Dissertations / Theses: 'The schedule optimization'

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Lindner, Thomas. "Train schedule optimization in public rail transport." [S.l. : s.n.], 2000. http://deposit.ddb.de/cgi-bin/dokserv?idn=95980479X.

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Wilcox, Ronald James. "Flexible schedule optimization for human-robot collaboration." Thesis, Massachusetts Institute of Technology, 2013. http://hdl.handle.net/1721.1/81713.

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Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2013. Cataloged from PDF version of thesis. Includes bibliographical references (p. 99-101). Robots are increasingly entering domains typically thought of as human-only. This convergence of human and robotic agents leads to a need for new technology to enable safe and efficient collaboration. The goal of this thesis is to develop a task allocation and scheduling algorithm for teams of robots working with or around teams of humans in intense domains where tight, fluid choreography of robotic schedules is required to guarantee the safety of all involved while maintaining high levels of productivity. Three algorithms are presented in this work: the Adaptive Preferences Algorithm, the Multi-Agent Optimization Algorithm, and Tercio. Tercio, the culminatory algorithm, is capable of assigning robots to tasks and producing near-optimal schedules for ten agents and hundreds of tasks in seconds while making guarantees about process specifications such as worker safety and deadline satisfaction. This work extends dynamic scheduling methods to incorporate flexible windows with an optimization framework featuring a mixed integer program and a satisficing hueristic scheduler. By making use of Tercio, a manufacturing facility or other high-intensity domain may fluidly command a team of robots to complete tasks in a quick, efficient manner while maintaining an ability to respond seamlessly to disturbances at execution. This greatly increases both productivity, by decreasing the time spent recompiling solutions, and responsiveness to humans in the area. These improvements in performance are displayed with multiple live demonstrations and simulations of teams of robots responding to disturbances. Tercio acts as an enabling step towards the ultimate goal of fully coordinated factories of dozens to hundreds of robots accomplishing many thousands of tasks in a safe, predictable, efficient manner. by Ronald J. Wilcox. S.M.

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Shenoi, Rajesh Gopalakrishna. "Integrated airline schedule optimization : models and solution methods." Thesis, Massachusetts Institute of Technology, 1996. http://hdl.handle.net/1721.1/10655.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 1996. Includes bibliographical references (p. 133-148). by Rajesh Gopalakrishna Shenoi. Ph.D.

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Yuan, Duojia, and S3024047@student rmit edu au. "Flight Delay-Cost Simulation Analysis and Airline Schedule Optimization." RMIT University. Aerospace, Mechanical, Manufacturing Engineering, 2007. http://adt.lib.rmit.edu.au/adt/public/adt-VIT20080618.092923.

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In order to meet the fast-growing demand, airlines have applied much more compact air-fleet operation schedules which directly lead to airport congestion. One result is the flight delay, which appears more frequently and seriously; the flight delay can also significantly damage airline's profitability and reputation The aim of this project is to enhance the dispatch reliability of Australian X Airline's fleet through a newly developed approach to reliability modeling, which employs computer-aided numerical simulation of the departure delay distribution and related cost to achieve the flight schedule optimization. The reliability modeling approach developed in this project is based on the probability distributions and Monte Carlo Simulation (MCS) techniques. Initial (type I) delay and propagated (type II) delay are adopted as the criterion for data classification and analysis. The randomicity of type I delay occurrence and the internal relationship between type II delay and changed flight schedule are considered as the core factors in this new approach of reliability modeling, which compared to the conventional assessment methodologies, is proved to be more accurate on the departure delay and cost evaluation modeling. The Flight Delay and Cost Simulation Program (FDCSP) has been developed (Visual Basic 6.0) to perform the complicated numerical calculations through significant amount of pseudo-samples. FDCSP is also designed to provide convenience for varied applications in dispatch reliability modeling. The end-users can be airlines, airports and aviation authorities, etc. As a result, through this project, a 16.87% reduction in departure delay is estimated to be achieved by Australian X Airline. The air-fleet dispatch reliability has been enhanced to a higher level - 78.94% compared to initial 65.25%. Thus, 13.35% of system cost can be saved. At last, this project also achieves to set a more practical guideline for air-fleet database and management upon overall dispatch reliability optimization.

