximation and offers a good trade-off between the goal objectives. Hereafter, a Multi-stage approach for the multi-objective optimization process is presented. This approach involves two algorithms: a deterministic and evolutionary algorithm. In which both algorithms complement each other in despite of their drawbacks and improve the results of the overall optimization in terms of convergence and accuracy. Further, the introduction of reliability based objective into the multi-objective problem is carried out, to measure the performance degradation. It is worthwhile to mention that, due to the existence of uncertainties in real-world designing and manufacturing having this design objective will give another perspective to the designer. In order to validate the approach, two different case studies has been considered, the Boiler control problem for controller tuning and as second case, a non-linear Peltier Cell. Finally, the third part of this thesis, the contributions on controller tuning have been presented. First, a set of tuning rules based on the NS for a proportional-integral (PI) controller have been devised, where the robustness/performance trade-off have been considered. Moreover, as a second case it is presented a tuning for proportional-integral-derivative controller where the trade-off of the performance/robustness and servo/regulation operation mode has been considered. Moreover, the fractional-order-proportional-integral-derivative controller is tuned by using the Multi-stage approach for the MOO process.

Thesis (MBA)--Stellenbosch University, 2004.<br>ENGLISH ABSTRACT: Everyone, generally. would like to make good decisions, or receive the greatest benefit from a decision made. Companies are no different in this respect and the process of selecting an investment project portfolio has become an important activity. This is, further, complicated by the fact that companies have multiple, and often, conflicting objectives in a situation of capital rationing. This study project proposes a conceptual framework for project portfolio establishment, for application in an industrial manufacturing type environment, by integrating project evaluation and selection, a multi-criteria decision analysis technique and group decision-making. The project issues, the selection of a multi-criteria decision analysis technique and group decisionmaking are dealt with sequentially and then integrated to develop this conceptual framework. The explorative part of this study project deals with project evaluation and selection issues, and the concept of the triple bottom line is proposed to capture the multiple objectives of the company's decision context. Further, decision analysis concepts are reviewed and three categories of multi-criteria decision analysis methods identified. Selected methods in these categories are described, examined and the advantages and drawbacks of the different categories highlighted. The Analytic Hierarchy Process is proposed as the underlying multi-criteria decision analysis technique to support this conceptual framework. Group decision-making is investigated, and aggregation procedures and a method of consistency checking suggested. Finally, the framework is applied to a hypothetical case and the results presented.<br>AFRIKAANSE OPSOMMING: Oor die algemeen wil almal goeie besluite neem, of maksimum voordeel uit die besluite trek. Maatskappye het dieselfde motivering en die aktiwiteit om 'n kapitaalinvesteringsportfolio saam te stel word as van groot belang beskou. Hierdie aktiwiteit is ook deur die werklikheid van vele, dikwels teenstrydige doelwitte sowel as beperkte fondse bemoeilik. In hierdie werkstuk word 'n begripsraamwerk vir die daarstelling van 'n investeringsportfolio vir kapitaalprojekte in 'n nywerheidsomgewing, wat projekevaluering en - keuring, veelvoudige kriterium besluitnemingstegnieke en groepsbesluitneming insluit, voorgestel. Projekverwante faktore, die keuse van 'n veelvoudige kriterium besluitnemingstegniek en derdens groepsbesluitneming word apart bespreek en daarna in die bogenoemde raamwerk geintegreer. Die navorsingsgedeelte van hierdie werkstuk verwys na die evaluering en keuse van projekte. Die begrip van 'n drievoudige maatstaf ('triple bottom line') om die kompleksiteit van 'n maatskappy se besluitnemingsdoelwitte te illustreer, word ondersteun. Daarna word besluitnemingsbegrippe bespreek en drie kategoriee van tegnieke vir veelvoudige kriterium besluitnemings uitgelig. Onder hierdie kategoriee is verkose metodes beskryf en ondersoek, en voor- en nadele van die kategoriee uitgewys. Die Analitiese Hierargie proses word voorgestel as basis van die begripsraamwerk. Groepsbesluitneming word ondersoek en versamelingsmetodes met kontrole vir konsekwentheid word voorgestel. Laastens word die besluitnemingsraamwerk op 'n denkbeeldige geval toegepas en word die resultate bespreek.

Dealing with optimization problems with more than one objective has been an important research area in evolutionary computation. The class of multi-objective problems (MOPs) is an important one because multi-objectivity exists in almost all aspects of human life; whereby there usually exist several compromises in each problem. Multi-objective evolutionary algorithms (MOEAs) have been applied widely in many real-world problems. This is because (1) they work with a population during the course of action, which hence offer more flexible control to find a set of efficient solutions, and (2) real-world problems are usually black-box where an explicit mathematical representation is unknown. However, MOEAs usually require a large amount of computational effort. This is a sub- stantial challenge in bringing MOEAs to practice. This thesis primarily aims to address this challenge through an investigation into issues of scalability and the balance between exploration and exploitation. These have been outstanding research challenges, not only for MOEAs, but also for evolutionary algorithms in general. A distributed framework of local models using explicit niching is introduced as an overarching umbrella to solve multi-objective optimization problems. This framework is used to address the two-part question about first, the role of communication messages and second, the role of explicit niching in distributed evolutionary multi-objective optimization. The concept behind the framework of local models is for the search to be conducted locally in different areas of the decision search space, which allows the local models to be distributed on different processing nodes. During the optimization process, local models interact (exchange messages) with each other using rules inspired from Particle Swarm Optimization (PSO). Hence, the hypothesis of this work is that running simultaneously several search engines in different local areas is better for exploiting local information, while exchanging messages among those diverse engines can provide a better exploration strategy. For this framework, as the models work locally, they gain access to some global knowledge of each other. In order to validate the proposed framework, a series of experiments on a wide range of test problems was conducted. These experiments were motivated by the following studies which in their totality contribute to the verification of our hypothesis: (1) studying the performance of the framework under different aspects such as initialization, convergence, diversity, scalability, and sensitivity to the framework's parameters, (2) investigating interleaving guidance in both the decision and objective spaces, (3) applying local models using estimation of distributions, (4) evaluating local models in noisy environments and (5) the role of communication messages and explicit niching in distributed computing. The experimental results showed that: (1) the use of local models increases the chance of MOEAs to improve their performance in finding the Pareto optimal front, (2) interaction strategies using PSO rules are suitable for controlling local models, and that they also can be coupled with specialization in order to refine the obtained non-dominated set, (3) estimation of distribution improves when coupled with local models, (4) local models work well in noisy environments, and (5) the communication cost in distributed systems with local models can be reduced significantly by using summary information (such as the direction information naturally determined by local models) as the communication messages, in comparison with conventional approaches using descriptive information of individuals. In summary, the proposed framework is a successful step towards efficient distributed MOEAs.

The research objective of this dissertation is to create and demonstrate methods for parameterizing the Pareto frontiers of continuous multi-attribute design problems using barycentric coordinates, and in doing so, to enable intuitive exploration of optimal trade spaces. This work is enabled by two observations about Pareto frontiers that have not been previously addressed in the engineering design literature. First, the observation that the mapping between non-dominated designs and Pareto efficient response vectors is a bijection almost everywhere suggests that points on the Pareto frontier can be inverted to find their corresponding design variable vectors. Second, the observation that certain common classes of Pareto frontiers are topologically equivalent to simplices suggests that a barycentric coordinate system will be more useful for parameterizing the frontier than the Cartesian coordinate systems typically used to parameterize the design and objective spaces. By defining such a coordinate system, the design problem may be reformulated from y = f(x) to (y,x) = g(p) where x is a vector of design variables, y is a vector of attributes and p is a vector of barycentric coordinates. Exploration of the design problem using p as the independent variables has the following desirable properties: 1) Every vector p corresponds to a particular Pareto efficient design, and every Pareto efficient design corresponds to a particular vector p. 2) The number of p-coordinates is equal to the number of attributes regardless of the number of design variables. 3) Each attribute y_i has a corresponding coordinate p_i such that increasing the value of p_i corresponds to a motion along the Pareto frontier that improves y_i monotonically. The primary contribution of this work is the development of three methods for forming a barycentric coordinate system on the Pareto frontier, two of which are entirely original. The first method, named "non-domination level coordinates," constructs a coordinate system based on the (k-1)-attribute non-domination levels of a discretely sampled Pareto frontier. The second method is based on a modification to an existing "normal boundary intersection" multi-objective optimizer that adaptively redistributes its search basepoints in order to sample from the entire frontier uniformly. The weights associated with each basepoint can then serve as a coordinate system on the frontier. The third method, named "Pareto simplex self-organizing maps" uses a modified a self-organizing map training algorithm with a barycentric-grid node topology to iteratively conform a coordinate grid to the sampled Pareto frontier.

