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Dächert, Kerstin [Verfasser]. "Adaptive Parametric Scalarizations in Multicriteria Optimization / Kerstin Dächert." Wuppertal : Universitätsbibliothek Wuppertal, 2014. http://d-nb.info/1054221308/34.
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Filomeno, Coelho Rajan. "Multicriteria optimization with expert rules for mechanical design." Doctoral thesis, Universite Libre de Bruxelles, 2004. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/211184.
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Though lots of numerical methods have been proposed in the literature to optimize me-chanical structures at the final stage of the design process, few designers use these tools since the first stage. However, a minor modification at the first step can bring significant change to the global performances of the structure. Usually, during the initial stage, models are based on theoretical and empirical equations, which are often characterized by mixed variables: continuous (e.g. geometrical dimensions), discrete (e.g. the cross section of a beam available in a catalogue) and/or integer (e.g. the number of layers in a composite material). Furthermore, the functions involved may be non differentiable, or even discontinuous. Therefore, classical algorithms based on the computation of sensi-tivities are no more applicable. Consequently, to solve these problems, the most wide-spread meta-heuristic methods are evolutionary algorithms (EAs), which work as follows: the best individuals among an initial population of randomly generated potential solutions are favoured and com-bined (by specific operators like crossover and mutation) in order to create potentially better individuals at the next generation. The creation of new generations is repeated till the convergence is reached. The ability of EAs to explore widely the design space is useful to solve single-objective unconstrained optimization problems, because it gener-ally prevents from getting trapped into a local optimum, but it is also well known that they do not perform very efficiently in the presence of constraints. Furthermore, in many industrial applications, multiple objectives are pursued together.
Therefore, to take into account the constrained and multicriteria aspects of optimization problems in EAs, a new method called PAMUC (Preferences Applied to MUltiobjectiv-ity and Constraints) has been proposed in this dissertation. First the user has to assign weights to the m objectives. Then, an additional objective function is built by linearly aggregating the normalized constraints. Finally, a multicriteria decision aid method, PROMETHEE II, is used in order to rank the individuals of the population following the m+1 objectives.
PAMUC has been validated on standard multiobjective test cases, as well as on the pa-rametrical optimization of the purge valve and the feed valve of the Vinci engine, both designed by Techspace Aero for launcher Ariane 5.
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Doctorat en sciences appliquées
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Zhang, Tianfang. "Machine learning multicriteria optimization in radiation therapy treatment planning." Thesis, KTH, Matematisk statistik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-257509.
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In radiation therapy treatment planning, recent works have used machine learning based on historically delivered plans to automate the process of producing clinically acceptable plans. Compared to traditional approaches such as repeated weighted-sum optimization or multicriteria optimization (MCO), automated planning methods have, in general, the benefits of low computational times and minimal user interaction, but on the other hand lack the flexibility associated with general-purpose frameworks such as MCO. Machine learning approaches can be especially sensitive to deviations in their dose prediction due to certain properties of the optimization functions usually used for dose mimicking and, moreover, suffer from the fact that there exists no general causality between prediction accuracy and optimized plan quality.In this thesis, we present a means of unifying ideas from machine learning planning methods with the well-established MCO framework. More precisely, given prior knowledge in the form of either a previously optimized plan or a set of historically delivered clinical plans, we are able to automatically generate Pareto optimal plans spanning a dose region corresponding to plans which are achievable as well as clinically acceptable. For the former case, this is achieved by introducing dose--volume constraints; for the latter case, this is achieved by fitting a weighted-data Gaussian mixture model on pre-defined dose statistics using the expectation--maximization algorithm, modifying it with exponential tilting and using specially developed optimization functions to take into account prediction uncertainties.Numerical results for conceptual demonstration are obtained for a prostate cancer case with treatment delivered by a volumetric-modulated arc therapy technique, where it is shown that the methods developed in the thesis are successful in automatically generating Pareto optimal plans of satisfactory quality and diversity, while excluding clinically irrelevant dose regions. For the case of using historical plans as prior knowledge, the computational times are significantly shorter than those typical of conventional MCO.Inom strålterapiplanering har den senaste forskningen använt maskininlärning baserat på historiskt levererade planer för att automatisera den process i vilken kliniskt acceptabla planer produceras. Jämfört med traditionella angreppssätt, såsom upprepad optimering av en viktad målfunktion eller flermålsoptimering (MCO), har automatiska planeringsmetoder generellt sett fördelarna av lägre beräkningstider och minimal användarinteraktion, men saknar däremot flexibiliteten hos allmänna ramverk som exempelvis MCO. Maskininlärningsmetoder kan vara speciellt känsliga för avvikelser i dosprediktionssteget på grund av särskilda egenskaper hos de optimeringsfunktioner som vanligtvis används för att återskapa dosfördelningar, och lider dessutom av problemet att det inte finns något allmängiltigt orsakssamband mellan prediktionsnoggrannhet och kvalitet hos optimerad plan. I detta arbete presenterar vi ett sätt att förena idéer från maskininlärningsbaserade planeringsmetoder med det väletablerade MCO-ramverket. Mer precist kan vi, givet förkunskaper i form av antingen en tidigare optimerad plan eller en uppsättning av historiskt levererade kliniska planer, automatiskt generera Paretooptimala planer som täcker en dosregion motsvarande uppnåeliga såväl som kliniskt acceptabla planer. I det förra fallet görs detta genom att introducera dos--volym-bivillkor; i det senare fallet görs detta genom att anpassa en gaussisk blandningsmodell med viktade data med förväntning--maximering-algoritmen, modifiera den med exponentiell lutning och sedan använda speciellt utvecklade optimeringsfunktioner för att ta hänsyn till prediktionsosäkerheter.Numeriska resultat för konceptuell demonstration erhålls för ett fall av prostatacancer varvid behandlingen levererades med volymetriskt modulerad bågterapi, där det visas att metoderna utvecklade i detta arbete är framgångsrika i att automatiskt generera Paretooptimala planer med tillfredsställande kvalitet och variation medan kliniskt irrelevanta dosregioner utesluts. I fallet då historiska planer används som förkunskap är beräkningstiderna markant kortare än för konventionell MCO.
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Sánchez, Corrales Helem Sabina. "Multi-objective optimization and multicriteria design of PI /PID controllers." Doctoral thesis, Universitat Autònoma de Barcelona, 2016. http://hdl.handle.net/10803/393990.
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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.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.
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Bokrantz, Rasmus. "Multicriteria optimization for managing tradeoffs in radiation therapy treatment planning." Doctoral thesis, KTH, Optimeringslära och systemteori, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-122663.
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Treatment planning for radiation therapy inherently involves tradeoffs, such as between tumor control and normal tissue sparing, between time-efficiency and dose quality, and between nominal plan quality and robustness. The purpose of this thesis is to develop methods that can facilitate decision making related to such tradeoffs. The main focus of the thesis is on multicriteria optimization methods where a representative set of treatment plans are first calculated and the most appropriate plan contained in this representation then selected by the treatment planner through continuous interpolation between the precalculated alternatives. These alternatives constitute a subset of the set of Pareto optimal plans, meaning plans such that no criterion can be improved without a sacrifice in another. Approximation of Pareto optimal sets is first studied with respect to fluence map optimization for intensity-modulated radiation therapy. The approximation error of a discrete representation is minimized by calculation of points one at the time at the location where the distance between an inner and outer approximation of the Pareto set currently attains its maximum. A technique for calculating this distance that is orders of magnitude more efficient than the best previous method is presented. A generalization to distributed computational environments is also proposed. Approximation of Pareto optimal sets is also considered with respect to direct machine parameter optimization. Optimization of this form is used to calculate representations where any interpolated treatment plan is directly deliverable. The fact that finite representations of Pareto optimal sets have approximation errors with respect to Pareto optimality is addressed by a technique that removes these errors by a projection onto the exact Pareto set. Projections are also studied subject to constraints that prevent the dose-volume histogram from deteriorating. Multicriteria optimization is extended to treatment planning for volumetric-modulated arc therapy and intensity-modulated proton therapy. Proton therapy plans that are robust against geometric errors are calculated by optimization of the worst case outcome. The theory for multicriteria optimization is extended to accommodate this formulation. Worst case optimization is shown to be preferable to a previous more conservative method that also protects against uncertainties which cannot be realized in practice.En viktig aspekt av planering av strålterapibehandlingar är avvägningar mellan behandlingsmål vilka står i konflikt med varandra. Exempel på sådana avvägningar är mellan tumörkontroll och dos till omkringliggande frisk vävnad, mellan behandlingstid och doskvalitet, och mellan nominell plankvalitet och robusthet med avseende på geometriska fel. Denna avhandling syftar till att utveckla metoder som kan underlätta beslutsfattande kring motstridiga behandlingsmål. Primärt studeras en metod för flermålsoptimering där behandlingsplanen väljs genom kontinuerlig interpolation över ett representativt urval av förberäknade alternativ. De förberäknade behandlingsplanerna utgör en delmängd av de Paretooptimala planerna, det vill säga de planer sådana att en förbättring enligt ett kriterium inte kan ske annat än genom en försämring enligt ett annat. Beräkning av en approximativ representation av mängden av Paretooptimala planer studeras först med avseende på fluensoptimering för intensitetsmodulerad strålterapi. Felet för den approximativa representationen minimeras genom att innesluta mängden av Paretooptimala planer mellan inre och yttre approximationer. Dessa approximationer förfinas iterativt genom att varje ny plan genereras där avståndet mellan approximationerna för tillfället är som störst. En teknik för att beräkna det maximala avståndet mellan approximationerna föreslås vilken är flera storleksordningar snabbare än den bästa tidigare kända metoden. En generalisering till distribuerade beräkningsmiljöer föreslås även. Approximation av mängden av Paretooptimala planer studeras även för direkt maskinparameteroptimering, som används för att beräkna representationer där varje interpolerad behandlingsplan är direkt levererbar. Det faktum att en ändlig representation av mängden av Paretooptimala lösningar har ett approximationsfel till Paretooptimalitet hanteras via en metod där en interpolerad behandlingsplan projiceras på Paretomängden. Projektioner studeras även under bivillkor som förhindrar att den interpolerade planens dos-volym histogram kan försämras. Flermålsoptimering utökas till planering av rotationsterapi och intensitetsmodulerad protonterapi. Protonplaner som är robusta mot geometriska fel beräknas genom optimering med avseende på det värsta möjliga utfallet av de föreliggande osäkerheterna. Flermålsoptimering utökas även teoretiskt till att innefatta denna formulering. Nyttan av värsta fallet-optimering jämfört med tidigare mer konservativa metoder som även skyddar mot osäkerheter som inte kan realiseras i praktiken demonstreras experimentellt.
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Schott, Jason R. (Jason Ramon). "Fault tolerant design using single and multicriteria genetic algorithm optimization." Thesis, Massachusetts Institute of Technology, 1995. http://hdl.handle.net/1721.1/11582.
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Arreola-Risa, Jesus S. "Multicriteria optimization for design of multivariate control charts for manufacturing processes." Diss., Georgia Institute of Technology, 1989. http://hdl.handle.net/1853/27997.
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Heiserer, Daniel F. [Verfasser]. "Fast Reanalysis for Large Scale Multicriteria Structural Optimization / Daniel F Heiserer." Aachen : Shaker, 2005. http://d-nb.info/1186576960/34.
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Sarma, Kamal C. "Fuzzy discrete multicriteria cost optimization of steel structures using genetic algorithm /." The Ohio State University, 2001. http://rave.ohiolink.edu/etdc/view?acc_num=osu1488205318509081.
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Buonanno, Michael Alexander. "A Method for Aircraft Concept Exploration using Multicriteria Interactive Genetic Algorithms." Diss., Georgia Institute of Technology, 2005. http://hdl.handle.net/1853/7571.
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The problem of aircraft concept selection has become increasingly difficult in recent years due to changes in the primary evaluation criteria of concepts. In the past, performance was often the primary discriminator whereas modern programs have placed increased emphasis on factors such as environmental impact, economics, supportability, aesthetics, and other metrics. The revolutionary nature of the vehicles required to simultaneously meet these conflicting requirements has prompted a shift from design using historical data regression techniques for metric prediction to the use of sophisticated physics-based analysis tools that are capable of analyzing designs outside of the historical database. The use of optimization methods with these physics-based tools, however, has proven difficult because of the tendency of optimizers to exploit assumptions present in the models and drive the design towards a solution which, while promising to the computer, may be infeasible due to factors not considered by the computer codes. In addition to this difficulty, the number of discrete options available at this stage may be unmanageable due to the combinatorial nature of the concept selection problem, leading the analyst to select a sub-optimum baseline vehicle. Some extremely important concept decisions, such as the type of control surface arrangement to use, are frequently made without sufficient understanding of their impact on the important system metrics due to a lack of historical guidance, computational resources, or analysis tools.