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Agbokou, Claudine Biova 1979. "Robust airline schedule planning : review and development of optimization approaches." Thesis, Massachusetts Institute of Technology, 2004. http://hdl.handle.net/1721.1/30143.

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Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering; and, (S.M.)--Massachusetts Institute of Technology, Operations Research Center, 2004. Includes bibliographical references (p. 87-89). Major airlines aim to generate schedules that maximize profit potential and satisfy constraints involving flight schedule design, fleet assignment, aircraft maintenance routing and crew scheduling. Almost all aircraft and crew schedule optimization models assume that flights, aircraft, crews, and passengers operate as planned. Thus, airlines typically construct plans that maximize revenue or minimize cost based on the assumption that every flight departs and arrives as planned. Because flight delays and cancellations result from numerous causes, including severe weather conditions, unexpected aircraft and crew failures, and congestion at the airport and in the airspace, this deterministic, optimistic scenario rarely, if ever, occurs. In fact, schedule plans are frequently disrupted and airlines often incur significant costs in addition to those originally planned. To address this issue, an approach is to design schedules that are robust to schedule disruptions and attempt to minimize realized, and not planned, costs. In this research, we review recovery approaches and robustness criteria in the context of airline schedule planning. We suggest new approaches for designing fleet assignments that facilitate recovery operations, and we present models to generate plans that allow for more robust crew operations, based on the idea of critical crew connections. We also examine the impact on robustness of new scheduling practices to debank hub airports. by Claudine Biova Agbokou. S.M.

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McIntire, Seth (Seth Cullen). "Modeling drug substance purification manufacturing through schedule optimization and simulation." Thesis, Massachusetts Institute of Technology, 2017. http://hdl.handle.net/1721.1/111489.

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Thesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, in conjunction with the Leaders for Global Operations Program at MIT, 2017. Thesis: S.M., Massachusetts Institute of Technology, Department of Mechanical Engineering, in conjunction with the Leaders for Global Operations Program at MIT, 2017. Cataloged from PDF version of thesis. Includes bibliographical references (pages 35-36). This thesis develops a method by which overtime could be reduced in a highly variable drug substance purification manufacturing environment. Purification production overtime (20%) is a big cost driver at Building XX1 (BXX). Current production planning and labor resource evaluation methods at BXX Purification are manual, do not capture schedule delays, and do not adequately account for labor availability. Because of this, BXX is unable to accurately evaluate to what extent labor resource contributes to bottlenecking or how to improve overtime. A tool is devised in the Virtually Exhaustive Combinatorial System (VirtECS®) Scheduler software whereby purification production schedules are modeled and optimized. The model simulates production delays and the flow of production. Results lead to a more accurate understanding of how labor resource constrains the lot cycle time and where improvements in shift structure could be made to improve lot cycle time and variability of lot cycle time. The purification production schedules of two monoclonal antibodies (mAb) were modeled with the use of VirtECS® Scheduler. These two drug substances are selected to reflect the majority of BXX's mAb pipeline. The plant, BXX, produces a high mix of clinical and commercial launch drug substances, and is subject to a number of stochastic scheduling delays. Excel® is used to generate random sets of process times to simulate delays. These process times are fed into VirtECS®, a production schedule optimization tool, which then produces a simulated set of production schedules. Scheduling decisions of shift labor allocation and when manufacturing should start production during the week are simulated using the model. Results from this evaluation illustrate opportunities for BXX to improve overtime. Lot cycle time is found to be reduced by up to 5.9% based on model results by moving the start of production towards the end of the week and allocating more resources to the third shift from second shift. Additionally, cycle time variability, could be reduced by up to 22%. The model makes a number of assumptions which simplify purification operations whose effect should be further investigated. Future improvements for VirtECS® are proposed to better model BXX processes. by Seth McIntire. M.B.A. S.M.

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Brändström, Johan. "Optimization for Train Energy Performance." Thesis, Uppsala universitet, Avdelningen för beräkningsvetenskap, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-237844.