Because of the increasing demand for the provision of energy worldwide and the numerous damages caused by a major use of fossil sources, the contribution of renewable energies has been increasing significantly in the global energy mix with the aim at moving towards a more sustainable development. In this context, this work aims at the development of a general methodology for designing PV systems based on ecodesign principles and taking into account simultaneously both techno-economic and environmental considerations. In order to evaluate the environmental performance of PV systems, an environmental assessment technique was used based on Life Cycle Assessment (LCA). The environmental model was successfully coupled with the design stage model of a PV grid-connected system (PVGCS). The PVGCS design model was then developed involving the estimation of solar radiation received in a specific geographic location, the calculation of the annual energy generated from the solar radiation received, the characteristics of the different components and the evaluation of the techno-economic criteria through Energy PayBack Time (EPBT) and PayBack Time (PBT). The performance model was then embedded in an outer multi-objective genetic algorithm optimization loop based on a variant of NSGA-II. A set of Pareto solutions was generated representing the optimal trade-off between the objectives considered in the analysis. A multi-variable statistical method (i.e., Principal Componet Analysis, PCA) was then applied to detect and omit redundant objectives that could be left out of the analysis without disturbing the main features of the solution space. Finally, a decision-making tool based on M-TOPSIS was used to select the alternative that provided a better compromise among all the objective functions that have been investigated. The results showed that while the PV modules based on c-Si have a better performance in energy generation, the environmental aspect is what makes them fall to the last positions. TF PV modules present the best trade-off in all scenarios under consideration. A special attention was paid to recycling process of PV module even if there is not yet enough information currently available for all the technologies evaluated. The main cause of this lack of information is the lifetime of PV modules. The data relative to the recycling processes for m-Si and CdTe PV technologies were introduced in the optimization procedure for ecodesign. By considering energy production and EPBT as optimization criteria into a bi-objective optimization cases, the importance of the benefits of PV modules end-of-life management was confirmed. An economic study of the recycling strategy must be investigated in order to have a more comprehensive view for decision making.

Orientador: Fernando José Von Zuben<br>Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Elétrica e de Computação<br>Made available in DSpace on 2018-08-26T06:49:07Z (GMT). No. of bitstreams: 1 Azevedo_CarlosRenatoBelo_D.pdf: 3449858 bytes, checksum: 7a1811aa772f1ae996e8851c60627b7c (MD5) Previous issue date: 2012<br>Resumo: A presença de incerteza em resultados futuros pode levar a indecisões em processos de escolha, especialmente ao elicitar as importâncias relativas de múltiplos critérios de decisão e de desempenhos de curto vs. longo prazo. Algumas decisões, no entanto, devem ser tomadas sob informação incompleta, o que pode resultar em ações precipitadas com consequências imprevisíveis. Quando uma solução deve ser selecionada sob vários pontos de vista conflitantes para operar em ambientes ruidosos e variantes no tempo, implementar alternativas provisórias flexíveis pode ser fundamental para contornar a falta de informação completa, mantendo opções futuras em aberto. A engenharia antecipatória pode então ser considerada como a estratégia de conceber soluções flexíveis as quais permitem aos tomadores de decisão responder de forma robusta a cenários imprevisíveis. Essa estratégia pode, assim, mitigar os riscos de, sem intenção, se comprometer fortemente a alternativas incertas, ao mesmo tempo em que aumenta a adaptabilidade às mudanças futuras. Nesta tese, os papéis da antecipação e da flexibilidade na automação de processos de tomada de decisão sequencial com múltiplos critérios sob incerteza é investigado. O dilema de atribuir importâncias relativas aos critérios de decisão e a recompensas imediatas sob informação incompleta é então tratado pela antecipação autônoma de decisões flexíveis capazes de preservar ao máximo a diversidade de escolhas futuras. Uma metodologia de aprendizagem antecipatória on-line é então proposta para melhorar a variedade e qualidade dos conjuntos futuros de soluções de trade-off. Esse objetivo é alcançado por meio da previsão de conjuntos de máximo hipervolume esperado, para a qual as capacidades de antecipação de metaheurísticas multi-objetivo são incrementadas com rastreamento bayesiano em ambos os espaços de busca e dos objetivos. A metodologia foi aplicada para a obtenção de decisões de investimento, as quais levaram a melhoras significativas do hipervolume futuro de conjuntos de carteiras financeiras de trade-off avaliadas com dados de ações fora da amostra de treino, quando comparada a uma estratégia míope. Além disso, a tomada de decisões flexíveis para o rebalanceamento de carteiras foi confirmada como uma estratégia significativamente melhor do que a de escolher aleatoriamente uma decisão de investimento a partir da fronteira estocástica eficiente evoluída, em todos os mercados artificiais e reais testados. Finalmente, os resultados sugerem que a antecipação de opções flexíveis levou a composições de carteiras que se mostraram significativamente correlacionadas com as melhorias observadas no hipervolume futuro esperado, avaliado com dados fora das amostras de treino<br>Abstract: The presence of uncertainty in future outcomes can lead to indecision in choice processes, especially when eliciting the relative importances of multiple decision criteria and of long-term vs. near-term performance. Some decisions, however, must be taken under incomplete information, what may result in precipitated actions with unforeseen consequences. When a solution must be selected under multiple conflicting views for operating in time-varying and noisy environments, implementing flexible provisional alternatives can be critical to circumvent the lack of complete information by keeping future options open. Anticipatory engineering can be then regarded as the strategy of designing flexible solutions that enable decision makers to respond robustly to unpredictable scenarios. This strategy can thus mitigate the risks of strong unintended commitments to uncertain alternatives, while increasing adaptability to future changes. In this thesis, the roles of anticipation and of flexibility on automating sequential multiple criteria decision-making processes under uncertainty are investigated. The dilemma of assigning relative importances to decision criteria and to immediate rewards under incomplete information is then handled by autonomously anticipating flexible decisions predicted to maximally preserve diversity of future choices. An online anticipatory learning methodology is then proposed for improving the range and quality of future trade-off solution sets. This goal is achieved by predicting maximal expected hypervolume sets, for which the anticipation capabilities of multi-objective metaheuristics are augmented with Bayesian tracking in both the objective and search spaces. The methodology has been applied for obtaining investment decisions that are shown to significantly improve the future hypervolume of trade-off financial portfolios for out-of-sample stock data, when compared to a myopic strategy. Moreover, implementing flexible portfolio rebalancing decisions was confirmed as a significantly better strategy than to randomly choosing an investment decision from the evolved stochastic efficient frontier in all tested artificial and real-world markets. Finally, the results suggest that anticipating flexible choices has lead to portfolio compositions that are significantly correlated with the observed improvements in out-of-sample future expected hypervolume<br>Doutorado<br>Engenharia de Computação<br>Doutor em Engenharia Elétrica

Environmentally conscious construction has received a significant amount of research attention during the last decades. Even though construction literature is rich in studies that emphasize the importance of environmental impact during the construction phase, most of the previous studies failed to combine environmental analysis with other project performance criteria in construction. This is mainly because most of the studies have overlooked the multi-objective nature of construction projects. In order to achieve environmentally conscious construction, multi-objectives and their relationships need to be successfully analyzed in the complex construction environment. The complex construction system is composed of changing project conditions that have an impact on the relationship between time, cost and environmental impact (TCEI) of construction operations. Yet, this impact is still unknown by construction professionals. Studying this impact is vital to fulfill multiple project objectives and achieve environmentally conscious construction. This research proposes an analytical framework to analyze the impact of changing project conditions on the relationship of TCEI. This study includes green house gas (GHG) emissions as an environmental impact category. The methodology utilizes multi-agent systems, multi-objective optimization, analytical network process, and system dynamics tools to study the relationships of TCEI and support decision-making under the influence of project conditions. Life cycle assessment (LCA) is applied to the evaluation of environmental impact in terms of GHG. The mixed method approach allowed for the collection and analysis of qualitative and quantitative data. Structured interviews of professionals in the highway construction field were conducted to gain their perspectives in decision-making under the influence of certain project conditions, while the quantitative data were collected from the Florida Department of Transportation (FDOT) for highway resurfacing projects. The data collected were used to test the framework. The framework yielded statistically significant results in simulating project conditions and optimizing TCEI. The results showed that the change in project conditions had a significant impact on the TCEI optimal solutions. The correlation between TCEI suggested that they affected each other positively, but in different strengths. The findings of the study will assist contractors to visualize the impact of their decision on the relationship of TCEI.