This thesis discusses the difficulties associated with revolutionary system design, and introduces several new techniques designed to remedy them. First, an interactive design method has been developed that allows the designer to provide feedback to a numerical optimization algorithm during runtime, thereby preventing the optimizer from exploiting weaknesses in the analytical model. This method can be used to account for subjective criteria, or as a crude measure of un-modeled quantitative criteria. Other contributions of the work include a modified Structured Genetic Algorithm that enables the efficient search of large combinatorial design hierarchies and an improved multi-objective optimization procedure that can effectively optimize several objectives simultaneously. A new conceptual design method has been created by drawing upon each of these new capabilities and aspects of more traditional design methods.
The ability of this new technique to assist in the design of revolutionary vehicles has been demonstrated using a problem of contemporary interest: the concept exploration of a supersonic business jet. This problem was found to be a good demonstration case because of its novelty and unique requirements, and the results of this proof of concept exercise indicate that the new method is effective at providing additional insight into the relationship between a vehicle's requirements and its favorable attributes.
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Kuhn, Tobias [Verfasser], and Stefan [Akademischer Betreuer] Ruzika. "Representative Systems and Decision Support for Multicriteria Optimization Problems / Tobias Kuhn. Betreuer: Stefan Ruzika." Kaiserslautern : Technische Universität Kaiserslautern, 2015. http://d-nb.info/1078504431/34.
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Bokrantz, Rasmus, and Kaisa Miettinen. "Improved plan quality in multicriteria radiation therapy optimization by projections onto the Pareto surface." KTH, Optimeringslära och systemteori, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-122664.
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We consider an approach to multicriteria radiation therapy optimization where the clinical treatment plan is selected from a representationof the set of Pareto optimal treatment plans in the form of a discrete setof plans and their combinations. The approximate nature of this representation implies that a selected plan in general has an approximationerror with respect to Pareto optimality. To assess and, if necessary, improve the quality of such plans, a technique is suggested that eliminatesthe approximation error of a given treatment plan by a projection ontothe Pareto surface. A more elaborate form of projection is also suggested that requires the projected solution to be not only as good asthe input plan in terms of objective function values, but also equallygood or better with respect to the three-dimensional dose distribution.The versatility of the suggested technique is demonstrated by application to planning for step-and-shoot and sliding window delivery ofintensity-modulated radiation therapy, and planning for spot-scanneddelivery of intensity-modulated proton therapy. Our numerical resultsshow that the proposed projections generally lead to improved sparingof organs at risk and a higher degree of dose conformity compared towhen projections are not performed.QC 20130527
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Pieume, Calice Olivier. "Multiobjective optimization approaches in bilevel optimization." Phd thesis, Université Paris-Est, 2011. http://tel.archives-ouvertes.fr/tel-00665605.
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This thesis addresses two important classes of optimization : multiobjective optimization and bilevel optimization. The investigation concerns their solution methods, applications, and possible links between them. First of all, we develop a procedure for solving Multiple Objective Linear Programming Problems (MOLPP). The method is based on a new characterization of efficient faces. It exploits the connectedness property of the set of ideal tableaux associated to degenerated points in the case of degeneracy. We also develop an approach for solving Bilevel Linear Programming Problems (BLPP). It is based on the result that an optimal solution of the BLPP is reachable at an extreme point of the underlying region. Consequently, we develop a pivoting technique to find the global optimal solution on an expanded tableau that represents the data of the BLPP. The solutions obtained by our algorithm on some problems available in the literature show that these problems were until now wrongly solved. Some applications of these two areas of optimization problems are explored. An application of multicriteria optimization techniques for finding an optimal planning for the distribution of electrical energy in Cameroon is provided. Similary, a bilevel optimization model that could permit to protect any economic sector where local initiatives are threatened is proposed. Finally, the relationship between the two classes of optimization is investigated. We first look at the conditions that guarantee that the optimal solution of a given BPP is Pareto optimal for both upper and lower level objective functions. We then introduce a new relation that establishes a link between MOLPP and BLPP. Moreover, we show that, to solve a BPP, it is possible to solve two artificial M0PPs. In addition, we explore Bilevel Multiobjective Programming Problem (BMPP), a case of BPP where each decision maker (DM) has more than one objective function. Given a MPP, we show how to construct two artificial M0PPs such that any point that is efficient for both problems is also efficient for the BMPP. For the linear case specially, we introduce an artificial MOLPP such that its resolution can permit to generate the whole feasible set of the leader DM. Based on this result and depending on whether the leader can evaluate or not his preferences for his different objective functions, two approaches for obtaining efficient solutions are presented
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Іванов, Віталій Олександрович, Виталий Александрович Иванов, and Vitalii Oleksandrovych Ivanov. "Система багатокритеріальної оптимізації компоновок верстатних пристроїв." Thesis, Вид-во СумДУ, 2010. http://essuir.sumdu.edu.ua/handle/123456789/5421.
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Kurdi, Mohammad H. "Robust multicriteria optimization of surface location error and material removal rate in high-speed milling under uncertainty." [Gainesville, Fla.] : University of Florida, 2005. http://purl.fcla.edu/fcla/etd/UFE0011626.
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Sarrazin, Renaud. "Multiobjective Optimization and Multicriteria Decision Aid Applied to the Evaluation of Road Projects at the Design Stage." Doctoral thesis, Universite Libre de Bruxelles, 2015. https://dipot.ulb.ac.be/dspace/bitstream/2013/222235/6/contrat.msg.
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Constructing a road is a complex process that may be represented as a series of correlated steps, from the planning to the construction and usage of the new road. At the heart of this process, the preliminary and detailed design stages are key elements that will ensure the quality and the adequacy of the final solution regarding the constraints and objectives of the project. In particular, infrastructure layout and design will have a strong impact on the global performances of the road in operational conditions. Among them, road safety, mobility, environment preservation, noise pollution limitation, economic feasibility and viability of the project, or even its socio-economic impact at the local level. Consequently, it is crucial to offer engineers and road planners some tools and methods that may assist them in designing and selecting the most efficient solutions considering the distinctive features of each design problem. In this work, a multicriteria analysis methodology is developed to carry out an integrated and preventive assessment of road projects at the design stage by considering both their safety performances and some economic and environmental aspects. Its purpose is to support design engineers in the analysis of their projects and the identification of innovative, consistent and effective solutions. The proposed methodology is composed of two main research frameworks. On the one hand, the road design problem is addressed by focusing successively on the structuring of the multicriteria problem, the identification of the approximate set of non-dominated solutions using a genetic algorithm (based on NSGA-II), and the application of the methodology to a real road design project. On the other hand, the methodological development of a multicriteria interval clustering model was performed (based on PROMETHEE). Due to the applicability of this model to the studied problem, the interactions between the two frameworks are also analysed.Doctorat en Sciences de l'ingénieur et technologie
The present PhD thesis is an aggregation of published contributions related to the application of multicriteria analysis to the evaluation of road projects at the design stage. The aim of the two introductory chapters is to offer a synthesised and critical presentation of the scientific contributions that constitute the PhD thesis. The complete version of the journal articles and preprints are found in Chapters 3 to 6. In the appendices, we also provide reprints of conference papers that are usually related to one of the main contributions of the thesis.
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Reynoso, Meza Gilberto. "Controller Tuning by Means of Evolutionary Multiobjective Optimization: a Holistic Multiobjective Optimization Design Procedure." Doctoral thesis, Editorial Universitat Politècnica de València, 2014. http://hdl.handle.net/10251/38248.
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This thesis is devoted toMultiobjective Optimization Design (MOOD) procedures
for controller tuning applications, by means of EvolutionaryMultiobjective
Optimization (EMO).With such purpose, developments on tools, procedures
and guidelines to facilitate this process have been realized.
This thesis is divided in four parts. The first part, namely Fundamentals,
is devoted on the one hand, to cover the theorical background required for
this Thesis; on the other hand, it provides a state of the art review on current
applications of MOOD for controller tuning.
The second part, Preliminary contributions on controller tuning, states early
contributions using the MOOD procedure for controller tuning, identifying
gaps on methodologies and tools used in this procedure. The contribution
within this part is to identify the gaps between the three fundamental steps of
theMOOD procedure: problemdefinition, search and decisionmaking. These
gaps are the basis for the developments presented in parts III and IV.
The third part, Contributions on MOOD tools, is devoted to improve the
tools used in Part II. Although applications on the scope of this thesis are related
to controller tuning, such improvements can also be used in other engineering
fields. The first contribution regards the decision making process,
where tools and guidelines for design concepts comparison in m-dimensional
Pareto fronts are stated. The second contribution focuses on amending the gap
between search process and decisionmaking. With this in mind, a mechanism
for preference inclusion within the evolutionary process is developed. With
this it is possible to calculate pertinent approximations of the Pareto front;
furthermore, it allows to deal efficiently with many-objective and constrained
optimization instances.
Finally, in the fourth part, Final contributions on controller tuning, a stochastic
sampling procedure for proportional-integral-derivative (PID) controllers
is proposed, to guarantee that (1) any sampled controller will stabilize the
closed loop and (2) any stabilizing controller could be sampled. Afterwards,
two control engineering benchmarks are solved using this sampling strategy,
the MOOD guidelines highlighted trough this Thesis for multivariable controller
tuning and the tools developed in Part III.Reynoso Meza, G. (2014). Controller Tuning by Means of Evolutionary Multiobjective Optimization: a Holistic Multiobjective Optimization Design Procedure [Tesis doctoral]. Editorial Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/38248
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Fredriksson, Albin. "Robust optimization of radiation therapy accounting for geometric uncertainty." Doctoral thesis, KTH, Optimeringslära och systemteori, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-122262.
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Geometric errors may compromise the quality of radiation therapy treatments. Optimization methods that account for errors can reduce their effects. The first paper of this thesis introduces minimax optimization to account for systematic range and setup errors in intensity-modulated proton therapy. The minimax method optimizes the worst case outcome of the errors within a given set. It is applied to three patient cases and shown to yield improved target coverage robustness and healthy structure sparing compared to conventional methods using margins, uniform beam doses, and density override. Information about the uncertainties enables the optimization to counterbalance the effects of errors. In the second paper, random setup errors of uncertain distribution---in addition to the systematic range and setup errors---are considered in a framework that enables scaling between expected value and minimax optimization. Experiments on a phantom show that the best and mean case tradeoffs between target coverage and critical structure sparing are similar between the methods of the framework, but that the worst case tradeoff improves with conservativeness. Minimax optimization only considers the worst case errors. When the planning criteria cannot be fulfilled for all errors, this may have an adverse effect on the plan quality. The third paper introduces a method for such cases that modifies the set of considered errors to maximize the probability of satisfying the planning criteria. For two cases treated with intensity-modulated photon and proton therapy, the method increased the number of satisfied criteria substantially. Grasping for a little less sometimes yields better plans. In the fourth paper, the theory for multicriteria optimization is extended to incorporate minimax optimization. Minimax optimization is shown to better exploit spatial information than objective-wise worst case optimization, which has previously been used for robust multicriteria optimization. The fifth and sixth papers introduce methods for improving treatment plans: one for deliverable Pareto surface navigation, which improves upon the Pareto set representations of previous methods; and one that minimizes healthy structure doses while constraining the doses of all structures not to deteriorate compared to a reference plan, thereby improving upon plans that have been reached with too weak planning goals.QC 20130516
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Gonçalves, Neto Jahyr 1980. "Algoritmo customizável por hierarquia para agendamento de tráfego de dados em redes Long Term Evolution (LTE)." [s.n.], 2014. http://repositorio.unicamp.br/jspui/handle/REPOSIP/261022.