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In many studies efforts are made to decrease the energy consumption of trains by optimizing their drive style, e.g. accelerate and brake optimally and regenerate electricity when braking. In other studies the goal is to distribute the run time between stations in an optimal way to decrease the energy consumption, given a relatively simple drive style. In this report the goal is to combine these two energy saving methods to obtain as low energy consumption as possible. By coupling one software containing a drive style optimizer with another software which by different optimization methods calculates the optimal run time distribution on a given track this is accomplished. The study also contains a comparison between drive styles, with the goal to find a relatively simple but energy efficient drive style. Finally the dependence between run time distribution and energy consumption is further analysed. The results show that by redistributing the run times the energy consumption can be decreased compared to previously existing time tables. They also show that a relatively simple drive style gives comparable energy consumption compared to the one obtained using a drive style optimizer. Finally the results show that the dependence between run time and energy consumption can be approximated with a simple second order equation.

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Husni, Mohammed Hamza. "A multiperiod optimization model to schedule large-scale petroleum development projects." [College Station, Tex. : Texas A&M University, 2008. http://hdl.handle.net/1969.1/ETD-TAMU-3218.

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Cobanov, Branislav. "Stochastic control of animal diets optimal sampling schedule and diet optimization /." Columbus, Ohio : Ohio State University, 2006. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1155661130.

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Yao, Enxin. "Optimization of energy consumption schedule of residential loads and electric vehicles." Thesis, University of British Columbia, 2016. http://hdl.handle.net/2429/58302.

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In the current electrical grid, utility companies have begun to use demand side management (DSM) programs and time-of-use (TOU) pricing schemes to shape the residential load profile. However, it is difficult for the residential users to respond to the pricing signal and manually manage the operation of various household appliances. Hence, the autonomous energy consumption scheduling of residential loads and electric vehicles (EVs) is necessary for the users to benefit from the DSM programs. In this thesis, we propose different algorithms to schedule the energy consumption of residential loads and EVs, and provide ancillary services to the electrical grid. First, we study the DSM for areas with high photovoltaic (PV) penetration. Since many rooftop PV units can be integrated in the distribution network, the voltage rise issue occurs when the reverse power flow from the households to the substation is significant. We use stochastic programming to formulate an energy consumption scheduling problem, which takes into account the voltage rise issue and the uncertainty of the power generation from PV units. We propose an algorithm by solving the formulated problem and jointly shave the peak load and reduce the reverse power flow. Subsequently, we study using the EVs to provide the frequency regulation service. We formulate a problem to schedule the hourly regulation capacity of the EVs using the probabilistic robust optimization framework. Our formulation takes into account the limited battery capacity of the EVs and the uncertainty of the automatic generation control (AGC) signal. An efficient algorithm is proposed to solve the formulated problem based on duality. Last but not least, we study the market participation of an aggregator which coordinates a fleet of EVs to provide frequency regulation service to an independent system operator (ISO). The two-settlement market system (i.e., the day-ahead market (DAM) and real-time market) is considered. We analyze two types of DAMs based on the market rules of New York ISO and California ISO. We formulate a problem to determine the bid for the aggregator in the DAM using stochastic program and conditional value at risk. Efficient algorithms are proposed to tackle the formulated problem. Applied Science, Faculty of Electrical and Computer Engineering, Department of Graduate

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Banham, Stephen R. "TaskMaster: a prototype graphical user interface to a schedule optimization model." Thesis, Monterey, California. Naval Postgraduate School, 1990. http://hdl.handle.net/10945/30673.

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Approved for public release, distribution is unlimited This thesis investigates the use of current graphical interface techniques to build more effective computer-user interfaces to Operations Research (OR) schedule optimization models. The design is directed at the scheduling decision maker who possesses limited OR experience. The feasibility and validity of building an interface for this kind of user is demonstrated in the development of a prototype graphical user interface called TaskMaster. TaskMaster is designed as the Dialog component of a scheduling Decision Support System (DSS). The underlying scheduling model uses set-partitioning and mixed-integer linear programming to generate optimal schedules. Although the model was originally developed to address a specific problem, inter-deployment scheduling of Navy surface ships, TaskMaster has been designed to be problem-independent, enabling it to address a broad range of scheduling problems with the same general structure. TaskMaster demonstrates the type of interactive, graphical interface that can be developed specifically for non-specialists. It is easy to learn and to use, and yet fully exploits the power of a sophisticated OR scheduling model. The prototype is implemented on a NeXT computer, chosen for its advanced computational power and state-of-the-art graphical interface development tools.

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Marla, Lavanya. "Airline schedule planning and operations : optimization-based approaches for delay mitigation." Thesis, Massachusetts Institute of Technology, 2010. http://hdl.handle.net/1721.1/62123.