Les systèmes robotiques modulaires (MRS) font aujourd’hui l’objet de recherches très actives. Ils ont la capacité de changer la perspective des systèmes robotiques, passant de machines conçues pour effectuer certaines tâches à des outils polyvalents capables d'accomplir presque toutes les tâches. Ils sont utilisés dans un large éventail d'applications, notamment la reconnaissance, les missions de sauvetage, l'exploration spatiale, les tâches militaires, etc. Constamment, MRS est constitué de "modules" allant de quelques à plusieurs centaines, voire milliers. Chaque module implique des actionneurs, des capteurs, des capacités de calcul et de communication. Habituellement, ces systèmes sont homogènes où tous les modules sont identiques ; cependant, il pourrait y avoir des systèmes hétérogènes contenant différents modules pour maximiser la polyvalence. L’un des avantages de ces systèmes est leur capacité à fonctionner dans des environnements difficiles dans lesquels les schémas de travail contemporains avec intervention humaine sont risqués, inefficaces et parfois irréalisables. Dans cette thèse, nous nous intéressons à la robotique modulaire auto-reconfigurable. Dans de tels systèmes, il utilise un ensemble de détecteurs afin de détecter en permanence son environnement, de localiser sa propre position, puis de se transformer en une forme spécifique pour effectuer les tâches requises. Par conséquent, MRS est confronté à trois défis majeurs. Premièrement, il offre une grande quantité de données collectées qui surchargent la mémoire de stockage du robot. Deuxièmement, cela génère des données redondantes qui compliquent la prise de décision concernant la prochaine morphologie du contrôleur. Troisièmement, le processus d'auto-reconfiguration nécessite une communication massive entre les modules pour atteindre la morphologie cible et prend un temps de traitement important pour auto-reconfigurer le robot. Par conséquent, les stratégies des chercheurs visent souvent à minimiser la quantité de données collectées par les modules sans perte considérable de fidélité. Le but de cette réduction est d'abord d'économiser de l'espace de stockage dans le MRS, puis de faciliter l'analyse des données et la prise de décision sur la morphologie à utiliser ensuite afin de s'adapter aux nouvelles circonstances et d'effectuer de nouvelles tâches. Dans cette thèse, nous proposons un mécanisme efficace de traitement de données et de prise de décision auto-reconfigurable dédié aux systèmes robotiques modulaires. Plus spécifiquement, nous nous concentrons sur la réduction du stockage de données, la prise de décision d'auto-reconfiguration et la gestion efficace des communications entre les modules des MRS dans le but principal d'assurer un processus d'auto-reconfiguration rapide<br>Modular robotic systems (MRSs) have become a highly active research today. It has the ability to change the perspective of robotic systems from machines designed to do certain tasks to multipurpose tools capable of accomplishing almost any task. They are used in a wide range of applications, including reconnaissance, rescue missions, space exploration, military task, etc. Constantly, MRS is built of “modules” from a few to several hundreds or even thousands. Each module involves actuators, sensors, computational, and communicational capabilities. Usually, these systems are homogeneous where all the modules are identical; however, there could be heterogeneous systems that contain different modules to maximize versatility. One of the advantages of these systems is their ability to operate in harsh environments in which contemporary human-in-the-loop working schemes are risky, inefficient and sometimes infeasible. In this thesis, we are interested in self-reconfigurable modular robotics. In such systems, it uses a set of detectors in order to continuously sense its surroundings, locate its own position, and then transform to a specific shape to perform the required tasks. Consequently, MRS faces three major challenges. First, it offers a great amount of collected data that overloads the memory storage of the robot. Second it generates redundant data which complicates the decision making about the next morphology in the controller. Third, the self reconfiguration process necessitates massive communication between the modules to reach the target morphology and takes a significant processing time to self-reconfigure the robotic. Therefore, researchers’ strategies are often targeted to minimize the amount of data collected by the modules without considerable loss in fidelity. The goal of this reduction is first to save the storage space in the MRS, and then to facilitate analyzing data and making decision about what morphology to use next in order to adapt to new circumstances and perform new tasks. In this thesis, we propose an efficient mechanism for data processing and self-reconfigurable decision-making dedicated to modular robotic systems. More specifically, we focus on data storage reduction, self-reconfiguration decision-making, and efficient communication management between modules in MRSs with the main goal of ensuring fast self-reconfiguration process