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Orientador: Max Henrique Machado CostaTese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Elétrica e de Computação
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Resumo: Long Term Evolution (LTE), um padrão desenvolvido pelo 3rd Generation Partnership Project (3GPP), é atualmente a principal tecnologia 4G, provendo convergência tecnológica para esta geração de sistemas de comunicação celular. As redes LTE prometem velocidades de transmissão de dados em torno de 100 Mbps no canal de descida. Para esta alta taxa de transferência de dados, é necessário otimizar o uso dos recursos de rede. A tecnologia LTE utiliza técnicas de agendamento para a alocação de recursos de rádio com base nas condições do canal de comunicação. Este trabalho apresenta um algoritmo customizável para agendamento de dados multi-usuário no canal de descida das redes LTE que pode priorizar diferentes tipos de serviços selecionados. O esquema de agendamento proposto é uma versão modificada do agendador Proportional Fairness, que usa a técnica Analytic Hierarchy Process (AHP). Isto permite agregar critérios de desempenho para melhorar a alocação de recursos com base nas condições de tráfego gerais e um conjunto de prioridades de serviços predefinidos. A abordagem para essa customização é atribuir pesos para determinados parâmetros utilizados no processo de alocação de recursos, modificando assim a importância relativa desses parâmetros, criando uma hierarquia de critérios. É possível ainda adicionar critérios para diferentes tipos de dados através de matrizes de comparação. A matriz de comparação quantifica o julgamento do tomador de decisão no que se refere à importância relativa dos diferentes critérios. Assim, o agendador pode se tornar flexível e adaptável a diferentes cenários de tráfego. Exemplos são apresentados onde o tráfego de vídeo é priorizado
Abstract: Long Term Evolution (LTE), a standard developed by the 3rd Generation Partnership Project (3GPP), is currently the 4G mainstream technology, providing technology convergence for this generation of cellular communication systems. LTE networks promise data transmission rates of 100 Mbps in the downlink channel. For this high throughput it needs to optimize the use of network resources. LTE uses scheduling techniques for radio resource allocation based on communication channel conditions. This paper presents a customizable algorithm for multi-user data scheduling in the LTE downlink channel that can prioritize selected types of services. The proposed scheduling scheme is a modified version of the proportional fairness scheduler that uses Analytic Hierarchy Process (AHP) techniques. This allows to aggregate performance criteria to improve resource allocation based on general traffic conditions and a set of predefined service priorities. The approach for this customization is to assign weights to certain parameters used in the resource allocation process, thus modifying the relative importance of these parameters and creating a hierarchy of criteria. It is possible to add criteria for different types of data through comparison matrices. A comparison matrix quantifies the judgement of the decision maker with respect to the relative importance of different criteria. Thus the scheduler can be made flexible and adaptive to different traffic scenarios. Examples are given where video traffic is prioritized
Doutorado
Telecomunicações e Telemática
Doutor em Engenharia Elétrica
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Kanaan, Georges. "Conception, modélisation et optimisation d'un procédé continu d'élaboration d'une dispersion stabilisée de particules de polystyrène dans un polyéther polyol." Thesis, Vandoeuvre-les-Nancy, INPL, 2007. http://www.theses.fr/2007INPL073N/document.
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Ces travaux de recherche ont porté sur la mise au point et l’optimisation d’un nouveau procédé continu d’élaboration de dispersions stabilisées de particules de polystyrène dans un polyéther polyol. L’objectif final était de parvenir à minimiser le diamètre moyen des particules et à maximiser le taux de solide dans le mélange tout en maintenant sa stabilité.L’étude bibliographique a montré l’importance du choix du stabilisant et des paramètres opératoires du procédé dans la formation de la dispersion. Une étude préliminaire menée en réacteur fermé avec différents stabilisants a conduit à sélectionner un polyol greffé polystyrène. Une étude complète a été réalisée pour mettre au point la synthèse de ce stabilisant et la transposer à l’échelle pilote.Le passage au procédé continu a nécessité la construction d’une unité pilote complète centrée autour d’une extrudeuse bi-vis. Apres optimisation des conditions opératoires, deux paramètres influents ont été mis en évidence : le taux de stabilisant et la concentration du taux de solide. A partir d’un plan d’expériences complet, un modèle simple a été établi rendant compte de l'influence des conditions opératoires sur la qualité des dispersions. L’'optimisation multicritère du procédé et l’utilisation d'outils de génie décisionnel appropriés a permis de déterminer les meilleurs compromis pour l’élaboration des dispersionsThis study dealt with the development and the optimization of a new continuous process for making stable dispersions of polystyrene particles in a polyether polyol. The objective was to maximize the solid mass fraction in the mixture and to minimize the mean particles diameter, by maintaining stable dispersion. The bibliographical research showed the importance of the stabilizer and the operating conditions choices. Preliminary studies carried out in a batch reactor with different stabilizers led to select a polystyrene grafted polyol. A complete study of the synthesis of this stabilizer was carried out and transposed on a pilot scale.For to the continuous process, a complete pilot unit was built around a twin screw extruder. Once the operating conditions were optimized, two influencing parameters were identified (rate of stabilizer and concentration of polystyrene), thus an experimental design was developed. A simple model was created in order to determine the relationships between operating conditions and dispersion’s quality. The use of multicriteria optimization process allowed determining the best compromises for making stable dispersions
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Van, Assche Dimitri. "New methodological perspectives on PROMETHEE methods." Doctoral thesis, Universite Libre de Bruxelles, 2019. https://dipot.ulb.ac.be/dspace/bitstream/2013/287858/6/contratDV.pdf.
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A few methodological contributions to the PROMETHEE method, essentially based on 3 articles:-FlowSort parameters elicitation based on categorization examples;-PROMETHEE is Not Quadratic: An O (qnlog (n)) Algorithm;-Lexicographic constrained multicriteria ordered clustering.Doctorat en Sciences de l'ingénieur et technologie
info:eu-repo/semantics/nonPublished
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Payan, Alexia Paule Marie-Renee. "Enabling methods for the design and optimization of detection architectures." Diss., Georgia Institute of Technology, 2013. http://hdl.handle.net/1853/47688.
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The surveillance of geographic borders and critical infrastructures using limited sensor capability has always been a challenging task in many homeland security applications. While geographic borders may be very long and may go through isolated areas, critical assets may be large and numerous and may be located in highly populated areas. As a result, it is virtually impossible to secure each and every mile of border around the country, and each and every critical infrastructure inside the country. Most often, a compromise must be made between the percentage of border or critical asset covered by surveillance systems and the induced cost. Although threats to homeland security can be conceived to take place in many forms, those regarding illegal penetration of the air, land, and maritime domains under the cover of day-to-day activities have been identified to be of particular interest. For instance, the proliferation of drug smuggling, illegal immigration, international organized crime, resource exploitation, and more recently, modern piracy, require the strengthening of land border and maritime awareness and increasingly complex and challenging national security environments. The complexity and challenges associated to the above mission and to the protection of the homeland may explain why a methodology enabling the design and optimization of distributed detection systems architectures, able to provide accurate scanning of the air, land, and maritime domains, in a specific geographic and climatic environment, is a capital concern for the defense and protection community. This thesis proposes a methodology aimed at addressing the aforementioned gaps and challenges. The methodology particularly reformulates the problem in clear terms so as to facilitate the subsequent modeling and simulation of potential operational scenarios. The needs and challenges involved in the proposed study are investigated and a detailed description of a multidisciplinary strategy for the design and optimization of detection architectures in terms of detection performance and cost is provided. This implies the creation of a framework for the modeling and simulation of notional scenarios, as well as the development of improved methods for accurate optimization of detection architectures. More precisely, the present thesis describes a new approach to determining detection architectures able to provide effective coverage of a given geographical environment at a minimum cost, by optimizing the appropriate number, types, and locations of surveillance and detection systems. The objective of the optimization is twofold. First, given the topography of the terrain under study, several promising locations are determined for each sensor system based on the percentage of terrain it is covering. Second, architectures of sensor systems able to effectively cover large percentages of the terrain at minimal costs are determined by optimizing the number, types and locations of each detection system in the architecture. To do so, a modified Genetic Algorithm and a modified Particle Swarm Optimization are investigated and their ability to provide consistent results is compared. Ultimately, the modified Particle Swarm Optimization algorithm is used to obtain a Pareto frontier of detection architectures able to satisfy varying customer preferences on coverage performance and related cost.
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Falasca, Mauro. "Quantitative Decision Models for Humanitarian Logistics." Diss., Virginia Tech, 2009. http://hdl.handle.net/10919/28774.
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Humanitarian relief and aid organizations all over the world implement efforts aimed at recovering from disasters, reducing poverty and promoting human rights. The purpose of this dissertation is to develop a series of quantitative decision models to help address some of the challenges faced by humanitarian logistics.
The first study discusses the development of a spreadsheet-based multicriteria scheduling model for a small development aid organization in a South American developing country. Development aid organizations plan and execute efforts that are primarily directed towards promoting human welfare. Because these organizations rely heavily on the use of volunteers to carry out their social mission, it is important that they manage their volunteer workforce efficiently. In this study, we demonstrate not only how the proposed model helps to reduce the number of unfilled shifts and to decrease total scheduling costs, but also how it helps to better satisfy the volunteers’ scheduling preferences, thus supporting long-term retention and effectiveness of the workforce.
The purpose of the second study is to develop a decision model to assist in the management of humanitarian relief volunteers. One of the challenges faced by humanitarian organizations is that there exist limited decision technologies that fit their needs while it has also been pointed out that those organizations experience coordination difficulties with volunteers willing to help. Even though employee workforce management models have been the topic of extensive research over the past decades, no work has focused on the problem of managing humanitarian relief volunteers. In this study, we discuss a series of principles from the field of volunteer management and develop a multicriteria optimization model to assist in the assignment of both individual volunteers and volunteer groups to tasks. We present illustrative examples and analyze two complementary solution methodologies that incorporate the decision maker's preferences and knowledge and allow him/her to trade-off conflicting objectives.
The third study discusses the development of a decision model for the procurement of goods in humanitarian efforts. Despite the prevalence of procurement expenditures in humanitarian efforts, procurement in humanitarian contexts is a topic that has only been discussed in a qualitative manner in the literature. In our paper, we introduce a two stage decision model with recourse to improve the procurement of goods in humanitarian relief supply chains and present an illustrative example. Conclusions, limitations, and directions for future research are also discussed.Ph. D.
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Besbes, Khaoula. "Supply chain design with product life cycle considerations." Thesis, Artois, 2013. http://www.theses.fr/2013ARTO0209/document.
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Notre travail de recherche traite la problématique de la conception d’une chaîne logistique multi-niveaux tout en tenant compte du cycle de vie du produit. Par cycle de vie du produit, nous voulons dire la succession des quatre phases de commercialisation que traverse un produit à travers le temps, à savoir : l’introduction, la croissance, la maturité et le déclin. L’objectif est de mette en place un modèle mathématique qui soit fondé sur une analyse approfondie des différents acteurs de la chaîne, selon la phase du cycle de vie du produit.Trois principaux modèles ont été développés dans cette thèse. Chacun fait l’objet d’un chapitre à part entière.Le premier modèle développé vise à concevoir une chaîne logistique de coût minimum, tout en prenant en considération l’efficacité des différents acteurs potentiels calculée selon plusieurs critères (coût, qualité, innovation, qualité du service, délais de livraisons, …), ainsi que sa variation au cours du cycle de vie du produit. Un deuxième modèle a été mis en place pour la conception d’une chaîne logistique durable, tout en prenant en considération le cycle de vie du produit. Dans ce modèle, trois objectifs différents ont été pris en compte à la fois, à savoir, un objectif économique, un objectif environnemental et un objectif social. Dans les deux premiers modèles, nous avons supposé que le produit aura un cycle de vie classique. Cependant, dans la réalité, ceci n’est pas toujours le cas. En effet, quelques produits connaissent des cycles de vie très atypiques et donc très éloignés de la courbe d’un cycle de vie théorique. Pour ce faire, un troisième modèle stochastique a été proposé pour la conception d’une chaîne logistique robuste, tenant compte des différents scénarios du cycle de vie du produitOur research addresses the problem of designing a multi-level supply chain, while taking into consideration the product life cycle. By product life cycle, we mean the succession of the four marketing stages that a product goes through since its introduction to the market and until it will be removed from. All products have a life cycle which can be classified into four discrete stages: introduction, growth, maturity and decline.Depending on the product life cycle phases, and based on a thorough analysis of the different supply chain potential actors, this study aims to establish mathematical models to design an efficient supply chain network. Three main models have been developed in this thesis. The first proposed model aims to design a product-driven supply chain with a minimal total cost, taking into consideration the evaluation of the different potential actors effectiveness, according to several criteria (cost, quality, innovation, quality service, timely delivery, ...).A second model was developed to design of a sustainable supply chain network, taking into account the product life cycle. In this model, three different objectives at the time were considered, namely, an economic objective, an environmental objective and a social objective.In the two previous models, we have assumed that the product has a classical life cycle. However, in the reality this is not always the case. Indeed, some products have very atypical life cycles, whose curves are very different from the classical one. To tackle this problem, in the third part of this thesis, we propose a stochastic model to design a robust supply chain network, taking into account the different product life cycle scenarios
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Moissenet, Florent. "Modélisation musculo-squelettique : vers un modèle plus proche de la clinique." Thesis, Lyon 1, 2011. http://www.theses.fr/2011LYO10093.