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Thesis (Ph. D. in Transportation Studies)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 2010. Cataloged from PDF version of thesis. Includes bibliographical references (p. 157-162). We study strategic and operational measures of improving airline system performance and reducing delays for aircraft, crew and passengers. As a strategic approach, we study robust optimization models, which capture possible future operational uncertainties at the planning stage, in order to generate solutions that when implemented, are less likely to be disrupted, or incur lower costs of recovery when disrupted. We complement strategic measures with operational measures of managing delays and disruptions by integrating two areas of airline operations thus far separate - disruption management and flight planning. We study different classes of models to generate robust airline scheduling solutions. In particular, we study, two general classes of robust models: (i) extreme-value robust-optimization based and (ii) chance-constrained probability-based; and one tailored model, which uses domain knowledge to guide the solution process. We focus on the aircraft routing problem, a step of the airline scheduling process. We first show how the general models can be applied to the aircraft routing problem by incorporating domain knowledge. To overcome limitations of solution tractability and solution performance, we present budget-based extensions to the general model classes, called the Delta model and the Extended Chance-Constrained programming model. Our models enhance tractability by reducing the need to iterate and re-solve the models, and generate solutions that are consistently robust (compared to the basic models) according to our performance metrics. In addition, tailored approaches to robustness can be expressed as special cases of these generalizable models. The extended models, and insights gleaned, apply not only to the aircraft routing model but also to the broad class of large-scale, network-based, resource allocation. We show how our results generalize to resource allocation problems in other domains, by applying these models to pharmaceutical supply chain and corporate portfolio applications in collaboration with IBM's Zurich Research Laboratory. Through empirical studies, we show that the effectiveness of a robust approach for an application is dependent on the interaction between (i) the robust approach, (ii) the data instance and (iii) the decision-maker's and stakeholders' metrics. We characterize the effectiveness of the extreme-value models and probabilistic models based on the underlying data distributions and performance metrics. We also show how knowledge of the underlying data distributions can indicate ways of tailoring model parameters to generate more robust solutions according to the specified performance metrics. As an operational approach towards managing airline delays, we integrate flight planning with disruption management. We focus on two aspects of flight planning: (i) flight speed changes; and (ii) intentional flight departure holds, or delays, with the goal of optimizing the trade-off between fuel costs and passenger delay costs. We provide an overview of the state of the practice via dialogue with multiple airlines and show how greater flexibility in disruption management is possible through integration. We present models for aircraft and passenger recovery combined with flight planning, and models for approximate aircraft and passenger recovery combined with flight planning. Our computational experiments on data provided by a European airline show that decrease in passenger disruptions on the order of 47.2%-53.3% can be obtained using our approaches. We also discuss the relative benefits of the two mechanisms studied - that of flight speed changes, and that of intentionally holding flight departures, and show significant synergies in applying these mechanisms. We also show that as more information about delays and disruptions in the system is captured in our models, further cost savings and reductions in passenger delays are obtained. by Lavanya Marla. Ph.D.in Transportation Studies

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Cobanov, Branislav. "Stochastic control of animal eiets: optimal sampling schedule and diet optimization." The Ohio State University, 2006. http://rave.ohiolink.edu/etdc/view?acc_num=osu1155661130.

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CRUZ, ANDRE VARGAS ABS DA. "SCHEDULE OPTIMIZATION WITH PRECEDENCE CONSTRAINTS USING GENETIC ALGORITHMS AND COOPERATIVE CO-EVOLUTION." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2003. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=3725@1.