Questa tesi descrive l’attività di ricerca svolta durante i tre anni di dottorato (2013-2015) in Scienze dell’ Ingegneria, nel ramo di studio di Ingegneria Civile e Ambientale. Il lavoro di ricerca si è focalizzato sullo sviluppo di un approccio modellistico sistematico per calibrare e validare (C/V; Calibrazione/Validazione) il modello agro-idrologico SWAT per simulare realisticamente tutti i processi di quantità e qualità delle acque in grandi bacini idrografici in Europa (ovvero deflusso superficiale, flusso laterale, baseflow, erosione e sedimentazione, la crescita delle piante, ciclo dei nutrienti/destino/trasporto, denitrificazione e fenomeni carsici). Questa ricerca nasce dalla necessità di fornire robuste valutazioni ai fini di una corretta gestione e per il supporto alle decisioni politiche e normative. Molte innovazioni sono state introdotte nell’approccio modellistico sia per migliorare la struttura che la procedura di calibrazione. Prima di tutto, sono state fatte modifiche al modello SWAT per produrre nuovi e utili outputs per la calibrazione ed interpretazione di specifici processi. Nuovi algoritmi per il calcolo del parametro lunghezza di versante e del fattore LS sono stati testati e validati, cosi come modifiche alla equazione MUSLE. Inoltre, i processi carsici sono stati rappresentati usando il modello KSWAT (qui sviluppato), una combinazione del modello SWAT con un modello di flusso carsico. Per quanto riguarda la calibrazione/validazione, un approccio basato sui processi è stato sviluppato utilizzando sia “hard data” (lunghe serie temporali di dati in molteplici punti di monitoraggio) che “soft data” (informazioni da letteratura di uno specifico processo all’interno del bilancio idrologico, dei sedimenti o dei nutrienti che possono non essere direttamente misurate nell’area di studio, per esempio stima della media annuale di denitrificazione) per un triplice obiettivo: simulare bene le osservazioni, capire i processi all’interno di un bacino e fornire accurate analisi di scenario di costi-benefici per raggiungere gli obiettivi delle principali Direttive Europee. L’approccio modellistico sistematico qui proposto coinvolge diversi aspetti: una strategia di calibrazione e validazione che considera i processi sia relativi alla quantità (portata e sue componenti) che alla qualità (sedimenti e nutrienti); studio di dettaglio per rappresentare i processi idrologici in differenti zone climatiche, cosi come in aree con morfologie carsiche dominanti; validazione delle componenti del bilancio idrologico usando l’approccio di Budyko; la definizione di un setup di modello basato su un'analisi di sensibilità degli attributi topografici derivati da Modelli Digitali del Terreno (DEMs) con diverse risoluzioni; una inter-comparazione dei risultati di diversi modelli (approccio di 2 benchmarking) e la definizione di misure economicamente efficaci per le implementazioni delle migliori pratiche di gestione. Cinque casi studio, e dunque 5 modelli SWAT, che ricoprono circa il 55% d’Europa, sono stati realizzati per spiegare questi argomenti. La Penisola Iberica (556,000 km2) e la Scandinavia (1,000,000 km2) sono state scelte per testare la metodologia di C/V in differenti aree climatiche, mentre il Bacino del Danubio (800,000 km2), cosi come l’Upper Danubio (132,000 km2), sono stati considerati come strategiche, estese-socioeconomiche and eterogenee aree per studiare i principali temi della procedura attraverso la valutazione idrologica e qualitativa. L’isola di Creta invece è stata selezionata per rappresentare fenomeni carsici dal momento che ne è ricoperta piu’del 40%. L’analisi di queste applicazioni modellistiche con SWAT ha mostrato che la metodologica di C/V permette di ottenere buone performance statistiche e buone conoscenze di ogni processo idrologico attraverso l’analisi delle variazioni temporali e spaziali della portata calibrata in regioni diverse ed estese, caratterizzate da eterogenee caratteristiche quali topografia, uso del suolo, tipi di suoli e diversi regimi climatici. Inoltre, l’analisi delle principali componenti del bilancio idrologico (evapotraspirazione e deflusso di base) utilizzando l’approccio Budyko ha messo in evidenza le difficoltà del modello SWAT di predire correttamente il deflusso di base in bacini montuosi regolati, sottolineando la dipendenza della procedura di calibrazione dal numero e dalla distribuzione spaziale delle stazioni di monitoraggio e dall’impatto antropogenico di stoccaggio dell’acqua e diversioni. Si è osservato inoltre che la portata a grande scala non è influenzata né dalla risoluzione del DEM (sia di 25 m e di 100 m) né dagli attributi topografici derivati (per esempio pendenza e lunghezza di versante). Al contrario, le componenti della portata (superficiale, subsuperficiale e sotterranea) sono influenzate dal calcolato del parametro lunghezza di versante basato sul DEM, sottolineando la necessità di migliorare l’attuale algoritmo di SWAT per una migliore rappresentazione delle componenti della portata, cosi come i sedimenti tramite l’equazione “Modified Universal Soil Loss Equation (MUSLE)”. Questa equazione è stata modificata per ridurre la sensibilità dei sedimenti dalle dimensioni della Unità di Risposta Idrologica (HRU) e dal fattore pendenza –lunghezza (LS) ottenerlo robuste simulazioni di concentrazioni e carichi di sedimenti, come anche robusti bilanci in grandi bacini fluviali. E’stato inoltre dimostrato che se opportunamente adattato SWAT è in grado di simulare i processi carsici e le sue intrinseche caratteristiche (per esempio la veloce di infiltrazione nell’acquifero profondo, il movimento dell’acqua nei condotti carsici attraverso sottobacini non ideologicamente connessi in superfici, e il ritorno di flusso nei canali tramite sorgenti 3 carsiche, incrementando così la robustezza del bilancio idrologico in numerosi bacini fluviali in Europa influenzati dalle risorse di acqua carsiche. Per quanto riguarda la qualità delle acque (sedimenti e nutrienti), è stato dimostrato che solo pochi parametri erano sensibili alla calibrazione, aumentando così la difficoltà di rappresentare la variazione spaziale di alcuni processi a grande scala, come la denitrificazione e il trasporto di sedimenti nei fiumi. Comunque, la variazione mensile dell’azoto e fosforo totale sono stati ben simulati in molteplici stazioni di monitoraggio dando un controllo sostanziale dell’inquinamento come direttamente richiesto dalle Direttive Europee (come per esempio la Direttiva Acque Potabili, 98/83/EC). L’inter-comparazione dei carichi dei nutrienti tra diversi modelli ha inoltre confermato l’abilità di SWAT di simulare comparabili carichi di nutrienti in grandi bacini fluviali, sebbene si è evidenziata la necessità di incrementare le osservazioni. Infine, lo strumento di ottimizzazione multi-obiettivo per la gestione delle migliori pratiche di gestione (BMPs) è stato riconosciuto come un valido strumento per identificare efficienti scenari, per esempio correlati alla riduzione di fertilizzanti minerali e al miglioramento di efficienza di depurazione dei depuratori (WWTPs), fornendo una significativa riduzione delle concentrazioni con il miglior costo-beneficio. Questi risultati possono essere viste anche come utili raccomandazioni per i utenti/modellisti che usano SWAT. In conclusione, l’approccio sistematico proposto per la calibrazione/validazione del modello SWAT ha mostrato di essere pedagogico e un potente strumento per scienziati, per politici e anche stakeholders, e può essere esteso ad altri modelli quali-quantitativi che hanno una struttura simile a quella di SWAT.<br>This thesis describes the research I conducted during a three-year doctoral program (2013-2015) in Engineering Science, in the branch study of Civil and Environmental Engineering. During this period, I focused on the development of a systematic modeling approach for calibrating and validating the agro-hydrological SWAT model for realistically simulating all critical hydrological and water quantity processes in large River Basins in Europe (i.e. surface runoff, lateral flow, baseflow, erosion and sedimentation, plant growth, nutrients cycle/fate/transport, denitrification and karst phenomena). This research stems from the need to provide robust and suitable model assessment for making sound management, policy and regulatory decisions. Several innovations were introduced in the modeling approach aimed both to improve model structure and calibration procedure. First of all, modifications of SWAT model were applied to produce new useful outputs for calibration and interpretation of specific processes. New algorithms for the calculation of hillslope length parameter and LS factor were also proposed and tested, as well as a new MUSLE equation. Furthermore, karst processes were represented using the KSWAT model, a combination of SWAT with a karst-flow model. Concerning the calibration/validation, a process-based approach was developed involving both hard (i.e. long time series in multiple gauging stations) and soft data (i.e. literature information of a specific process within a water, sediment, or nutrient balance that may not be directly measured within the study area, e.g. average annual estimate of denitrification) for a threefold objective: to match well the observations, to understand the processes within a basin and to provide accurate cost-benefit scenarios analysis for achieving the goals of the main European Directives. The proposed systematic modeling approach consists on different aspects: the definition of a process-based calibration and validation (C/V) strategy for quantity (streamflow and its components) and quality aspects (sediment and nutrients); detailed study for representing hydrological processes at different climate regimes and in karst dominant morphologies; validation of water balance components using a Budyko framework approach; the inter-model-comparison of outputs 2 (Benchmarking approach); the definition of a suitable model setup based on a sensitivity analysis of derived topographic attributes from different Digital Elevation Model (DEM) pixel size; the definition of cost-effective measures for the Best Management Practices (BMPs) implementation. Five SWAT model case studies were used to illustrate these topics covering approximately 55% of Europe Union. The Iberian (556,000 km2) and the Scandinavia (1,000,000 km2) Peninsulas were selected to test the C/V strategy in different climate regimes, while the Danube River Basin (800,000 km2), as well as the Upper Danube (132,000 km2), were considered as strategic largesocioeconomic-heterogeneous areas for investigating the main key topics of the procedure through water quantity and quality assessment. The Crete Island (8,400 km2) was instead selected as representative for karst phenomena assessment, as it is covered more than 40% by karst features. The analysis of these SWAT model applications has shown that the processbased C/V strategy is able to obtain good performance statistics and to gain good knowledge of each hydrological process through the analysis of temporal and spatial variations of calibrated streamflow in different large regions, characterized by heterogeneous spatial topography, land uses, soils and different climate regimes. Furthermore, the analysis of the main components of the water balance (evapotranspiration and baseflow) via Budyko framework highlighted the difficulties of SWAT model to predict correctly the baseflow in regulated mountainous basins and the dependence of the procedure on the number and spatial distribution of gauging stations and on anthropogenic water storage impact, as well as the water diversions. It was also observed that the predicted streamflow at large-scale is not affected by DEM pixel size (both with 25 m and 100 m DEM pixel size) and SWAT topographic attributes (e.g. slope and hillslope length). Conversely, the streamflow components resulted markedly affected by the change of the hillslope length parameter calculation based on DEM pixel size, highlighting the need to improve the current SWAT algorithm for a better representation of the streamflow components, as well as sediment yields via Modified Universal Soil Loss Equation (MUSLE). This equation was modified to reduce the sensitivity of sediment yields to the Hydrologic Response Units (HRUs) and slope-length factor (LS) obtaining robust simulation of sediment concentrations, yields and suitable budgets in large River Basins. Furthermore, it was demonstrated that SWAT is 3 able to reproduce the karst processes when opportunely adapted to reproduce the karst features and their intrinsic characteristics (such as fast infiltration in deep groundwater, movement of water in the karst conduits across subbasins not hydrologically connected, and the return of water as springs discharges in the rivers), thus increasing the reliability of water balance prediction in numerous river basins in Europe affected by karst water resources. As regards the water quality (sediment and nutrients), it was observed that only few watershed parameters were sensitive to calibration, increasing the difficult to represent the spatial variation of some processes in large-areas, such as the denitrification and sediment transport in the river. However, the monthly seasonal variation of total nitrogen and phosphorous concentrations were well reproduced at multi-gauging stations, given a substantial control of pollution as directly request by the European Directives (i.e. Drinking Water Directive, 98/83/EC). Furthermore, the inter-model comparisons of nutrient loads confirmed the ability of SWAT model to predict comparable nutrient loads in large–river basins, albeit the need to collect more environmental data emerged. Finally, the proposed multi-objective optimization tool for BMPs implementation in SWAT was recognized as a very useful tool in identifying efficient scenarios, related to reduction of mineral fertilization and Waste Water Treatment Plants (WWTPs) upgrading, providing significantly nutrients concentration reduction with the best cost–effectiveness. These findings can be also summarised as several useful recommendations for SWAT modellers. In conclusion, the proposed systematic approach for C/V procedure with SWAT has shown to be pedagogic and a powerful tool both for scientists, policy makers and also stakeholders, and could be extended to other hydrological and water quality models with similar structure as SWAT.

Problem: Engineering design decisions require the integration of information from multiple and disparate sources. However, this information is often independently created, limited to a single perspective, and not formally represented, thus making it difficult to formulate decisions. Hence, the primary challenge is the development of computational representations that facilitate the exchange of information for decision support. Approach: First, the scope of this research is limited to representing design decisions as compromise decision support problems (cDSP). To address this challenge, the primary hypothesis is that a formal language will enable the semantics of cDSP to be captured, thus providing a digital interface through which design information can be exchanged. The primary hypothesis is answered through the development of a description logic (DL) based formal language. The primary research question is addressed in four sub-questions. The first two research questions relate to the development of a vocabulary for representing the semantics of the cDSP. The first hypothesis used to answer this question is that formal information modeling techniques can be used to explicitly capture the semantics and structure of the cDSP. The second research question is focused on the realization of a computer-processible representation. The hypothesis used to answer this question is that DL can be used for developing computational-based representations. The third research question is related to the organization and retrieval of decision information. The hypothesis used to answer this question is DL reasoning algorithms can be used to support organization and retrieval. Validation: The formal language developed in this dissertation is theoretically and empirically validated using the validation square approach. Validation of the hypotheses is achieved by systematically building confidence through example problems. Examples include the cDSP construct, analysis support models, the design of a cantilever beam, and design of a structural fin array heat sink. Contributions: The primary contribution from this dissertation is a formal language for capturing the semantics of cDSPs and analysis support models comprised of: (1) a systematic methodology for decision formulation, (2) a cDSP vocabulary, (3) a graphical information model, and (4) a DL-based representation. The components, collectively, provide a means for exchanging cDSP information.