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Dans un contexte où l'on voit émerger une demande croissante en termes de prévention, diagnostic, suivi et traitement, la modélisation numérique est devenue un outil incontournable pour comprendre les conditions de fonctionnement du système musculo-squelettique et quantifier des données encore inaccessibles par mesure directe telles que les efforts musculaires, ligamentaires ou de contact. De nombreux modèles ont été proposés et plusieurs logiciels commerciaux ont vu le jour ces dernières années autour de cette problématique. Ces derniers proposent d'utiliser un modèle générique, généralement basé sur un squelette de sujet adulte, afin de calculer ce type de données via des programmes de calcul plus ou moins ouverts. Néanmoins, si l'on s'écarte du cas idéal de l'homme adulte asymptomatique, ces modèles sont, pour le moment, tout à fait critiquables car difficiles à personnaliser. Ainsi, de nombreuses équipes se penchent aujourd'hui sur le développement d'une mise à échelle géométrique qui pourrait permettre à terme d'avoir un modèle sujet-spécifique. Cependant, très peu de travaux sont initiés autour de l'adaptation des algorithmes d'optimisation permettant d'obtenir les forces recherchées. Il est pourtant indispensable de personnaliser également ces programmes de calcul pour différentes pathologies. Les travaux de cette thèse reposent ainsi sur le développement d'algorithmes pour le calcul des forces musculo-tendineuses et ostéo-articulaires pendant la marche. Pour cela, un modèle musculo-squelettique versatile du membre inférieur, basé sur un paramétrage en coordonnées naturelles et comprenant une représentation détaillée des articulations de la cheville et du genou, est introduit. Un processus d'optimisation multicritères est également proposé, reposant sur la méthode par pseudoinverse et permettant l'introduction des forces ostéo-articulaires dans le problème de minimisation des forces musculo-tendineuses. De manière générale, cette thèse propose des bases de réflexion et de travail pour le développement de programmes de calcul appliqué et applicables à l'étude des pathologies de la marcheBecause of the increasing need of prevention, diagnosis, monitoring and treatment, numerical modeling has become an interesting tool to understand the interactions of the musculoskeletal system and to replace measurements that are still invasive for some data such as muscles, ligaments or contact forces. Many models have been proposed and some musculoskeletal simulation softwares are now avalaibales. These softwares are based on a generic model, developed using cadaver data of an adult man, and allow computing internal forces using some algorithms that are not always accessible. However, these models and algorithms are mainly adapted to the case of an asymptomatic adult man and their application to another subject, such as a pathologic subject, is criticism. Consequently, many studies have been proposed to develop geometric subject-specific models. Nevertheless, very few works have been proposed to personalize optimization algorithms that are used to solve the muscular redundancy problem, even if it seems essential to link them to pathologies. The objectives of this thesis were to develop new algorithms for musculo-tendon and osteo-articular force computation during gait. An original and versatile musculoskeletal model is developed using parameters based on natural coordinates and detailed kinematics models for both knee and ankle joints. Then, a multicriteria optimization procedure is proposed, based on the pseudoinverse method and allowing the simultaneous computation of osteo-articular and musculo-tendon forces. On the whole, this study proposes a new method to develop models and methods that could be used in the future for clinical applications during gait
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Siraj, Sajid. "Preference elicitation from pairwise comparisons in multi-criteria decision making." Thesis, University of Manchester, 2011. https://www.research.manchester.ac.uk/portal/en/theses/preference-elicitation-from-pairwise-comparisons-in-multicriteria-decision-making(bf9c4efe-28b3-4e5b-807d-76df5b858aa5).html.
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Decision making is an essential activity for humans and often becomes complex in the presence of uncertainty or insufficient knowledge. This research aims at estimating preferences using pairwise comparisons. A decision maker uses pairwise comparison when he/she is unable to directly assign criteria weights or scores to the available options. The judgments provided in pairwise comparisons may not always be consistent for several reasons. Experimentation has been used to obtain statistical evidence related to the widely-used consistency measures. The results highlight the need to propose new consistency measures. Two new consistency measures - termed congruence and dissonance - are proposed to aid the decision maker in the process of elicitation. Inconsistencies in pairwise comparisons are of two types i.e. cardinal and ordinal. It is shown that both cardinal and ordinal consistency can be improved with the help of these two measures. A heuristic method is then devised to detect and remove intransitive judgments. The results suggest that the devised method is feasible for improving ordinal consistency and is computationally more efficient than the optimization-based methods. There exist situations when revision of judgments is not allowed and prioritization is required without attempting to remove inconsistency. A new prioritization method has been proposed using the graph-theoretic approach. Although the performance of the proposed prioritization method was found to be comparable to other approaches, it has practical limitation in terms of computation time. As a consequence, the problem of prioritization is explored as an optimization problem. A new method based on multi-objective optimization is formulated that offers multiple non-dominated solutions and outperforms all other relevant methods for inconsistent set of judgments. A priority estimation tool (PriEsT) has been developed that implements the proposed consistency measures and prioritization methods. In order to show the benefits of PriEsT, a case study involving Telecom infrastructure selection is presented.
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Kaczmarczyk, Václav. "Optimální metody řízení energetické spotřeby budov." Doctoral thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2015. http://www.nusl.cz/ntk/nusl-233629.
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This thesis discusses the operational coordination of electrical appliances and devices in a smart home. At present, the diminishing volume of fossil fuels and the increasing pressure to use renewable sources of energy necessitate the integration of such volatile sources into electrical grids. This process, however, results in higher energy costs, and the consumers are thus more willing to change their behaviour to either reduce the expenses or maintain them at a reasonable level. One of the relatively few customer-oriented options to optimise energy costs consists in the demand – response principle, which utilises external information to minimise energy consumption during high price periods. Assuming the constantly changing conditions in electrical grids, and thus also the varying demands, it is vital to provide for automatic optimisation excluding the need of user intervention. The thesis presents a method which, after being implemented into the control member, will facilitate the optimal use of appliances and devices within a smart home. As the behaviour considered optimal from the perspective of demand - response is often inconsistent with the consumer‘s requirements for comfortable use of the appliances, the proposed technique offers a compromise through enabling the consumer to select the appropriate strategy. Five universal optimisation models are designed within the thesis; these models facilitate description of common home appliances and local electricity sources. The core of the method lies in formulating and optimising a mixed integer quadratic problem (MIQP). The optimisation task yields an operational schedule for the individual appliances, and this scheme considers the energy costs, the working cycle of the appliance, the user’s demands, the system restrictions and/or other input data. Furthermore, the author extends the above-discussed general technique, enabling it to adopt robust behaviour. The method then secures the preset strategy even during a marked change of the input conditions, and its robustness is a viable precondition for the overall applicability of the technique in the real control member.
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Delolme, Laurent. "Optimisation multicritères de gammes d'usinages." Thesis, Université Clermont Auvergne (2017-2020), 2017. http://www.theses.fr/2017CLFAC019.
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L’objectif de ces travaux est de développer une méthodologie de génération automatique de gammes d’usinage optimises et innovantes qui permettent aux sous-traitants aéronautiques de faire face aux problématiques de productivité et de compétitivité actuelles. Dans un premier temps, un état de l’art sur les systèmes existants de génération de gammes est présenté et permet d’introduire les limites des systèmes actuels. Une méthodologie en quatre étapes est ensuite proposée, permettant à l’utilisateur d’obtenir des gammes d’usinage optimisées respectant son savoir-faire et son expérience et introduisant de l’innovation. Cette méthodologie s’appuie sur une représentation du comportement décisionnel des méthodistes dans une situation donnée ainsi que face au risque à l’industrialisation et élargit la formalisation de la performance d’une gamme en prenant en compte d’autres critères de performance autres que le temps d’usinage ou le coût global. Ainsi, un état de l’art sur les méthodes d’aide à la décision multicritère permet de sélectionner la méthode pour l’agrégation des performances par rapport à la problématique industrielle. Après une description géométrique et technologique de la pièce et la création par les méthodistes, d’opérations d’usinage élémentaires, un algorithme génétique est utilisé pour générer des gammes optimisées. Lors d’une dernière étape, la méthodologie présente les meilleures gammes générées au méthodiste et l’utilisation de la théorie du choix social lui permet de cibler les gammes les plus performantes à implanter, en intégrant un critère de risque à l’industrialisation. Cette méthodologie a été appliquée à une pièce de train d’atterrissage usinée en alliage de Titane et a permis une diminution de 25% du temps d’usinage tout en augmentant la fiabilisation. Des perspectives d’amélioration de l’outil d’aide à la décision, à diverses étapes de la méthodologie, sont enfin proposéesThe objective of this work is to develop a Computer-Aided Process Planning (CAPP) methodology to allow aeronautical subcontractors to face the current productivity and competitiveness problems. To start, a state of the art on the existing CAPP systems is presented and introduce the limits of the current systems. A four-step methodology is then proposed, allowing the user to obtain optimized machining ranges respecting his know-how and experience and introducing innovation. This methodology is based on a representation of the decision-making behavior of the process planners in a given situation as well as the risk of industrialization and broadens the formalization of the performance by taking into account performance criteria other than the machining time or cost. Thus, a state of the art on multicriteria decision-making methods helps to select the method for the aggregation of performance in relation to the industrial problem. After a geometrical and technological description of a mechanical part and the creation by the process planners of elementary machining operations, a genetic algorithm is used to generate optimized ranges. In a final step, the methodology presents the best process plans generated to the process planners and the use of the social choice theory allows to target the most efficient ones to choose, integrating a risk criterion based on tool deflection. This methodology was applied to a Titanium alloy machined landing gear part and allowed a 25% reduction in machining time while increasing reliability. Finally, prospects for improving the decision-making tool at various stages of the methodology are proposed
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Harbaoui, dridi Imen. "Optimisation heuristique pour la résolution du m-PDPTW statique et dynamique." Thesis, Ecole centrale de Lille, 2010. http://www.theses.fr/2010ECLI0031/document.
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De nos jours, le problème de transport de marchandise occupe une place importante dans la vie économique des sociétés modernes. Le problème de ramassage et de livraison (pick-up and delivery problem) est l’un des problèmes dont une grande partie des chercheurs s’y est intéressée.Il s’agit de déterminer un circuit de plusieurs véhicules, de façon à servir à coût minimal un ensemble de clients et de fournisseurs répartis dans un réseau, satisfaisant certaines contraintes relatives aux véhicules, à leurs capacités et à des précédences entre les nœuds. Les travaux de recherche développés dans cette thèse portent sur le PDPTW (Pickup and Delivery Problem with Time Windows) à plusieurs véhicules (m-PDPTW). Ce dernier a été traité dans les deux cas : statique et dynamique. Nous avons proposé plusieurs approches de résolution du m-PDPTW basées sur les algorithmes génétiques, l’optimisation multicritère et le calcul des bornes inférieures, et ceci pour minimiser un certain nombre de critères comme : le nombre de véhicules utilisés, la somme des retards ou le coût total de transport. Ces approches ont donné de bons résultats, principalement au niveau de la minimisation de la somme des retards où nous avons obtenu, dans plusieurs cas, un retard nul avec un coût de transport tolérableNowadays, the transport goods problem occupies an important place in the economic life of modern societies. The PDPTW (Pickup and delivery problem with Time Windows) is one which a large part of researchers was interested. This is an optimization vehicles routing problem which must meet requests for transport between suppliers and customers satisfying precedence and capacity.Researchers developed in this thesis concerns the resolution of the PDPTW with multiple vehicles (m-PDPTW). The latter was treated in two cases: static and dynamic.We have proposed some approaches to solving the m- PDPTW, based on genetic algorithms, multicriteria optimization and the lower bounds, and this to minimize a number of criteria such as: the vehicles number, the total travel cost, and the total tardiness time.Computational results indicate that the proposed approach gives good results with a total tardiness equal to zero with a tolerable cost
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Jaini, Nor. "An efficient ranking analysis in multi-criteria decision making." Thesis, University of Manchester, 2017. https://www.research.manchester.ac.uk/portal/en/theses/an-efficient-ranking-analysis-in-multicriteria-decision-making(c5a694d5-fd43-434f-9f9f-b86f7581b97c).html.
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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.
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Schwarz, Alexander [Verfasser], and A. [Akademischer Betreuer] Albers. "Integration von Messdaten in die Simulation zur multikriteriellen, zeiteffizienten versuchsbasierten Optimierung technischer Systeme = Integration of measurement data in the simulation for the multicriteria time-efficient testbased optimization of technical systems / Alexander Schwarz. Betreuer: A. Albers." Karlsruhe : KIT-Bibliothek, 2013. http://d-nb.info/1046888781/34.