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CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO Esta dissertação investiga o uso de Algoritmos Genéticos e de Co-Evolução Cooperativa na otimização de problemas de planejamento com restrições de precedência. Neste tipo de problema algumas ou todas as tarefas têm restrições que implicam na necessidade de planejá-las ou executá-las antes ou depois de outras. Por esta razão, o uso de modelos evolucionários convencionais como, por exemplo, os baseados em ordem pode gerar soluções inválidas, não penalizáveis, que precisam ser descartadas, comprometendo assim o desempenho do algoritmo. O objetivo do trabalho foi, portanto, estudar formas de representação de soluções para este tipo de problema capazes de gerar somente soluções válidas, bem como avaliar o desempenho dos modelos propostos. O trabalho consistiu de 3 etapas principais: um estudo sobre problemas de otimização de planejamento com algoritmos genéticos; a definição de novos modelos usando algoritmos genéticos e co-evolução cooperativa para otimização de problemas de planejamento com restrições de precedência e a implementação de uma ferramenta para estudo de caso. O estudo sobre os problemas de otimização de planejamentos com algoritmos genéticos envolveu o levantamento de representações, dificuldades e características deste tipo de problema e, mais especificamente, de representações baseadas em ordem. A modelagem do algoritmo genético consistiu fundamentalmente na definição de uma representação dos cromossomas e da função da avaliação que levasse em conta a existência de restrições de precedência (tarefas que devem ser planejadas/executadas antes de outras). A construção do modelo co-evolucionário por sua vez consistiu em definir uma nova população, com uma outra representação, que se responsabilizasse pela distribuição dos recursos para execução das tarefas, responsabilidade esta que, no modelo com algoritmos genéticos convencionais, era tratada de forma simples por um conjunto de heurísticas. Finalmente, desenvolveu-se uma ferramenta para implementar estes modelos e tratar de um estudo de caso complexo que oferecesse as características necessárias para testar a qualidade das representações e avaliar os resultados. O estudo de caso escolhido foi a otimização do planejamento da descarga, armazenamento e embarque de minério de ferro de modo a minimizar o tempo de estadia dos navios em um porto fictício. Foram realizados vários testes que demonstraram a capacidade dos modelos desenvolvidos em gerar soluções viáveis, sem a necessidade de heurísticas de correção, e os resultados obtidos foram comparados com os de um processo de busca aleatória. Em todos os casos, os resultados obtidos pelos modelos foram sempre superiores aos obtidos pela busca aleatória. No caso do modelo de representação com uma única população obteve-se resultados até 41% melhores do que com os obtidos por uma busca aleatória. No caso do modelo de representação com co-evolução o resultado ficou 33% melhor que a busca aleatória com tratamento de solução idêntico ao da solução co-evolucionária. Os resultados da co-evolução comparados com o algoritmo genético com uma única espécie foram 29% melhores. This work investigates the use of Genetic Algorithms and Cooperative Co-Evolution in optimization of scheduling problems with precedence constraints. In this kind of problem some or all tasks have constraints that imply planning or executing them before or after others. For this reason, the use of order-based conventional evolutionary models may generate invalid solutions, which cannot be penalized, needing to be discarded and therefore compromising the algorithm performance. The main goal was therefore to study models for this kind of problem that are capable of generating only valid solutions. The work was divided in 3 main steps: a survey on scheduling optimization problems using genetic algorithms; definition of two models based on genetic algorithms and cooperative co-evolution for optimizing scheduling problems with precedence constraints; and the implementation of a tool for a case study. The study on scheduling optimization problems with genetic algorithms consisted in gathering information about representations and characteristics of this kind of problem and, more specifically, about order-based representations. The genetic algorithm modeling consisted basically in defining a chromosome representation and an evaluation function that took into account the existence of precedence constraints (tasks that must be scheduled or executed before others). The co-evolutionary model consisted in defining a new population, with another representation scheme, which was responsible for distributing resources for tasks execution. On the conventional genetic algorithm model, this role was played by a simple set of heuristics. Finally, a tool was developed for implementing those models and treating a complex case study which offered the needed characteristics for testing representation performance and evaluating results. The chosen case study was the optimization of iron ore dumping, stocking and ship loading on a fictitious harbor, targeting minimization of ships waiting time. Tests were done in order to demonstrate the ability of the developed models in generating viable solutions without the need of corrective heuristics and the results were compared to the results obtained through exhaustive search. In all cases, the models` results were better than the exhaustive search ones. In the case where the representation used a single population the results obtained were up to 41% better than the ones with the exhaustive search. The co- evolutionary results outperformed the co-evolutionary search with the same solution representation by 33%. Compared to the single specie genetic algorithm, the co- evolutionary model outperformed it by 29%.

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Peng, Tingqing. "WSN Routing Schedule Based on Energy-aware Adaptation." Thesis, Mittuniversitetet, Institutionen för informationssystem och –teknologi, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-39223.