Esta Dissertação aborda o Problema de Alocação de Aulas a Salas (PAAS), também conhecido como Problema de Alocação de Salas (PAS). As instituições de ensino superior, no começo de seus calendários letivos, resolvem um PAAS ao determinar os espaços a serem utilizados para as atividades didáticas. Porém, em muitas destas instituições o PAAS é ainda resolvido manualmente, gerando altas cargas de trabalho para os responsáveis. Neste trabalho, o Instituto de Ciências Matemáticas e de Computação (ICMC) da Universidade de São Paulo (USP) foi tomado como caso de estudo para o PAAS. Um modelo de programação matemática inteiro é proposto e abordado por técnicas de resolução exata, metaheurísticas mono-objetivo e uma abordagem multi-objetivo. Uma estrutura de vizinhança proposta obteve resultados comparáveis à da metodologia exata, para um tempo fixo de execução. Demonstra-se que, a abordagem multi-objetivo é uma possibilidade de contornar algumas dificuldades clássicas do problema, como incertezas sobre a escolha dos pesos das métricas. Os métodos de solução propostos para o problema fornecem, aos responsáveis, bons instrumentos de auxílio à tomada de decisão para o PAAS.<br>This Dissertation addresses the Classroom Assignment Problem (CAP). All Higher Education Institutes, at the schoolyear\'s begin, faces a CAP to define where the classes will be taught. However, many of those still solves this problem manually, demanding high efforts from the responsible staff. In this study, the Universidade de São Paulo\'s (USP) Instituto de Ciências Matemáticas e de Computação (ICMC) was tackled as study case for the CAP. An Integer Programming Model is proposed and tackled by exact methods, meta-heuristics and a multi-objective approach. A novel neighborhood operator is proposed for the local search and obtains good results, even comparable to the exact method. The multi-objective approach is shown to overcome some of the classical adversity of the mono-objective approach, e.g., choosing weights to quality metric. Those CAP\'s proposed solution methods, gives the responsible staff a good decision making support.

Cette thèse vise à contribuer à la compréhension des cycle de vie d’une opération humanitaire (HOLC). Gestion de la chaîne d'approvisionnement humanitaire (HSCM) dans un contexte de mise en perspective et dans l’objectif de proposer un modèle décisionnel qui s'applique aux phases de HOLC lors d’une situation réelle. Cela inclut la mise en oeuvre du modèle proposé pour concevoir et développer un outil d'aide à la décision afin d'améliorer les performances de la logistique humanitaire tant dans les opérations de secours nationaux qu’internationaux.Cette recherche est divisée en trois phases. La première partie vise à présenter le sens de l'étude ; la zone de recherche prise en compte pour la gestion de la chaîne d'approvisionnement (SCM) doit être clairement définie. La première phase consiste à clarifier et définir le HSCM HL, la gestion de la chaîne d'approvisionnement commerciale (CSCM) et le SCM, ainsi que la relation entre ces différents éléments. La gestion du cycle de vie du projet (PLCM) et les différentes approches sont également présentés. La compréhension de la différence entre la gestion du cycle de vie du projet (PLM) et la PLCM est également nécessaire, cela ne peut être abordé dans la phase de cycle de vie de l'opération humanitaire. De plus, les modèles Multiple-Criteria Decision Making (MCDM) et l’aide à la décision concernant le HL sont analysés pour établir le fossé existant en matière de recherche. Les approches MCDM qui mettent en oeuvre le système d'aide à la décision (DSS) et la manière dont le MAS a été utilisé dans le contexte HSCM sont étudiées.La deuxième phase consiste en la proposition d’un modèle décisionnel fondé sur l’approche MCDM à l'appui de la décision du décideur avant qu'il/elle prenne des mesures. Ce modèle prévoit le classement des alternatives concernant l'entrepôt, le fournisseur et le transport au cours des phases de HOLC. Le modèle décisionnel proposé est réalisée en 3 scénarios. I. La décision en 4phases HOLC – opération de secours internationale de la Croix-Rouge Française (CRF). II. La décision en3phases HOLC – opération nationale dela Croix-Rouge thaïlandaise (TRC). III. La décision au niveau de la phase de réponse HOLC – opération internationale du TRC dans quatre pays. Dans cette phase, le scénario I et II sont réalisés étape par étape au travers de calculs numériques et formules mathématiques. Le scénario III sera présenté dans la troisième phase. Pour établir trois scénarios, les données internes recueillies lors des entretiens avec le chef de la logistique de la Croix-Rouge Française, et le vice-président de la fondation de la Coix-Rouge thaïlandaise, seront utilisées. Les données externes proviennent de chercheurs qui sont des experts dans le domaine HL ou le champ du HSCM, de la littérature, et de sources issues des organismes humanitaires (documents d’ateliers, rapports, informations publiées sur leurs sites officiels).Dans la troisième phase, une application Internet multi-critères (decision support system MCDSS WB) mettant en oeuvre le modèle proposé est élaborée. Afin d'atteindre une décision appropriée en temps réel, le WB-MCDSS est développé sur la base d’un protocole client-serveur et est simple à utiliser. Le dernier mais non le moindre ; une application de validation du modèle est réalisée à l'aide de l'approche de l'analyse de sensibilité<br>This thesis aims to contribute to the understanding of HOLC in context of the HSCM and to propose a decision model which applies to the phases of HOLC the decision making regarding a real situation . This include the implementation of the proposed model to design and develop a decision support tool in order to improve the performance of humanitarian logistics in both national and international relief operations.This research is divided into three phases; the first phase is to clarify and define HL among HSCM, commercial supply chain management (CSCM) and SCM and their relationship. Project Life Cycle Management (PLCM) approaches are also presented. The difference between project life cycle management (PLM) and PLCM is also required to distinguish a clear understanding which can be addressed in the phase of humanitarian operation life cycle. Additionally, the literature of Multiple-Criteria Decision Making (MCDM) models and existing decision aid system for HL are analyzed to establish the research gap. The MCDM approaches which implement the decision support system (DSS) and lastly how DSS has been used in the HSCM context.The second phase is to propose a decision model based on MCDM approaches to support the decision of the decision maker before he/she takes action. This model provides the ranking alternatives to warehouse, supplier and transportation over the phases of HOLC. The proposed decision model is conducted in 3 scenarios; I. The decision in 4-phase HOLC, international relief operation of French Red Cross (FRC). II. The decision on 3-phase HOLC, national operation by the Thai Red Cross (TRC). III. The decision on response phase HOLC, international operation by the FRC in four countries. In this phase, the scenario I and II are performed step by step though numerical calculation and mathematical formulas. The scenario III will be presented in the third phase.In the third phase, an application of web-based multi-criteria decision support system (WB-MCDSS) which implement the proposed model is developed. The web-based multi-criteria decision support system is developed based on the integration of analytical hierarchy process (AHP) and TOPSIS approaches. In order to achieve an appropriate decision in a real time response, the WB-MCDSS is developed based on server-client protocol and is simple to operate. Last but not least, a validation application of the model is performed using the sensitivity analysis approach