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Bitar, Abdoul. "Ordonnancement sur machines parallèles appliqué à la fabrication de semi-conducteurs : ateliers de photolithographie." Thesis, Saint-Etienne, EMSE, 2015. http://www.theses.fr/2015EMSE0808/document.
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Le secteur des semi-conducteurs a connu un développement considérable ces dernières décennies, du fait des nouvelles applications de la microélectronique dans l'industrie. Le processus de fabrication est réputé pour sa complexité. L'un des ateliers les plus critiques de la production, l'atelier de photolithographie, est régi par un ensemble conséquent de contraintes de production. La multiplicité des ressources utilisées, le nombre important de produits traités, en font une zone importante à optimiser. Les objectifs de la thèse ont été de modéliser cet atelier sous la forme d'un problème d'ordonnancement sur machines parallèles et d'optimiser plusieurs critères jugés pertinents pour évaluer la qualité des solutions. Des résultats en termes de complexité, et d'algorithmes de résolution, ont permis une application industrielle, dans la mesure où un logiciel d'optimisation destiné à l'ordonnancement des lots en photolithographie a été développéSemiconductor manufacturing has grown considerably in recent decades, due to new industrial applications of microelectronic devices. The related manufacturing process is known to be complex. A bottleneck process step, the photolithography workshop, gathers various types of constraints, related to the number of auxiliary resources and the tools characteristics. The aims of the thesis were to model this workstation as a parallel machine scheduling problem and to optimize various criteria, determined by industrial needs. Some complexity results are provided and optimization algorithms led to an industrial application, i.e. a software providing optimized schedules in a specific fab
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Giacon, Joice Cavalheiro Ribeiro. "Seleção de fornecedores por análise de decisão multicritério e otimização combinatória considerando aspectos de logística e sustentabilidade." Universidade de São Paulo, 2011. http://www.teses.usp.br/teses/disponiveis/3/3148/tde-22032012-180429/.
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A seleção de fornecedores é um problema complexo e que vem ganhando importância estratégica nas organizações, principalmente devido à inclusão de diversos atributos que podem ser especificados de acordo com as necessidades da situação, pois o fator custo não é mais o único responsável pela decisão. A relevância da sustentabilidade, em termos econômicos, ambientais e sociais, traz ao tema ainda mais atributos que devem ser mapeados como parte da decisão. Neste trabalho é proposta uma abordagem baseada em otimização combinatória (programação linear inteira) aliada à análise de valor multicriterial que estabelece prioridades e compensações entre os atributos definidos, para seleção de fornecedores de um conjunto de embalagens de cosméticos para uma nova linha de produtos. A solução encontrada é comparada aos métodos de otimização tradicionais (monocriteriais) e à otimização multicriterial sem leilão combinatório. Também são realizadas análises de sensibilidade com o modelo, permitindo que sejam feitas validações de forma a justificar a decisão.Supplier selection is a complex issue that has gained strategic importance in organizations, mainly due to the consideration of several criteria that can be specified according to the situation, since cost is no longer solely responsible for the decision. The sustainability relevance, in economical, environmental and social terms, brings to the theme even more criteria that should be included as part of the decision. This work proposes an approach based on combinatorial optimization (integer linear programming) combined with multi-criteria value analysis that establishes priorities and trade-offs among the defined criteria, to the supplier selection of a cosmetics packaging set for a new product line. The obtained solution is compared to traditional optimization methods (mono-criteria) and to the multi-criteria optimization without combinatorial auction. Sensitivity analyses are also performed with the model, allowing assessments to be made in order to justify the decision.
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Avril, Sophie. "A multidisciplinary approach to the introduction of the solar photovoltaic technologies in the energy mix." Thesis, Châtenay-Malabry, Ecole centrale de Paris, 2014. http://www.theses.fr/2014ECAP0057.
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Les problématiques énergétiques sont au sommet des préoccupations politiques dans de nombreux pays, du fait des enjeux environnementaux inhérents, du rôle moteur de l’énergie dans tous les secteurs économiques ainsi que des préoccupations relatives à l’indépendance énergétique. Cet intérêt est accru du fait de la part croissante des sources d’énergie renouvelables et intermittentes dans le mix énergétique mondial. En particulier, de par son fort potentiel et la volonté politique de soutien dont elle a bénéficié, l’énergie photovoltaïque est désormais un acteur clé dans la mutation énergétique mondiale, et son intégration dans le mix mondial doit être réalisée avec attention. Afin d’avoir une compréhension approfondie de la façon dont l’énergie solaire peut pénétrer et transformer le panorama énergétique, nous avons adopté une stratégie en trois niveaux avec une approche multidisciplinaire visant à apporter quelques réponses aux questions suivantes : i/ quel sera la position de l’énergie solaire dans le futur mix énergétique ?; ii/ du fait de son inconvénient majeur, l’intermittence, pouvons-nous fournir une architecture optimale d’une système basé sur l’énergie solaire associant des systèmes de stockage ?; iii/ quelle est l’efficacité des politiques incitatives mises en œuvre pour accélérer son déploiement ?Ainsi, dans un premier chapitre, nous analysons la position particulière de l’énergie photovoltaïque dans le mix énergétique. Après un rappel des enjeux des futurs mix énergétiques mondiaux, nous proposons une description sommaire des différentes technologies solaires et de leurs évolutions attendues en termes d’améliorations techniques et de réductions de coûts. Enfin, nous décrivons la croissance très rapide du marché photovoltaïque et de ces conséquences à la fois sur le mix électrique et sur le secteur industriel. Dans le deuxième chapitre, nous nous intéressons à la problématique de l’intégration de cette énergie intermittente dans le mix électrique, en développant une méthodologie d’évaluation multicritère ainsi qu’un outil d’optimisation multicritère sous contraintes qui permet de faire des simulations d’un système composé de panneaux photovoltaïques et de technologies de stockage. Des cas d’applications sur le cas réel du Cirque de Mafate (L’île de la Réunion, France) sont présentés pour illustrer l’intérêt de la méthode.Enfin, dans le troisième chapitre, nous questionnons l’efficacité de différentes politiques de soutien aux technologies photovoltaïques dans les pays les plus pertinents. Nous examinons plus particulièrement la corrélation entre la puissance installée, l’argent publique dépensé, ainsi que les prix de l’électricitéThe energetic issue is on the top of the political agenda in many countries, for environmental reasons, for its driving role in all the economic sectors, as well as for the energetic independency concerns. This problematic is stressed by the increasing weight of renewable intermittent power sources in the global energy mix. In particular, due to its high potential and the strong national policy support it beneficiated, solar photovoltaic energy is now a key player in the world energy mutation, and the way it is integrated into the global mix should be carefully performed. To deeply understand the way solar energy can penetrate and transform the forthcoming energy framework, we adopted a three-level strategy with an multidisciplinary approach to provide some answers to the following questions: i/ how can we situate the photovoltaic power role in future energy mixes?; ii/ due to its main drawback, intermittency, could we provide an optimal design of a system combining storage devices?; iii/ what is the efficiency of the incentive policies that are or have been implemented to accelerate its deployment?That is why, in a first chapter, the peculiar position of the solar photovoltaic energy in the energy mix is analyzed. After recalling the general issue of future global energetic mixes, we propose a brief description of the different photovoltaic technologies and their promising evolutions in terms of technical improvements and cost reductions. Then, we describe the fast growing photovoltaic market and its consequences both on the electricity mix and the industry sector.In the second chapter we investigate the issue of integrating such an intermittent energy in the electricity mix, by developing a multicriteria evaluation methodology and a multicriteria under constraint optimization tool which simulates a system composed of photovoltaic panels and storage devices. Applications on a real case in the Cirque de Mafate (L’île de la Réunion, France) are presented to illustrate the interest of our method.Finally, in chapter three, we question the efficiency of different public support policies to the photovoltaic technologies in the most relevant countries. We focus on correlating the installed power capacity with the spent public money and the electricity prices
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Aribi, Noureddine. "Contribution à l'élicitation des paramètres en optimisation multicritère." Phd thesis, Université Nice Sophia Antipolis, 2014. http://tel.archives-ouvertes.fr/tel-01065629.
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De nombreuses méthodes existent pour résoudre des problèmes d'optimisation multicritère, et il n'est pas aisé de choisir une méthode suffisamment adaptée à un problème multicritère donné. En effet, après le choix d'une méthode multicritère, différents paramètres (e.g. poids, fonctions d'utilité, etc.) doivent être déterminés, soit pour trouver la solution optimale (meilleur compromis) ou pour classer l'ensemble des solutions faisables (alternatives). Justement, vue cette difficulté pour fixer les paramètres, les méthodes d'élicitation sont utilisées pour aider le décideur dans cette tâche de fixation des paramètres. Par ailleurs, nous supposons que nous disposons d'un ensemble de solutions plausibles, et nous faisons aussi l'hypothèse de la disponibilité au préalable, des informations préférentielles obtenues après une interaction avec le décideur. Dans la première contribution de ce travail, nous tirons profit d'une mesure statistique simple et rapidement calculable, à savoir, le coefficient de corrélation $rho$ de Spearman, afin de développer une approche gloutonne (approchée), et deux approches exactes basées sur la programmation par contraintes (PPC) et la programmation linéaire en nombres entiers (PLNE). Ces méthodes sont ensuite utilisées pour éliciter automatiquement les paramètres appropriés de la méthode multicritère basée sur l'ordre lexicographique. Nous proposons aussi des modèles d'élicitation des paramètres d'autres méthodes multicritère, telles que la méthode MinLeximax issue de la théorie du choix social et du partage équitable, la méthode de la somme pondérée et les opérateurs OWA.
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Perez, Nicolas. "Contribution à la conception énergétique de quartiers : simulation, optimisation et aide à la décision." Thesis, La Rochelle, 2017. http://www.theses.fr/2017LAROS017/document.
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L’intégration de la recherche d’efficacité énergétique aux projets d’aménagement urbain est essentielle au vu du contexte actuel de transition énergétique et environnementale. Dans le but de réduire l’empreinte énergétique d’un quartier dès la phase de conception, un ensemble de contributions a été réalisé afin d’accompagner les aménageurs dans cette démarche. La plateforme de simulation DIMOSIM (DIstrict MOdeller and SIMulator) a été développée pour modéliser et simuler dynamiquement les flux énergétiques d’un quartier implanté au sein de son environnement urbain. La conception est optimisée à l’aide d’une procédure multiobjectif combinant les aspects énergétiques, économiques et environnementaux pour garantir la meilleure performance globale. Cette approche transversale est multi-étagée et intègre l’algorithme génétique NSGA-II afin de s’adapter aux spécificités du problème. La sélection de la solution préférentielle est ensuite facilitée par l’utilisation d’une méthode d’analyse multicritère de surclassement qui a été conçue dans le but de fournir une évaluation détaillée des différents concepts : la méthode ATLAS (Assistance TooL for decision support to Assess and Sort). Enfin, la procédure complète d’accompagnement a été appliquée à des projets de conception d’écoquartier pour en valider le fonctionnement mais également pour fournir l’aide à la décision nécessaire aux décideursThe integration of the research of energy efficiency into urban development projects is essential in the current context of energy and environmental transition. In order to reduce the energy footprint of a district already starting from the design phase, a set of contributions was elaborated to support the planners in this process. The DIMOSIM simulation platform (DIstrict MOdeller and SIMulator) has been developed to dynamically model and simulate the energy flows of a district located within its urban environment. The design of the district is optimized using a multi-objective procedure combining energy, economic and environmental aspects to ensure the best overall performance. A cross-cutting, multi-level approach integrating the NSGA-II genetic algorithm was implemented in order to adapt the procedure to the specificities of the problem. The selection of the preferred solution is then facilitated by the use of a multicriteria analysis method which was developed to provide a detailed evaluation of the different concepts : the outranking method ATLAS (Assistance TooL for decision support to assessment And Sort). Finally, the complete procedure dedicated to the district energy system design was applied to eco-district projects in order to validate its correct operation and also to provide the necessary support to decision-makers
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Varret, Antoine. "De la conception collaborative à l'ingénierie peformante de produits optimisés à base de connaissances métier." Phd thesis, Université de Technologie de Belfort-Montbeliard, 2012. http://tel.archives-ouvertes.fr/tel-00720656.