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In view of the problem of uneven load distribution and energy consumption among nodes in a multi-hop wireless sensor network, this research constructs the routing schedule problem as a MOP (Multi-objective Optimization Problem), and proposed an energy-aware routing optimization scheme RDSEGA based on multi-objective optimization. In this scheme, in order to avoid the searching space explosion problem caused by the increase of nodes, KSP Yen's algorithm was applied to prune the searching space, and the candidate paths selected after pruning are recoded based on priority. Then adopted the improved strengthen elitist genetic algorithm to get the entire network routing optimization scheme with the best energy efficiency. At the same time, in view of the problem of routing discontinuity in the process of path crossover and mutation, new crossover and mutation method was proposed that based on the gene fragments connected by the adjacent node or the same node to maximize the effectiveness of the evolution result. The experimental results prove that the scheme reduced the energy consumption of nodes in the network, the load between nodes becomes more balanced, and the working time of the network has been prolonged nearly 40% after the optimization. This brings convenience to practical applications, especially for those that are inconvenient to replace nodes.

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Geranmayeh, Shirin. "Optimizing Surgical Scheduling Through Integer Programming and Robust Optimization." Thesis, Université d'Ottawa / University of Ottawa, 2015. http://hdl.handle.net/10393/32976.

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This thesis proposes and verifies a number of optimization models for re-designing a master surgery schedule with minimized peak inpatient load at the ward. All models include limitations on Operating Rooms and surgeons availability. Surgeons` preference is included with regards to a consistent weekly schedule over a cycle. The uncertain in patients` length of stay was incorporated using discrete probability distributions unique to each surgeon. Furthermore, robust optimization was utilized to protect against the uncertainty in the number of inpatients a surgeon may send to the ward per block. Different scenarios were developed that explore the impact of varying the availability of operating rooms on each day of the week. The models were solved using Cplex and were verified by an Arena simulation model.

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Strukov, Denis. "Investigation and realization of the high school schedule optimization model in the internet environment." Master's thesis, Lithuanian Academic Libraries Network (LABT), 2010. http://vddb.laba.lt/obj/LT-eLABa-0001:E.02~2010~D_20100826_143838-47159.

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Every school, college and university has to deal with the scheduling task once or more times a year. The school schedule creation on its own is a very difficult task, furthermore, to make it convenient for students as well as for teachers makes it even more complex. The main aim of this paper is to present a flexible software system that is capable of creating a schedule for a secondary school using the latest technologies and distributed programming techniques. The literature analyzed in the paper is related to solving the tasks of school scheduling. Contemporary solutions are reviewed. The paper also contains analysis of existing commercial and non commercial solutions. The new software system is presented. Its advantages and disadvantages are analyzed. The optimization methods that can be used in school schedule optimization are analyzed and some of them are employed in the new software prototype in order to achieve better results. Kiekviena mokykla arba universitetas kasmet susiduria su tvarkaraščio sudarymo problema. Tai yra labai sudėtinga bei daug laiko reikalaujanti užduotis. Šio darbo tikslas yra pristatyti lanksčią mokyklos tvarkaraščių sudarymo bei optimizavimo sistemą. Analizuojama literatūra, egzistuojantis komerciniai bei nekomerciniai sprendimai. Pristatoma nauja sistema. Analizuojami jos privalumai bei trukumai. Apžvelgiami optimizaciniai metodai kurie gali būti panaudoti mokyklos tvarkaraščiui pagerinti. Taip pat pristatoma nauja architektūra bei modelis.

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Ganser, Stefan [Verfasser], and Christian [Akademischer Betreuer] Lengauer. "Iterative Schedule Optimization for Parallelization in the Polyhedron Model / Stefan Ganser ; Betreuer: Christian Lengauer." Passau : Universität Passau, 2020. http://d-nb.info/1206730978/34.

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Na, Byungsoo. "Optimization of automated float glass lines." Diss., Georgia Institute of Technology, 2010. http://hdl.handle.net/1853/39637.