[ES] La colaboración empresarial evidenciada en pequeñas y medianas empresas (Pymes) está contribuyendo a ampliar su competitividad, impulsar diversos procesos de innovación y mejorar su rendimiento; siendo, por tanto, fundamental la medición eficaz del rendimiento como una práctica estratégica para impulsar su desarrollo y eficiencia colectiva. La medición del rendimiento (MR) es un elemento esencial para la planificación efectiva y el control empresarial; así como para la toma de decisiones, a fin de desplegar diferentes acciones de mejora. La MR en Pymes incluye las siguientes tres categorías: las medidas de rendimiento o indicadores, el diseño del sistema de medición del rendimiento (SMR) y su desarrollo. El diseño del SMR para redes de Pymes es un proceso importante para asegurar que el marco de medición integre tanto, los factores y elementos del rendimiento propios del contexto colaborativo abordado, así como los métodos y técnicas para un proceso de medición del rendimiento balanceado y con alineamiento estratégico. Sin embargo, en la literatura fueron pocos los estudios que abordaban a la MR en contextos colaborativos. Entre aquellos que lo hacían, la mayoría se relacionaba con el direccionamiento hacia las mejores prácticas; lo que señaló dificultades en cuanto a la consideración de diversos factores entorno a este grupo de Pymes y con ello su implicación en el desarrollo de SMRs específicos. Otro aspecto importante en el diseño del SMR es la presencia de múltiples tomadores de decisión, espacio que tampoco evidenció mayor aporte entre la literatura revisada. Al considerar estos aspectos en el marco del diseño de SMRs para redes de Pymes en colaboración, ninguna investigación presentó un abordaje que contemple todas las características de forma simultánea. Considerando estas brechas, este trabajo de investigación tiene por objetivo proponer un sistema de medición del rendimiento para redes colaborativas de pymes (SMR - RECOP) en un escenario de toma de decisiones en grupo, considerando un enfoque de alineamiento estratégico. La propuesta tiene como finalidad integrar los principales factores de influencia del entorno de la red de Pymes, los requerimientos de medición básicos y la visión de un crecimiento sostenible enmarcado en la eficiencia colectiva. La propuesta de medición del rendimiento utiliza el Balanced Scorecard (BSC) como herramienta para direccionar la estrategia de la red al interior del sistema de medición, donde los indicadores se encuentran en alineación directa con los objetivos estratégicos; además, la técnica Fuzzy TOPSIS para apoyar el proceso de toma de decisiones en grupo que permite la determinación de los objetivos estratégicos y; por último, mesas de diálogo como los espacios para la discusión de ideas y formulación de indicadores de medición. Estas técnicas, juntamente con los elementos citados anteriormente son integrados en una metodología de tres fases. El sistema de medición propuesto se aplica en un caso de investigación para fines de validación; la red de Pymes evaluada pertenece al sector agroindustrial productor de cacao en Ecuador, donde los contextos empresariales tanto de red y cadena se evidencian como las estratégicas colaborativas con importante presencia. La aplicación empírica del SMR - RECOP mostró como resultados necesarios de su desarrollo a los siguientes productos: un conjunto de objetivos estratégicos; un procedimiento establecido para la definición y selección de estos objetivos en el marco de la toma de decisiones en grupo; un mapa estratégico consolidado y por último un conjunto de indicadores de rendimiento. Estos resultados muestran consistencia con los estamentos pretendidos por la red y su contexto de desarrollo; así como con los requerimientos que enmarcan un SMR para Pymes.<br>[CA] La col·laboració empresarial evidenciada en petites i mitjanes empreses (Pimes) està contribuint a ampliar la seva competitivitat, impulsar diversos processos d'innovació i millorar el seu rendiment; sent, per tant, fonamental el mesurament eficaç de l'rendiment com una pràctica estratègica per impulsar el seu desenvolupament i eficiència col·lectiva. El mesurament de l'rendiment (MR) és un element essencial per a la planificació efectiva i el control empresarial; així com per a la presa de decisions, per tal de desplegar diferents accions de millora. La MR a Pimes inclou les següents tres categories: les mesures de rendiment o indicadors, el disseny de sistema de mesurament de l'rendiment (SMR) i el seu desenvolupament. El disseny de l'SMR per a xarxes de Pimes és un procés important per assegurar que el marc de mesurament integri tant, els factors i elements de l'rendiment propis de l'context col·laboratiu abordat, així com els mètodes i tècniques per a un procés de mesurament de l'rendiment balancejat i amb alineament estratègic. No obstant això, en la literatura van ser pocs els estudis que abordaven a la MR en contextos col·laboratius. Entre aquells que ho feien, la majoria es relacionava amb l'adreçament cap a les millors pràctiques; el que va assenyalar dificultats pel que fa a la consideració de diversos factors entorn a aquest grup de Pimes i amb això la seva implicació en el desenvolupament de SMRs específics. Un altre aspecte important en el disseny de l'SMR és la presència de múltiples prenedors de decisió, espai que tampoc va evidenciar major aportació entre la literatura revisada. A l'considerar aquests aspectes en el marc de el disseny de SMRs per a xarxes de pimes en col·laboració, cap investigació va presentar un abordatge que contempli totes les característiques de forma simultània. Considerant aquestes bretxes, aquest treball de recerca té per objectiu proposar un sistema de mesurament de l'rendiment per a xarxes col·laboratives de pimes (SMR - Recull) en un escenari de presa de decisions en grup, considerant un enfocament d'alineament estratègic. La proposta té com a finalitat integrar els principals factors d'influència de l'entorn de la xarxa de pimes, els requeriments de mesurament bàsics i la visió d'un creixement sostenible emmarcat en l'eficiència col·lectiva. La proposta de mesurament de l'rendiment utilitza el Balanced Scorecard (BSC) com a eina per adreçar l'estratègia de la xarxa a l'interior de el sistema de mesurament, on els indicadors es troben en alineació directa amb els objectius estratègics; a més, la tècnica Fuzzy TOPSIS per donar suport al procés de presa de decisions en grup que permet la determinació dels objectius estratègics i; finalment, taules de diàleg com els espais per a la discussió d'idees i formulació d'indicadors de mesurament. Aquestes tècniques, conjuntament amb els elements esmentats anteriorment són integrats en una metodologia de tres fases. El sistema de mesurament proposat s'aplica en un cas d'investigació per a fins de validació; la xarxa de Pimes avaluada pertany a el sector agroindustrial productor de cacau a l'Equador, on els contextos empresarials tant de xarxa i cadena s'evidencien com les estratègiques col·laboratives amb important presència. L'aplicació empírica d'el SMR - RECOP va mostrar com a resultats necessaris del seu desenvolupament als següents productes: un conjunt d'objectius estratègics; un procediment per a la definició i selecció d'aquests objectius en el marc de la presa de decisions en grup; un mapa estratègic consolidat i finalment un conjunt d'indicadors de rendiment. Els resultats obtinguts mostren consistència amb els estaments pretesos per la xarxa i el seu context de desenvolupament; així com amb els requeriments que emmarquen un SMR per a Pimes.<br>[EN] The business collaboration evidenced in small and medium-sized companies (SMEs) is helping to expand their competitiveness, promote different innovation processes, and improve their performance. Therefore, effective performance measurement is essential as a strategic practice to promote its development and collective efficiency. Performance measurement (PM) is an essential element for effective business planning and control; as well as for decision making, in order to deploy different improvement actions. PM in SMEs includes the following three categories: performance measures or indicators, the design of the performance measurement system (PMS), and its development. The design of the PMS for SME networks is an important process to ensure that the measurement framework integrates both the factors and elements of the performance, which belong to the collaborative context addressed, as well as the methods and techniques for a balanced performance measurement process and with strategic alignment. However, in the literature, few studies addressed PM in collaborative contexts. Among those that did it, the majority was related to directing toward best practices; which pointed to difficulties in considering various factors around this group of SMEs and thus their involvement in the development of specific PMSs. Another important issue in the design of the PMS is the presence of multiple decision-makers, a space that did not show a greater contribution among the literature reviewed. When considering these aspects in the framework of PMSs design for collaborative SME networks, no research presented an approach that considers all the characteristics simultaneously. Considering these gaps, this research work aims to propose a performance measurement system for collaborative networks of SMEs (PMS - RECOP) in a group decision-making scenario, considering a strategic alignment approach. The purpose of the proposal is to integrate the main factors that influence the environment of the SMEs network, the basic measurement requirements, and the vision of sustainable growth framed in collective efficiency The performance measurement proposal uses the Balanced Scorecard (BSC) as a tool to direct the strategy of the network within the measurement system, where the indicators are in direct alignment with the strategic objectives. In addition, the Fuzzy TOPSIS technique supports the group decision-making process that allows the determination of strategic objectives and; finally, dialogue tables as spaces for the discussion of ideas and formulation of measurement indicators. These techniques, together with the elements aforementioned, are integrated into a three-phase methodology. The proposed evaluation system is applied in a research case for validation purposes; the network of SMEs evaluated belongs to the agro-industrial sector that produces cocoa in Ecuador, where the business contexts of both the network and the chain are evidenced as collaborative strategies with an important presence. The empirical application of the PMS - RECOP showed the following products as necessary results of its development: a set of strategic objectives, such as an established procedure for the definition and selection of these objectives within the framework of group decision-making; a consolidated strategic map, and finally a set of performance indicators. The obtained results showed consistency with the states intended by the network and its development context, as well as the requirements that frame a PMS for SMEs.<br>Rojas Lema, XB. (2021). Sistema de medición del rendimiento para redes colaborativas de Pymes en el sector agroindustrial de Ecuador [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/165779<br>TESIS

The overall goals of this dissertation are to investigate the sustainability of the built environment, holistically, by assessing its Triple Bottom Line (TBL): environmental, economic, and social impacts, as well as propose cost-effective, socially acceptable, and environmentally benign policies using several decision support models. This research is anticipated to transform life cycle assessment (LCA) of the built environment by using a TBL framework, integrated with economic input-output analysis, simulation, and multi-criteria optimization tools. The major objectives of the outlined research are to (1) build a system-based TBL sustainability assessment framework for the sustainable built environment, by (a) advancing a national TBL-LCA model which is not available for the United States of America; (b) extending the integrated sustainability framework through environmental, economic, and social sustainability indicators; and (2) develop a system-based analysis toolbox for sustainable decisions including Monte Carlo simulation and multi-criteria compromise programming. When analyzing the total sustainability impacts by each U.S. construction sector, “Residential Permanent Single and Multi-Family Structures" and "Other Non-residential Structures" are found to have the highest environmental, economic, and social impacts compared to other construction sectors. The analysis results also show that indirect suppliers of construction sectors have the largest sustainability impacts compared to on-site activities. For example, for all U.S. construction sectors, on-site construction processes are found to be responsible for less than 5 % of total water consumption, whereas about 95 % of total water use can be attributed to indirect suppliers. In addition, Scope 3 emissions are responsible for the highest carbon emissions compared to Scope 1 and 2. Therefore, using narrowly defined system boundaries by ignoring supply chain-related impacts can result in underestimation of TBL sustainability impacts of the U.S. construction industry. Residential buildings have higher shares in the most of the sustainability impact categories compared to other construction sectors. Analysis results revealed that construction phase, electricity use, and commuting played important role in much of the sustainability impact categories. Natural gas and electricity consumption accounted for 72% and 78% of the total energy consumed in the U.S. residential buildings. Also, the electricity use was the most dominant component of the environmental impacts with more than 50% of greenhouse gases emitted and energy used through all life stages. Furthermore, electricity generation was responsible for 60% of the total water withdrawal of residential buildings, which was even greater than the direct water consumption in residential buildings. In addition, construction phase had the largest share in income category with 60% of the total income generated through residential building's life cycle. Residential construction sector and its supply chain were responsible for 36% of the import, 40% of the gross operating surplus, and 50% of the gross domestic product. The most sensitive parameters were construction activities and its multiplier in most the sustainability impact categories. In addition, several emerging pavement types are analyzed using a hybrid TBL-LCA framework. Warm-mix Asphalts (WMAs) did not perform better in terms of environmental impacts compared to Hot-mix Asphalt (HMA). Asphamin&"174; WMA was found to have the highest environmental and socio-economic impacts compared to other pavement types. Material extractions and processing phase had the highest contribution to all environmental impact indicators that shows the importance of cleaner production strategies for pavement materials. Based on stochastic compromise programming results, in a balanced weighting situation, Sasobit&"174; WMA had the highest percentage of allocation (61%), while only socio-economic aspects matter, Asphamin&"174; WMA had the largest share (57%) among the WMA and HMA mixtures. The optimization results also supported the significance of an increased WMA use in the United States for sustainable pavement construction. Consequently, the outcomes of this dissertation will advance the state of the art in built environment sustainability research by investigating novel efficient methodologies capable of offering optimized policy recommendations by taking the TBL impacts of supply chain into account. It is expected that the results of this research would facilitate better sustainability decisions in the adoption of system-based TBL thinking in the construction field.<br>Ph.D.<br>Doctorate<br>Civil, Environmental, and Construction Engineering<br>Engineering and Computer Science<br>Civil Engineering