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Dans un processus traditionnel de conception de produits mécaniques, l'organisation classique est la conception du produit puis son dimensionnement et enfin son optimisation. Les concepteurs prennent des risques en n'évaluant les performances du produit que dans les dernières phases du processus, et l'étape d'optimisation est bien souvent mise de côté, faute de temps ou à cause du retard pris sur les autres phases. La phase de conception préliminaire est une étape délicate car les décisions doivent y être prises dans un contexte imprécis ou peu de choses sont définies. Il n'existe pas d'outils informatiques adaptés et l'étude de plusieurs concepts multiplie les tâches routinières et les pertes de temps associées. Le concepteur prend donc des risques en réduisant le nombre de concepts développés. Le dimensionnement de produits comporte également un certain nombre de difficultés, comme un positionnement tardif dans le processus, entraînant des étapes de pré et post traitement lourdes ainsi que des simulations longues. L'analyse d'aide à la décision est prometteuse mais elle reste marginale, faute de modèles simplifiés disponibles dans les phases amont du processus de conception.Cette thèse expose la synthèse de nos travaux de recherche portant sur l'optimisation en conception de systèmes mécaniques. L'étude proposée s'intègre dans une démarche d'ingénierie hautement productive de systèmes mécaniques et comporte plusieurs facettes : conception fonctionnelle paramétrique, application d'ingénierie à base de connaissances, outils de simulation numérique et d'optimisation. Nous proposons une méthodologie permettant d'introduire au plus tôt dans le processus de conception, une étape d'optimisation couplée à des simulations d'aide à la décision, en vue d'identifier des architectures optimales inédites, présentant les meilleurs compromis vis-à-vis d'objectifs multiples relatifs au comportement mécanique. L'objectif du travail de recherche est de développer des modèles, des méthodes et des outils dédiés à la génération semi-automatique de modèles géométriques tridimensionnels multiples identifiés comme solutions les plus performantes dans un cadre de conception collaborative de produits mécaniques. Notre méthodologie est ensuite expérimentée sur plusieurs projets de conception de systèmes mécaniques relevant de la mécanique des structures, en analyses statique et dynamique. Il s'agit en particulier de la conception d'organes du véhicule de l'UTBM participant au trophée SIA.
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Fortunet, Charles. "Une méthode d'optimisation multicritère pour le Design For Manufacturing : application aux portes d'avion." Thesis, Université Clermont Auvergne (2017-2020), 2017. http://www.theses.fr/2017CLFAC048.
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Actuellement, le marché aéronautique est en constante augmentation. Pour faire face à cela, les avionneurs doivent se restructurer et revoir les processus de fabrication des pièces. En effet, il est nécessaire d’augmenter les cadences et réduire les prix tout en conservant les performances des pièces (poids et résistance mécanique). Cependant, ces trois objectifs sont contradictoires et un compromis est difficile à trouver. Ces travaux de thèse abordent cette problématique dans le cadre du CORAC. Ils proposent une manière originale d’optimiser une pièce de structure aéronautique qui vise à développer une nouvelle approche de la conception de pièces et de processus de fabrication pour tendre vers des solutions de compromis performantes. Pour ce faire, une méthodologie multicritère en trois étapes est proposée. D’abord, l’expertise industrielle est formalisée afin de formuler le problème mathématiquement. Ensuite, un algorithme génétique est utilisé afin de déterminer une population de solutions dont les performances sont placées sur un front de Pareto.Enfin, une étape de choix parmi la population finale prenant en compte le contexte industriel est mise en place. Cette méthodologie est appliquée à une porte d’avion moyen-courrier fabriquée par matriçage puis usinage. Dans ce cas, elle permet de choisir la solution la plus adaptée au contexte industriel parmi mille solutions de compromisNowadays, the aeronautical market grows constantly. To face this, aircraft industry has to restructure and the manufacturing processes must be revised. Indeed, production rate must increase and manufacturing cost decrease while keeping the performances of the parts (weight and mechanical resistance). These objectives are contradictory and compromises must be found. This thesis broaches this problematic in relation to the CORAC. A novel method to optimize an aeronautical structural part and its manufacturing process is developed to tend toward performing compromise solutions. To do so, a three steps multi-criteria method is proposed. First, the industrial expertise is formalized to mathematically express the problem. Then, a genetic algorithm is used to determine a population in which every solution is located on a single Pareto front. At least, a decision step is set up to find the best solution in the population considering the industrial environment of the part. This methodology is applied to an aircraft door manufactured by forging and machining. In this case, it allows choosing the solution that fit the most the industrial environment within a one thousand solutions’ population
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Ammar, Achraf. "Affectation dynamique d'opérateurs polyvalents et dimensionnement des équipes dans les systèmes de production." Thesis, Clermont-Ferrand 2, 2015. http://www.theses.fr/2015CLF22620.
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Les ressources humaines jouent un rôle crucial dans les systèmes de production. D’une part, elles doivent être polyvalentes et flexibles pour pouvoir effectuer des tâches variées. D’autre part, elles doivent être affectées aux différentes machines du système de façon qu’elles puissent satisfaire les performances industrielles. Toutefois, il est souvent difficile de prendre des décisions concernant le nombre, les compétences et les stratégies d’affectation des opérateurs, en particulier dans les systèmes où la demande est aléatoire, changeante et fluctuante et lorsqu’il y a plusieurs objectifs à optimiser. Dans ce contexte, la présente thèse vise en premier lieu à déterminer comment affecter les opérateurs aux machines. En second lieu, elle vise à définir le nombre d’opérateurs et les compétences requises afin de réduire les durées de fabrication et le coût de la main d’œuvre. Deux heuristiques sont proposées pour affecter les opérateurs de façon dynamique, et en ligne, à chaque fois ils deviennent disponibles. Le choix de la machine se fait en se basant sur une analyse multicritère de l’état actuel du système avec la méthode TOPSIS pour la première heuristique et avec une méthode de restriction basée sur des seuils numériques pour la deuxième. Les critères utilisés ont été choisis à l'aide d’un jeu sérieux (simulation interactive visuelle dédiée) en utilisant le logiciel ARENA. Pour optimiser les poids de ces critères et les seuils numériques et afin d’adapter les heuristiques proposées, nous avons utilisé l’optimisation basée sur la simulation, qui intègre la dimension à la fois aléatoire et fluctuante de la demande. Les résultats des comparaisons avec les stratégies d’affectation les plus utilisées dans la littérature ont montré l’intérêt et la pertinence de nos heuristiques. Pour optimiser le nombre d’opérateurs et leurs compétences, nous avons proposé une approche basée sur la simulation et sur un algorithme évolutionnaire multi objectif (NSGAII). Nous suggérons d’accepter une certaine redondance aux niveaux des compétences afin de réduire l’impact de l’absentéisme des opérateurs sur la performance du système. Pour prendre en compte le comportement changeant et fluctuant des systèmes de production, nous avons intégré dans l’approche d’optimisation l’heuristique d’affectation la plus performante sur les heuristiques proposées. Un modèle de simulation d’un système de type Job-shop a été utilisé pour illustrer notre approche. Les résultats obtenus sur l’ensemble des solutions non dominées ont montré la pertinence de l’approche proposéeHuman resources play a crucial role in production systems. On one hand, they have to be multi-skilled and flexible to carry out various tasks. On the other hand, they must be assigned to the different machines in the system so as to satisfy industrial performances. However, it is often difficult to make decisions about the number, skills and workers assignment strategies, particularly when systems are characterized by random, changing and fluctuating demand and when there are multiple objectives to be optimized. In this context, the present thesis aims first to determine how to assign workers to machines. Second, it aims to define the number of workers and the required skills in order to reduce production times and manpower costs. Two heuristics are then proposed to assign workers dynamically, on line, each time they become idle. The choice of the machine is based on a multi criteria analysis of the current state of the system using TOPSIS method for the first heuristic and a restriction method based on numerical thresholds for the second one. The criteria used are chosen through a serious game (a dedicated Visual Interactive Simulation) implemented using ARENA software. In order to optimize the weights of these criteria and the numerical thresholds and to adapt the proposed heuristics, we used a simulation optimization, which integrates both of the random and fluctuating dimensions of the demand. The results of comparisons with the most used assignment strategies in the literature have shown the interest and relevance of our heuristics. In order to optimize the number of workers and their skills, we proposed an approach based on simulation and an evolutionary multi-objective algorithm (NSGAII). We suggest accepting some redundancy on skills so as to reduce the impact of worker absenteeism on system performance. In order to take into account the changing and fluctuating behavior of production systems, we have integrated in our optimization approach the most efficient assignment heuristic among the proposed ones. A simulation model of a job shop system has been used to illustrate our approach. The results obtained on all non-dominated solutions showed the relevance of the proposed approach
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Potelis, Artūras. "Investavimo į nekilnojamąjį turtą optimizavimas naudojant informacines technologijas." Master's thesis, Lithuanian Academic Libraries Network (LABT), 2009. http://vddb.library.lt/obj/LT-eLABa-0001:E.02~2009~D_20090610_160625-11410.
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Baigiamajame magistro darbe nagrinėjamos investavimo į nekilnojamąjį turtą problemos ir optimizavimo galimybės, naudojant kompiuterines programas. Pateiktas investavimo proceso etapų skirstymas ir išanalizuotos kiekvieno etapo optimizavimo galimybės, naudojant įvairias informacines technologijas. Atliktas nekilnojamojo turto rinkos kitimo per pastaruosius ketverius metus tyrimas pagrindžia optimizavimo priemonių taikymo būtinumą investicinėje veikloje. Nagrinėjamos užsienyje taikomos investavimą į nekilnojamąjį turtą optimizuojančios priemonės bei analizuojamos šių priemonių taikymo galimybės Lietuvoje. Taikant lyginamosios analizės principą, nustatoma geriausia investavimo proceso optimizavimo priemonė. Atliekama SSGG analizė pasirinktos optimizavimo priemonės ilgailaikiam taikymui Lietuoje. Išnagrinėjus teorinius ir praktinius investavimo į nekilnojamąjį turtą optimizavimo aspektus, pateikiamos baigiamojo darbo išvados ir siūlymai.Master degree thesis analyses Real Estate investment issues and optimisation possibilities through use of information technology. The whole investment process is divided into stages and each of them is explored for optimisation possibilities using several information technologies. The dinamic of Real Estate market in the past four years corroborates the need of optimisation in investment practice. Several means of investment optimisation used in foreign practice and possibilities applying them to Lithuanian market are explored. The comparative analysis reveals the best investment process optimising computer program for Lithuanian Real Estate market. The SWOT analysis shows strengths and weaknesses of chosen program while trying to apply it to long term usage in Lithuania. After theory and practice analysis of Real Estate investment optimization aspects final conclusions and suggestions are made.
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Galvez, Manriquez Daniel. "Évaluation de la capacité à innover : une approche par auto évaluation et suivi supporté par des analyses multicritères dynamiques." Thesis, Université de Lorraine, 2015. http://www.theses.fr/2015LORR0018/document.
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L’un des challenges les plus importants des pays développés ou émergents est de soutenir l’innovation dans les PME. Mais la question centrale ici, est de savoir si l’innovation dépend exclusivement de la disponibilité des ressources. La capacité à innover ne dispose pas d'un cadre de référence pour son évaluation, en raison principalement de sa complexité et sa nature abstraite. Sans les indicateurs appropriés, il est impossible d'établir les objectifs et de déterminer les efforts et les ressources nécessaires pour améliorer la capacité d'innovation. Le laboratoire ERPI a développé une approche d’évaluation de cette capacité privilégiant les pratiques internes qui favorisent l’innovation dans les entreprises (IIP, Indice d’Innovation Potentielle) basée sur des méthodes d’analyse multicritère. Mais une fois obtenu un résultat, quels sont les points sur lesquels une entreprise peut jouer afin d’améliorer son système d'innovation ? Dans cette thèse, nous proposons un modèle d'optimisation qui réplique la procédure d'évaluation de la capacité à innover utilisée par l'IIP et qui nous permettra de générer un plan d'action pour améliorer la capacité à innover des PME. Le modèle considère différents facteurs (la situation particulière de l'entreprise, les efforts économiques associés à la stratégie proposée, etc.) afin de générer le plan d'action le plus approprié aux besoins de chaque PME. Ainsi, trois stratégies potentielles sont proposées : améliorer le classement actuel avec un minimum d'effort, maximiser les économies de ressources, maximiser l’IIP avec un budget défini. Des scénarii sont simulés afin de tester les résultats de la mise en œuvre des différentes stratégiesOne of the most important challenges in the current industrial policy of developed and emerging countries is to support innovation in SMEs, issue which has been approach as a problem only dependent on the availability of resources. Innovation capability does not have an appropriate framework of evaluation, mainly because of its complexity and abstract nature. Without proper indicators, it is not possible to establish objectives and identify the efforts and resources necessary for its improvement. In response to this, the ERPI laboratory has developed an evaluation approach of innovation capability, taking into account internal practices to promote innovation. A field of knowledge has been developed in this direction allowing for the proposal of a novel metrology, the Potential Innovation index (PII), based on multi-criteria analysis methods for studying the dynamics within companies. In this thesis, we propose an optimization model that replicates the evaluation procedure of innovation capability to generate an action plan, i.e., the model returns concrete points in which companies can work to improve its innovation system. The model considers factors such as the particular situation of the company, the economic efforts associated with the proposed strategy, the goals of the entrepreneur, etc. Three optimization strategies are proposed: access to a higher category with a minimum of effort, maximize resource efficiency and maximize innovation performance with a defined budget. Scenarios are simulated to test the results of the implementation of the different strategies
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Antomarchi, Anne-Lise. "Conception et pilotage d'un atelier intégrant la fabrication additive." Thesis, Université Clermont Auvergne (2017-2020), 2019. http://www.theses.fr/2019CLFAC035/document.