Construction hors site (CHS), méthodes de construction modernes (MCM), fabrication hors site (FHS) et production hors site (PHS) sont tous des termes cités dans la littérature comme étant des solutions possibles pour résoudre les problèmes des délais, de qualité et de coût associés aux méthodes de construction traditionnelles. La mise en œuvre réussie de ces méthodes dans le cadre d'un projet de construction nécessite une analyse systématique et une prise de décision anticipée fondée sur des facteurs spécifiques au projet. Il n'existe pas actuellement une approche systémique efficace capable de répondre à l'évolution des besoins, de faire face à la complexité croissante des projets de construction et de prendre en compte les innovations, les technologies et les réglementations récemment mises au point. À cet égard, ces sujets ont été abordés dans la présente thèse de doctorat. L'objectif de ce travail de recherche est le développement d'un outil d'aide à la décision pour le choix des modes constructifs. Nous proposons un modèle de prise de décision multi-niveaux. Le premier niveau concerne l’étude de faisabilité et évalue l'applicabilité de la construction hors site. Le deuxième niveau propose une approche intégrée de prise de décision qui combine la méthode AHP (Analytic Hierarchy Process) et la méthode PROMETHEE. La combinaison des deux méthodes permet une évaluation minutieuse des différents modes constructifs et des scénarios pour un projet de construction donné. La méthodologie de recherche adoptée est une approche mixte, combinant des méthodes de collecte de données quantitatives et qualitatives, incluant trois études de cas, dix entretiens semi-structurés, des questionnaires avec différents acteurs de la construction, et un focus group avec neuf ingénieurs en construction. L'étude identifie d'abord les avantages et les limites de la construction hors site. Elle met ensuite en exergue les facteurs qui influencent les décisions relatives à l'utilisation de la construction hors site. Ensuite, elle présente et décrit un outil d’aide à la décision informatisé pensé pour aider les équipes projet dans leur processus décisionnel. Enfin, l'outil d'aide à la décision proposé a été testé auprès des professionnels de la construction sous la forme de deux études de cas. Ces dernières constituent une validation du modèle et l’outil informatisé, ainsi qu’une preuve de leur utilité et de son efficacité d’usage dans le processus décisionnel en construction<br>Offsite Construction (OSC), Modern Methods of Construction (MMC), Offsite Manufacturing (OSM), and Offsite Production (OSP) are all terms cited as being possible solutions for addressing time, quality and cost concerns associated with traditional construction method. Successful implementation of these methods on a particular project requires systematic analysis and early decision making based on specific factors of the project. There is a lack of an efficient systematic approach that is able to match the changing needs, deal with the growing complexity of building projects and take into consideration recently developed innovations, technologies and regulations. In this respect these issues have been addressed in this research study. The objective of this dissertation is the development of an early- phase decision tool to support the general contractor in selecting construction methods. We propose a multi-level decision framework. The first level conducts a feasibility study and evaluates the applicability of offsite construction. The second level proposes an integrated approach for the decision-making problem that combines the Analytical Hierarchy Process (AHP) and the Preference Ranking Organization Method for Enrichment Evaluations (PROMETHEE). The combination of both approaches enables a careful evaluation of different construction methods and scenarios for the same project. The research methodology adopted is a mixed approach, combining quantitative and qualitative data collection methods, including three case studies, 10 semi-structured interviews, questionnaires with different construction stakeholders and focus groups with 9 construction engineers. The study first identifies the advantages and limitation of offsite construction. Second, it highlights the factors influencing decisions on the use of prework. Then, it presents and describes a computerized tool to aid project teams in the decision-making process. Finally, the decision-making tool was tested and with construction practitioners on three different case studies. They validate that the developed framework and tool are useful and effective in the decision-making process

Les systèmes de cogénération (SC) sont largement définis par la production simultanée ou coïncidente de la production combinée de chaleur et d'électricité. L’idée de la cogénération revêt une importance particulière puisqu’elle est un outil de réduction des émissions à effet de serre. Comme les systèmes électriques ont été développés selon les carburants et leur utilisation énergétique, de même, les SC ont été développés afin d'utiliser l'énergie possible du carburant pour produire de l’électricité et de la chaleur. La décentralisation de la production électrique est désormais un événement existant. La favorisation maximale de l’électricité d’origine renouvelable ou des systèmes de cogénération, a abouti à cette décentralisation formant une partie de la production électrique. Cette thèse est appliquée au cas du système électrique libanais. Elle sert à évaluer la puissance optimale de cogénération qui doit être installée par le secteur public ou le secteur privé, ainsi que la mise en évidence des impacts économiques et environnementaux dus à l’intégration des SC et des énergies renouvelables dans le réseau. Dans ce travail de thèse, nous nous sommes intéressés à l’intégration des systèmes de cogénération dans un réseau électrique. Nous avons travaillé sur deux thèmes principaux et les avons appliqués au cas du réseau électrique libanais. Le premier thème principal est l’innovation d’une stratégie de prise de décision qui sert à trouver une puissance de cogénération respectant l’économie et l’environnement. Le second thème principal est l’optimisation et le contrôle du réseau électrique en fonction des énergies renouvelables (ER) et des SC intégrés. Les deux thèmes cités sont ensuite appliqués au cas du réseau électrique libanais pour montrer les avantages de l’intégration des SC et des ER dans ce réseau<br>Cogeneration systems (CS) are largely defined by the simultaneous or coincident production of combined heat and power. The idea of cogeneration is of particular importance since it is a tool for reducing greenhouse gases emissions. As electrical systems have been developed according to the fuel and energy use, the CS have been developed to profit from the possible potential of the fuel energy to produce electricity and heat. Decentralization of power generation is considered an important fact. The maximum use of electricity from renewable sources or cogeneration systems, has leaded to the decentralization of power generation.This thesis is applied to the Lebanese electrical system. It is used to assess the optimum cogeneration power to be installed by the public sector or the private sector, as well as highlighting the economic and environmental impacts due to the integration of the CS and renewables into the grid. In this thesis, we focused on the integration of cogeneration systems into a grid. We worked on two major themes and have applied them to the case of the Lebanese electrical grid. The first main theme is the innovation of a new decision making strategy to find the cogeneration power respecting the economy and the environment. The second main theme is the optimization and the control of the electrical grid due to the integration of renewable energy (RE) and CS. The two themes cited are then applied to the case of the Lebanese electrical grid to show the benefits of the integration of RE and CS into this grid

Aujourd'hui, les systèmes industriels deviennent de plus en plus complexes. Cette complexité est due d’une part à la structure du système qui ne se résume pas à des structures classiques en fiabilité, d’autre part à la prise en compte de composants présentant des phénomènes de dégradation graduelle que des systèmes de monitoring permettent de surveiller. Ceci mène à l'objectif de cette thèse portant sur le développement des stratégies de maintenance prévisionnelle pour des systèmes multi-composants complexes. Les politiques envisagées proposent notamment des stratégies de regroupement de composants permettant de tirer des dépendances économiques identifiées. Des facteurs d'importance permettant de prendre en compte la structure du système et la dépendance économique sont développés et combinés avec les évaluations de fiabilité prévisionnelle des composants pour l’élaboration de règles de décision de regroupement. De plus, un couplage des règles de décision de maintenance et de gestion des stocks est également étudié. L’ensemble des études menées montrent l’intérêt de la prise en compte de la fiabilité prévisionnelle des composants, des dépendances économiques et de la structure complexe du système dans l'aide à la décision de maintenance et de gestion des stocks. L’avantage des stratégies développées est vérifié en les comparant à d’autres existantes dans la littérature<br>Today, industrial systems become more and more complex. The complexity is due partly to the structure of the system that cannot be reduced to classic structure reliability (series structures, parallel structures, series-parallel structures, etc), secondly the consideration of components with gradual degradation phenomena that can be monitored. This leads to the main purpose of this thesis on the development of predictive maintenance strategies for complex multi-component systems. The proposed policies provide maintenance grouping strategies to take advantage of the economic dependence between components. The predictive reliability of components and importance measures allowing taking into account the structure of the system and economic dependence are developed to construct the grouping decision rules. Moreover, a joint decision rule for maintenance and spare parts provisioning is also studied.All the conducted studies show the interest in the consideration of the predictive reliability of components, economic dependencies as well as complex structure of the system in maintenance decisions and spare parts provisioning. The advantage of the developed strategies is confirmed by comparing with the other existing strategies in the literature

Aujourd'hui, la fabrication additive (FA) fait évoluer le monde de la fabrication grâce à ses capacités de production de formes complexes couche par couche. L'approche de conception pour la fabrication (DFM) aide à considérer les contraintes de FA et à maîtriser les caractéristiques du produit dans la gestion de son cycle de vie. Plusieurs études sont consacrées à l'approche de conception intégrée pour la FA, mais aucune approche ne prend en compte toutes les étapes du cycle de vie du produit dans le niveau d'optimisation de sa conception et de sa fabrication. Ainsi, cette thèse fournit une approche DFM pour la FA afin d'étudier simultanément différents attributs, contraintes et critères de conception et de fabrication dès la définition du produit. L'approche Peau-Squelette modélise la première définition du produit. Il contient une analyse fonctionnelle, un modèle d'usage et un modèle de fabrication. Dans ce travail, un nouveau moteur de résolution, qui agit à l’interface du modèle de produit et du modèle de fabrication, est proposé grâce à l'analyse des technologies FA et de leurs paramètres et critères. Ce moteur repose sur un problème d'optimisation bi-objectif pour minimiser le temps de production et la masse du matériau en proposant les solutions optimales pour les propriétés mécaniques et la rugosité du produit. Cette méthodologie permet de définir le modèle de produit. L'approche est mise en œuvre à travers une première technologie de dépôt par fil fondu (FDM) pour la production de deux études de cas<br>Nowadays, Additive Manufacturing (AM) evolves the manufacturing world by its capabilities for production of the complex shapes layer by layer. Design For Manufacturing (DFM) approach helps to overcome the AM constraints and mastering product features in product lifecycle. Several studies are devoted to integrated design approach for AM, but there is no approach that considers all product life cycle steps in optimization level for product and manufacturing process. So, this thesis provides a DFM approach for AM to investigate simultaneously different attributes, constraints, and criteria of design and manufacturing in product definition. Skin-Skeleton approach models the first definition of product and AM. It contains functional analysis, usage model, and manufacturing model. In this work, a novel interface processing engine as an interface between product and manufacturing model is developed through analysis of AM technologies and their parameters and criteria. This engine relies on a bi-objective optimization problem to minimize production time and material mass under limitation of mechanical properties and roughness of the product to obtain the optimal manufacturing parameters. This methodology permits to define the product model. The approach is implemented into Fused Deposition Modeling to verify the methodology through two case studies

L’objectif de ce travail est de développer un cadre méthodologique et générique d’éco-conception de procédés chimiques couplant des outils de modélisation et de simulation traditionnels de procédés (HYSYS, COCO, ProSimPlus et Ariane), d’Analyse du Cycle de Vie (ACV), d’optimisation multiobjectif basée sur des Algorithmes Génétiques et enfin des outils d’aide à la décision multicritère (ELECTRE, PROMETHEE, M-TOPSIS). Il s’agit de généraliser, d’automatiser et d’optimiser l’évaluation des impacts environnementaux au stade préliminaire de la conception d’un procédé chimique. L’approche comprend trois étapes principales. Les deux premières correspondent d’une part aux phases d’analyse de l’inventaire par calcul des bilans de matière et d’énergie et d’autre part à l’évaluation environnementale par ACV. Le problème du manque d’information ou de l’imprécision dans les bases de données classiques en ACV pour la production d’énergie notamment sous forme de vapeur largement utilisée dans les procédés a reçu une attention particulière. Une solution proposée consiste à utiliser un simulateur de procédés de production d’utilités (Ariane, ProSim SA) pour contribuer à alimenter la base de données environnementale en tenant compte de variations sur les conditions opératoires ou sur les technologies utilisées. Des sous-modules « énergie » sont ainsi proposés pour calculer les émissions relatives aux impacts liés à l’utilisation de l’énergie dans les procédés. La troisième étape réalise l’interaction entre les deux premières phases et l’optimisation multi-objectif qui met en jeu des critères économiques et environnementaux. Elle conduit à des solutions de compromis le long du front de Pareto à partir desquelles les meilleures sont choisies à l’aide de méthodes d’aide à la décision. L’approche est appliquée à des procédés de production continus : production de benzène par hydrodéalkylation du toluène HDA et production de biodiesel à partir d’huiles végétales. Une stratégie à plusieurs niveaux est mise en oeuvre pour l'analyse de l'optimisation multi-objectif. Elle est utilisée dans les deux cas d'étude afin d'analyser les comportements antagonistes des critères<br>The objective of this work is to propose an integrated and generic framework for eco-design coupling traditional modelling and flowsheeting simulation tools (HYSYS, COCO, ProSimPlus and Ariane), Life Cycle Assessment, multi-objective optimization based on Genetic Algorithms and multiple criteria decision-making methods MCDM (Multiple Choice Decision Making, such as ELECTRE, PROMETHEE, M-TOPSIS) that generalizes, automates and optimizes the evaluation of the environmental criteria at earlier design stage. The approach consists of three main stages. The first two steps correspond respectively to process inventory analysis based on mass and energy balances and impact assessment phases of LCA methodology. Specific attention is paid to the main issues that can be encountered with database and impact assessment i.e. incomplete or missing information, or approximate information that does not match exactly the real situation that may introduce a bias in the environmental impact estimation. A process simulation tool dedicated to production utilities, Ariane, ProSim SA is used to fill environmental database gap, by the design of specific energy sub modules, so that the life cycle energy related emissions for any given process can be computed. The third stage of the methodology is based on the interaction of the previous steps with process simulation for environmental impact assessment and cost estimation through a computational framework. The use of multi-objective optimization methods generally leads to a set of efficient solutions, the so-called Pareto front. The next step consists in identifying the best ones through MCDM methods. The approach is applied to two processes operating in continuous mode. The capabilities of the methodology are highlighted through these case studies (benzene production by HDA process and biodiesel production from vegetable oils). A multi-level assessment for multi-objective optimization is implemented for both cases, the explored pathways depending on the analysis and antagonist behaviour of the criteria

Cette thèse est dédiée à l’optimisation de composants et de systèmes énergétiques avec une application dans le secteur résidentiel. La méthodologie développée est composée d’une analyse de sensibilité, d’une optimisation multi-objectif et d’une aide à la décision multicritère pour sélectionner le meilleur compromis. Tout d’abord, une optimisation d’un système de production d’eau chaude sanitaire est mise en œuvre numériquement et s’appuie sur un banc expérimental du laboratoire IUSTI. Cette étude a pour but d’optimiser, en fonction de différents profils de puisage, les performances d’un dispositif basé sur une pompe à chaleur en améliorant sa régulation. Ensuite, la procédure est appliquée à l’optimisation paramétrique d’un échangeur air-sol (EAS). Le système utilise les ressources géothermiques pour chauffer ou rafraîchir l’air d’un bâtiment par ventilation. Le modèle de l’échangeur air-sol a été validé expérimentalement avec une plateforme géothermique existante à Strasbourg. Un système qui couple un EAS, une ventilation double flux et une pompe à chaleur est également étudié. Le dimensionnement optimal permet d’obtenir un système qui demeure à la fois rentable, autonome et performant pour les différents climats considérés. Enfin, le processus est appliqué à l’optimisation topologique des échangeurs de chaleur. La procédure identifie l’ensemble des topologies qui possède un bon compromis entre les pertes de charge et les transferts thermiques. La méthodologie d'aide à la décision sélectionne la topologie finale qui permet d’avoir une répartition optimisée d’éléments solides afin d’obtenir le meilleur compromis entre ces objectifs<br>This thesis is dedicated to the optimization of components and energy systems with an application in the residential sector. The methodology developed is composed of a sensitivity analysis, a multi-objective optimization and a multi-criteria decision-making aid to select the best compromise.First of all, an optimization of a domestic hot water production system is implemented numerically and is based on an experimental set-up in the IUSTI laboratory. The aim of this study is to optimize the performance of a heat pump-based system by improving its regulation according to different drawing profiles. Then, the procedure is applied to the parametric optimization of an earth-air heat exchanger (EAHE). The system uses geothermal resources to preheat or cool the air in a building by ventilation. The model of the earth-air heat exchanger has been experimentally validated with an existing geothermal platform at Strasbourg. A system that combines an EAHE, a double flow ventilation and a heat pump is also studied. Optimal sizing makes it possible to obtain a system that is profitable, autonomous and efficient for the different climates considered. Finally, the process is applied to the topological optimization of heat exchangers. The procedure identifies the set of topologies that has a good compromise between pressure drops and heat transfer. The decision aid methodology selects the final topology that allows to have an optimized distribution of solid elements in order to obtain the best compromise between these objectives