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La fabrication additive est un domaine en plein essor. Cependant, les industriels sont aujourd’hui dans une phase d’interrogation sur l’utilisation de ce procédé dans le cadre d’une production de masse. La problématique posée dans le cadre de ces travaux de recherche est : Comment rendre viable, industriellement, le procédé de fusion sur lit de poudre ? Nos travaux abordent la conception et le pilotage d’ateliers intégrant la fabrication additive et le processus complet d’obtention de la pièce selon les trois niveaux de décision : stratégique, tactique et opérationnel. D’un point du vue stratégique, des décisions fortes d’investissement, de sélection de machines et de choix d’organisation sont à prendre avec des enjeux économiques importants. L’objectif est de définir une méthode d’optimisation multicritère pour la conception modulaire d’un système de production intégrant la fabrication additive en présence de données incertaines, optimale sur le long terme et sur le court terme. D’un point de vue tactique, toutes les pièces ne sont pas forcément des candidates pertinentes pour la fabrication additive. Dans ces travaux, nous avons développé un outil d’aide à la décision qui évalue la pertinence ou non de la fabrication additive pour l’obtention des pièces dans une approche globale des coûts. Au niveau opérationnel, nous proposons un outil basé sur la simulation de flux qui permet de passer des commandes aux ordres de fabrication et leur ordonnancement de manière à garantir l’efficience de l’atelier. Ces travaux de recherche sont développés en lien avec des acteurs du monde industriel : AddUp, MBDA et Dassault qui alimentent nos travaux et nous permettent de confronter nos outils à une réalité industrielleThe additive manufacturing is a field on the rise. However, companies wonder about the use of additive manufacturing for mass production. The problem raised in the context of this thesis is: How to make the process of sintering laser melting industrially viable? Our work focuses on the design and on the management of workshops integrating the additive manufacturing and of the complete process to obtain part according to three levels of decision: strategic, tactic and operational. About the strategic level, strong decisions of investment, machines selection and organization choice are taken with important economic issues. The aim is to define a multicriteria optimization method for the modular design of a production system integrating the additive manufacturing in the presence of uncertain data, optimal in the long term and the short term. From a tactical point of view, not all parts are necessarily relevant candidates for additive manufacturing. In this work, we developed a decision support tool that evaluates the relevance or not of additive manufacturing to obtain parts in a global cost approach. At the operational level, we offer a tool based on flow simulation that allows orders to be placed to production orders and their scheduling in order to guarantee the efficiency of the workshop. This research work is developed in collaboration with companies: AddUp, MBDA and Dassault, who contribute to our work and enable us to compare our tools with an industrial reality
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Dufossé, Fanny. "Scheduling for Reliability : complexity and Algorithms." Phd thesis, Ecole normale supérieure de lyon - ENS LYON, 2011. http://tel.archives-ouvertes.fr/tel-00660236.
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This thesis deals with the mapping and the scheduling of workflows. In this context, we consider unreliable platforms, with processors subject to failures. In a first part, we consider a particular model of streaming applications : the filtering services. In this context, we aim at minimizing period and latency. We first neglect communication costs. In this model, we study scheduling problems on homogeneous and heterogeneous platforms. Then, the impact of communication costs on scheduling problems of a filtering application is studied. Finally, we consider the scheduling problem of such an application on a chain of processors. The theoretical complexity of any variant of this problem is proved. This filtering property can model the reliability of processors. The results of some computations are successfully computed, and some other ones are lost. We consider the more frequent failure types : transient failures. We aim efficient and reliable schedules. The complexity of many variants of this problem is proved. Two heuristics are proposed and compared using using simulations. Even if transient failures are the most common failures in classical grids, some particular type of platform are more concerned by other type of problems. Desktop grids are especially unstable. In this context, we want to execute iterative applications. All tasks are executed, then a synchronization occurs, and so on. Two variants of this problem are considered : applicationsof independent tasks, and applications where all tasks need to be executed at same speed. In both cases, the problem is first theoretically studied, then heuristics are proposed and compared using simulations.
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Götthans, Tomáš. "Pokročilé algoritmy analýzy datových sekvencí v Matlabu." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2010. http://www.nusl.cz/ntk/nusl-218618.
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Cílem této práce je se seznámení s možnostmi programu Matlab z hlediska detailní analýzy deterministických dynamických systémů. Jedná se především o analýzu časové posloupnosti a o nalezení Lyapunových exponentů. Dalším cílem je navrhnout algoritmus umožňující specifikovat chování systému na základě znalosti příslušných diferenciálních rovnic. To znamená, nalezení chaotických systémů.
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Makhlouf, Anissa. "Méthodologie pour l'optimisation dynamique multicritère d'un procédé discontinu alimenté : application à la production bactérienne d'arômes laitiers." Thesis, Vandoeuvre-les-Nancy, INPL, 2006. http://www.theses.fr/2006INPL067N/document.
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Ce travail s’intéresse essentiellement au développement et à l’application d’une méthodologie pour l’optimisation dynamique multicritère d’un procédé discontinu alimenté de production bactérienne d’arômes laitiers. L’étude réalisée comprend principalement quatre parties ; la première décrit l'utilisation des plans d’expériences multicritère, couvrant un large domaine expérimental (pH, température et oxygénation), afin de collecter le maximum d'information sur le comportement physiologique de Lactococcus lactis. La deuxième concerne l'analyse cinétique détaillée de l’effet des combinaisons des facteurs opératoires sur la croissance et l'orientation du métabolisme. La troisième, traite de la construction d'un modèle cinétique en mode discontinu et discontinu alimenté. Dans la dernière, l’outil d’optimisation dynamique multicritère a été validé et appliqué au problème de production d’arômes étudié. Les résultats obtenus pour l’optimisation multicritère sont satisfaisantsThe aim of the present work is to develop and apply an innovative approach for multicriteria and dynamic optimization of fed-batch fermentation for the production of lactic aroma. This study is mainly divided in four parts: the first one describes the use of multicriteria experimental design, covering an extended operating conditions domain (pH, temperature and oxygenation), in order to collect large experimental information in batch culture of Lactococcus lactis. The second part involves detailed kinetic analysis of operating factor effect combinations on growth and metabolism orientation. The third part deals with the development of a model to predict the kinetic behaviour of this strain in batch and fed-batch cultures. In the last part, the tool for multicriteria and dynamic optimization was validated and applied to the studied problem of lactic aroma production. The results obtained for multicriteria and dynamic optimization are satisfactory
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Talbourdet, Fabien. "Développement d'une démarche d’aide à la connaissance pour la conception de bâtis performants." Thesis, Vaulx-en-Velin, Ecole nationale des travaux publics, 2014. http://www.theses.fr/2014ENTP0010/document.
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Les demandes des usagers conjuguées à la réglementation nécessitent de concevoir des bâtiments de plus en plus confortables et économes en énergie. En parallèle de ces exigences, les réglementations concernant les bâtiments sont renforcées dans différents domaines (acoustique, sécurité incendie, risque sismique,…) afin d’obtenir des bâtiments plus sûrs et correspondant aux demandes des usagers. Les impacts conjugués de ces deux facteurs engendrent une complexification de la conception des bâtiments.Cette thèse présente une démarche d’aide à la connaissance pour la conception de bâtis performants se basant sur une méthode d’optimisation. Cette démarche vise à ce que les architectes et les bureaux d’études aient une connaissance claire du potentiel de leur projet (exploration de solutions) en phase amont de conception, pour concevoir des bâtiments les plus performants possibles. Ce potentiel est évalué via des paramètres de la géométrie extérieure et intérieure ainsi que des caractéristiques énergétiques du bâti. La démarche leur permet également d’évaluer les avantages et inconvénients de différentes géométries et solutions de conception qu’ils envisagent pour répondre à leurs projets. Cette démarche est appliquée à un immeuble de bureaux à Lyon.Pour le cas testé, la démarche permet d’obtenir rapidement des solutions performantes et de définir pour certains des paramètres étudiés, des valeurs conduisant aux solutions performantes dans une partie de l’espace des solutions ou dans l’ensemble de cet espace.Cette application de la démarche montre également qu’il peut exister des solutions ayant des besoins énergétiques et des coûts de construction proches mais étant très différentes en termes de paramètres de conception. Bien que remettant en cause l'applicabilité directe de la démarche, ce résultat met en exergue un problème nouveau. Cette thèse pose alors les bases pour une nouvelle étudeBoth aspirations of users and improvements in the thermal regulation require that the comfort and the energy efficiency of new buildings improve. In addition to these requirements, regulations are strengthening in many fields such as acoustics, fire safety and mechanical performance. The combined effects of these factors are making it increasingly hard to design buildings. This thesis presents a knowledge-aid approach for designing high-performance buildings based on an optimization method. This approach aims to provide clear knowledge of the potential of projects (exploration of various options) for architects and design offices at the beginning of the design that will allow them to design the best possible high-performance buildings. This potential is evaluated using external and internal geometric parameters as well as the energy characteristics of buildings. This approach also allows them to assess geometries and design solutions which are intended to be used for their projects.This approach will be applied to an office building in Lyon, France. For the tested case, the approach obtains quickly efficient solutions and also finds, for some parameters, values to design efficient solutions on part of the Paretofront or in this entire front. This application of the approach also shows that there may be solutions which are close in terms of energy needs and cost but could be very different on design parameters. This problem could influence robustness of the approach but highlights a new problem. This thesis then lays the foundation of a new study on this topic
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Darradi, Younès. "Optimisation de la performance environnementale des activités agricoles à l’échelle d’un espace à enjeux : le cas du bassin versant de la Boulouze." Thesis, Bordeaux 1, 2011. http://www.theses.fr/2011BOR14224/document.
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Les travaux présentés dans cette thèse portent sur la notion de performance environnementale comme cadre analytique pour l’étude des impacts des activités agricoles sur l’environnement. Après avoir mis en évidence un manque de formalisation de cette notion dans la littérature, nous la définissons comme la distance entre l’état environnemental d’un écosystème à un moment donné et un état environnemental à atteindre pour cet écosystème, dit « de haute performance environnementale ». Dans cette étude, l’état environnemental est approché par trois critères liés à la ressource « eau » : les concentrations en nitrates et en matières en suspension, et les débits.Suite à la description de l’état initial, nous proposons une méthode d’optimisation de la performance environnementale des activités agricoles basée sur un couplage entre un modèle agro-hydrologique (SWAT) et un modèle d’optimisation multicritère (Weighted Goal Programming). La démarche d’optimisation considère la réaffectation spatialisée de systèmes de culture sur l’espace considéré comme facteur d’amélioration, les différents critères de l’optimisation étant examinés simultanément.La méthode est implémentée sur le bassin versant de la Boulouze (coteaux de Gascogne). Les résultats montrent une amélioration de la performance environnementale du système étudié. L’analyse de la nouvelle occupation des sols souligne qu’au-delà des évolutions quantitatives des surfaces allouées aux systèmes de culture, la spatialisation des changements d’un système vers un autre influe également sur la performance environnementale à l’échelle du bassin versant. Enfin, nous interrogeons l’applicabilité de cette méthode et mettons en évidence l’intérêt qu’elle présente comme outil à la fois de modélisation de scénarios et de communicationWe introduce in this thesis the notion of environmental performance as an analytical framework aimed at studying the impacts of agricultural activities on the environment. We outline first a need to formalize this notion and then define it as the distance between the “environmental” state of a system at a specific time and a state of “high environmental performance” to achieve. Focus is on water management at the watershed level with three criteria: nitrogen, sediments (water quality) and water flows (water quantity).Our aim is to optimize the environmental performance of agricultural activities at the watershed scale. First the initial status of the watershed is described, then a method is proposed. This method is based on a coupling between an agro-hydrological model, the Soil and Water Assessment Tool (SWAT), and the Weighted Goal Programming optimization method. Our purpose is the reallocation of farming systems within the watershed when considering the optimization criteria simultaneously.We implement this method on the Boulouze watershed (coteaux de Gascogne, in the southwestern part of France). Results outline an improvement of the environmental performance. The analysis of the new land-use plan emphasizes the fact that the changes of farming systems are not only due to evolutions of the surfaces where they are implemented, but that the environmental performance at watershed scale is also affected by their location.Finally we explore the applicability of the method used highlighting its attributes as a relevant tool for modeling scenarios and for communicating
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Perez, Escobedo José Luis. "Optimisation du développement de nouveaux produits dans l'industrie pharmaceutique par algorithme génétique multicritère." Thesis, Toulouse, INPT, 2010. http://www.theses.fr/2010INPT0038/document.
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Le développement de nouveaux produits constitue une priorité stratégique de l'industrie pharmaceutique, en raison de la présence d'incertitudes, de la lourdeur des investissements mis en jeu, de l'interdépendance entre projets, de la disponibilité limitée des ressources, du nombre très élevé de décisions impliquées dû à la longueur des processus (de l'ordre d'une dizaine d'années) et de la nature combinatoire du problème. Formellement, le problème se pose ainsi : sélectionner des projets de Ret D parmi des projets candidats pour satisfaire plusieurs critères (rentabilité économique, temps de mise sur le marché) tout en considérant leur nature incertaine. Plus précisément, les points clés récurrents sont relatifs à la détermination des projets à développer une fois que les molécules cibles sont identifiées, leur ordre de traitement et le niveau de ressources à affecter. Dans ce contexte, une approche basée sur le couplage entre un simulateur à événements discrets stochastique (approche Monte Carlo) pour représenter la dynamique du système et un algorithme d'optimisation multicritère (de type NSGA II) pour choisir les produits est proposée. Un modèle par objets développé précédemment pour la conception et l'ordonnancement d'ateliers discontinus, de réutilisation aisée tant par les aspects de structure que de logique de fonctionnement, a été étendu pour intégrer le cas de la gestion de nouveaux produits. Deux cas d'étude illustrent et valident l'approche. Les résultats de simulation ont mis en évidence l'intérêt de trois critères d'évaluation de performance pour l'aide à la décision : le bénéfice actualisé d'une séquence, le risque associé et le temps de mise sur le marché. Ils ont été utilisés dans la formulation multiobjectif du problème d'optimisation. Dans ce contexte, des algorithmes génétiques sont particulièrement intéressants en raison de leur capacité à conduire directement au front de Pareto et à traiter l'aspect combinatoire. La variante NSGA II a été adaptée au problème pour prendre en compte à la fois le nombre et l'ordre de lancement des produits dans une séquence. A partir d'une analyse bicritère réalisée pour un cas d'étude représentatif sur différentes paires de critères pour l'optimisation bi- et tri-critère, la stratégie d'optimisation s'avère efficace et particulièrement élitiste pour détecter les séquences à considérer par le décideur. Seules quelques séquences sont détectées. Parmi elles, les portefeuilles à nombre élevé de produits provoquent des attentes et des retards au lancement ; ils sont éliminés par la stratégie d'optimistaion bicritère. Les petits portefeuilles qui réduisent les files d'attente et le temps de lancement sont ainsi préférés. Le temps se révèle un critère important à optimiser simultanément, mettant en évidence tout l'intérêt d'une optimisation tricritère. Enfin, l'ordre de lancement des produits est une variable majeure comme pour les problèmes d'ordonnancement d'atelierNew Product Development (NPD) constitutes a challenging problem in the pharmaceutical industry, due to the characteristics of the development pipeline, namely, the presence of uncertainty, the high level of the involved capital costs, the interdependency between projects, the limited availability of resources, the overwhelming number of decisions due to the length of the time horizon (about 10 years) and the combinatorial nature of a portfolio. Formally, the NPD problem can be stated as follows: select a set of R and D projects from a pool of candidate projects in order to satisfy several criteria (economic profitability, time to market) while copying with the uncertain nature of the projects. More precisely, the recurrent key issues are to determine the projects to develop once target molecules have been identified, their order and the level of resources to assign. In this context, the proposed approach combines discrete event stochastic simulation (Monte Carlo approach) with multiobjective genetic algorithms (NSGA II type, Non-Sorted Genetic Algorithm II) to optimize the highly combinatorial portfolio management problem. An object-oriented model previously developed for batch plant scheduling and design is then extended to embed the case of new product management, which is particularly adequate for reuse of both structure and logic. Two case studies illustrate and validate the approach. From this simulation study, three performance evaluation criteria must be considered for decision making: the Net Present Value (NPV) of a sequence, its associated risk defined as the number of positive occurrences of NPV among the samples and the time to market. Theyv have been used in the multiobjective optimization formulation of the problem. In that context, Genetic Algorithms (GAs) are particularly attractive for treating this kind of problem, due to their ability to directly lead to the so-called Pareto front and to account for the combinatorial aspect. NSGA II has been adapted to the treated case for taking into account both the number of products in a sequence and the drug release order. From an analysis performed for a representative case study on the different pairs of criteria both for the bi- and tricriteria optimization, the optimization strategy turns out to be efficient and particularly elitist to detect the sequences which can be considered by the decision makers. Only a few sequences are detected. Among theses sequences, large portfolios cause resource queues and delays time to launch and are eliminated by the bicriteria optimization strategy. Small portfolio reduces queuing and time to launch appear as good candidates. The optimization strategy is interesting to detect the sequence candidates. Time is an important criterion to consider simultaneously with NPV and risk criteria. The order in which drugs are released in the pipeline is of great importance as with scheduling problems
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Leroy, Cassandre. "Élicitation incrémentale combinée à la recherche heuristique pour l'optimisation combinatoire multi-objectifs." Electronic Thesis or Diss., Sorbonne université, 2022. https://accesdistant.sorbonne-universite.fr/login?url=https://theses-intra.sorbonne-universite.fr/2022SORUS367.pdf.
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Cette thèse s'intéresse à la résolution de problèmes de décision sur domaine combinatoire par des méthodes d'élicitation incrémentale des préférences basée le regret pour l'optimisation interactive. On se situe à l'intersection de la théorie de la décision, de la recherche opérationnelle et de l'intelligence artificielle, en théorie de la décision algorithmique. On suppose que les préférences du décideur peuvent être représentées par une fonction de scalarisation paramétrée (somme pondérée, OWA et intégrale de Choquet), mais que les paramètres (par exemple, le jeu de poids) ne sont pas connus au départ. L'apprentissage actif des paramètres est entremêlé à la résolution du problème dans le but d'apprendre seulement la part d'information sur ce paramètre qui est utile pour résoudre le problème donnée. L'originalité de ces travaux réside dans la conception de méthodes fondées sur la recherche heuristique couplée à l'élicitation incrémentale pour déterminer la meilleure solution du décideur. Nous proposons d'abord deux méthodes pour résoudre des problèmes d'optimisation combinatoire multi-objectifs avec des préférences imprécises, la première basée sur la recherche locale et la seconde sur un algorithme génétique. Nous proposons ensuite deux approches permettant l'élicitation d'une fonction d'ensemble linéaire, sous-modulaire et super-modulaire avec la construction d'un sous-ensemble indépendant optimal soumis à une contrainte de matroïde. La première approche est basée sur un algorithme glouton et l'autre sur la recherche locale. Afin de démontrer l'efficacité pratique de nos approches, nos algorithmes sont testés numériquement sur différents problèmes et évalués en termes de temps de calcul, de nombre de requêtes et d'erreur empiriqueThis thesis is concerned with solving combinatorial domain decision problems using incremental regret-based preference elicitation methods for interactive optimization. It is situated at the intersection of decision theory, operations research and artificial intelligence, in algorithmic decision theory. It is assumed that the decision maker's preferences can be represented by a parameterised scalarization function (weighted sum, OWA and Choquet integral), but the parameters (e.g. set of weights) are not known at the beginning. The active learning of the parameters is intertwined with the solution of the problem in order to learn only that part of the information about the parameter that is useful to solve the given problem. The originality of this work lies in the use of methods based on heuristic search coupled with incremental elicitation to determine the best solution for the decision maker. In first we propose two methods for solving multi-objective combinatorial optimisation problems with imprecise preferences, the first based on local search and the second on a genetic algorithm. We then propose two approaches for the elicitation of a linear, submodular and super-modular set function with the construction of an optimal independent subset subject to a matroid constraint. The first approach is based on a greedy algorithm and the other on local search. In order to demonstrate the practical effectiveness of our approaches, our algorithms are numerically tested on different problems and evaluated in terms of computation time, number of queries and empirical error
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Haddou, Benderbal Hichem. "Développement d’une nouvelle famille d’indicateurs de performance pour la conception d’un système manufacturier reconfigurable (RMS) : approches évolutionnaires multicritères." Thesis, Université de Lorraine, 2018. http://www.theses.fr/2018LORR0112/document.
Full textAbstract:
L'environnement manufacturier moderne est face à un bouleversement de paradigmes nécessitant plus de changeabilité au niveau physique et logique. Un système manufacturier Changeable est défini comme un système de production ayant les capacités de faciliter les changements adéquats, permettant d'ajuster ses structures et ses processus en réponse aux différents besoins. Dans ce contexte, les systèmes manufacturiers doivent se doter d’un très haut niveau de reconfigurabilité, qui est considérée comme l’un des facteurs majeurs du concept de changeabilité. En effet, dans la vision de l'Usine du Futur, la reconfigurabilité est essentielle pour s'adapter efficacement à la complexité croissante des environnements manufacturiers. Elle assure une adaptation rapide, efficace et facile de ces systèmes tout en étant réactif, robuste et économiquement compétitif. L’objectif est de répondre aux nouvelles contraintes internes et externes telles que la globalisation, la variété des produits, la personnalisation de masse ou le raccourcissement des délais. À travers cette thèse, nous étudions la problématique de conception des systèmes manufacturiers reconfigurables (Reconfigurable Manufacturing System – RMS). L’objectif consiste à concevoir des systèmes réactifs en se basant sur leurs capacités en matière de reconfigurabilité. Nous avons étudié ce problème sur trois niveaux : (i) le niveau des composantes, relatif aux modules des machines reconfigurables, (ii) le niveau des machines et leurs interactions, ainsi que l’impact de ces interactions sur le système et (iii) le niveau de l'atelier, composé de l'ensemble des machines reconfigurables. Nous avons développé pour chaque niveau, des indicateurs de performance afin d’assurer les meilleures performances du système conçu, tels que l’indicateur de modularité, l’indicateur de flexibilité, l’indicateur de robustesse et l’effort d'évolution d'un système reconfigurable. Pour l'ensemble des problèmes étudiés, nous avons développé des modèles d’optimisation multicritère, résolus à travers des heuristiques ou des métaheuristiques multicritères (comme le recuit simulé multicritère (AMOSA) et les algorithmes génétiques multicritère (NSGA-II)). De nombreuses expériences numériques et analyses ont été réalisées afin de démontrer l’applicabilité de nos approchesThe modern manufacturing environment is facing a paradigm shift that require more changeability at physical and logical levels. A Changeable Manufacturing System is defined as a production system that has the ability to facilitate the right changes, allowing the adjustment of its structures and processes in response to the different needs. In this context, manufacturing systems must have a very high level of reconfigurability, which is considered to be one of the major enablers of changeability. From the perspective of the “Factory of the future”, the reconfigurability is essential to effectively adapt to the ever-increasing complexity of manufacturing environments. It allows a rapid, efficient and easy adaptation of these systems while being responsive, robust and economically competitive. The objective is to respond to new internal and external constraints in terms of globalization, variety of products, mass customization, and shorter lead times. Through this thesis, we study the problem of design of reconfigurable manufacturing systems (RMS) that meets these requirements. The goal is to design responsive systems based on their key features of reconfigurability. We have studied the RMS design problem on three levels: (i) the level of the components, relating to the modules of the reconfigurable machines, (ii) the machine level and their interactions, as well as the impact of these interactions on the system and (iii) the workshop level composed of all the reconfigurable machines. We have developed for each level, performance indicators to ensure a better responsiveness and a high performance of the designed system, like the modularity index, the flexibility index, the robustness index and the layout evolution effort of a reconfigurable system. For each of the studied problems, we developed multicriteria optimization models, solved through heuristics or multicriteria metaheuristics (such as archived multi-objective simulated annealing (AMOSA) and multi-objective genetic algorithms (NSGA-II)). Numerous numerical experiments and analyzes have been performed to demonstrate the applicability of our approaches