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Motivated by operational issues in real-world glass manufacturing, this thesis addresses a problem of laying out and sequencing the orders so as to minimize wasted glass, called scrap. This optimization problem combines aspects of traditional cutting problems and traditional scheduling and sequencing problems. In so far as we know, the combination of cutting and scheduling has not been modeled, or solved. We propose a two-phase approach: snap construction and constructing cutting and offload schedules. Regarding the second phase problem, we introduce FGSP (float glass scheduling problem), and provide its solution structure, called coveys. We analyze simple sub-models of FGSP considering the main elements: time, unit, and width. For each model, we provide either a polynomial time algorithm or a proof of NP-completeness. Since FGSP is NP-complete, we propose a heuristic algorithm, Longest Unit First (LUF), and analyze the worst case performance of the algorithm in terms of the quality of solutions; the worst case performance bound is {1+(m-1)/m}+{1/3-1/(3m)} where m is the number of machines. It is 5/3 when m=2. For the real-world problem, we propose two different methods for snap construction, and we apply two main approaches to solve cutting and offloading schedules: an MIP approach and a heuristic approach. Our solution approach produces manufacturing yields greater than 99%; current practice is about 95%. This is a significant improvement and these high-yield solutions can save millions of dollars.

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Garcia, Flora A. 1979. "Integrated optimization model for airline schedule design : profit maximization and issues of access for small markets." Thesis, Massachusetts Institute of Technology, 2004. http://hdl.handle.net/1721.1/28299.

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Thesis (S.M. in Transportation)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering; and, (S.M.)--Massachusetts Institute of Technology, Technology and Policy Program, 2004. Includes bibliographical references (p. 99-100). The purpose of the National Airspace System Strategy Simulator is to provide the FAA with a decision support system to evaluate long-term infrastructure and regulatory strategies. The NAS strategy simulator consists of several modules representing the different entities within the NAS embedded in a system dynamics framework. The MIT Airline Scheduling Module is the module within the NAS Strategy Simulator that represents the decision making process of the airlines with respect to the schedules that they fly. The MIT Airline Scheduling Module is an incremental optimization tool to determine schedule changes from one time step to another that best meets demand using available resources. The optimization model combines an Integrated Schedule Design and Fleet Assignment model and a model, based on Passenger Decision Window model, that determines passenger preference for itineraries. We simultaneously establish frequency, departure times, fleet assignment, passenger loads and revenue within a competitive environment. Optimization methods often lead to extreme schedule decisions such as eliminating service to markets, often small markets, that are not financially profitable for the airlines. This is of grave concern to government policy makers as rural access to markets, goods and services is a politically charged subject. The issue is to understand what is likely to happen in small communities if the government doesn't respond in some way and how much subsidy, if any, would it be necessary to encourage airlines to maintain service in these markets. The approach we will use is based on economic policy and cost-benefit analysis. by Flora A. Garcia. S.M. S.M.in Transportation

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Dinh, Tien. "Creating a More Efficient Course Schedule at UNO Department o Economics and Finance Using Linear Optimization." ScholarWorks@UNO, 2018. https://scholarworks.uno.edu/honors_theses/105.

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In 2012, Wormald R. & Guimond C. developed a mathematical model utilizing integer linear programming and network flow to help Worchester Polytechnic Institute (WPI) create a more efficient course schedule. Course scheduling was a major problem at WPI in 2012, as the manual process at that time often resulted in courses being assigned to inappropriate (too large or too small) classrooms. The University of New Orleans (UNO) is facing a similar challenge, as the current scheduling system at UNO does not always produce efficient course schedules. The goal of this thesis, therefore, is to improve upon the 2012 model by WPI, from that developing a more efficient course schedule at UNO Department of Economics and Finance. This can serve as a starting point for future research on finding an optimal schedule at UNO, given the restrictions and preferences on room assignments.

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22

Ozlu, Ahmet Oguzhan. "Optimization approaches for designing baseball scout networks under uncertainty." Diss., Georgia Institute of Technology, 2016. http://hdl.handle.net/1853/54983.

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Major League Baseball (MLB) is a 30-team North American professional baseball league and Minor League Baseball (MiLB) is the hierarchy of developmental professional baseball teams for MLB. Most MLB players first develop their skills in MiLB, and MLB teams employ scouts, experts who evaluate the strengths, weaknesses, and overall potential of these players. In this dissertation, we study the problem of designing a scouting network for a Major League Baseball (MLB) team. We introduce the problem to the operations research literature to help teams make strategic and operational level decisions when managing their scouting resources. The thesis consists of three chapters that aim to address decisions such as how the scouts should be assigned to the available MiLB teams, how the scouts should be routed around the country, how many scouts are needed to perform the major scouting tasks, are there any trade-off s between the scouting objectives, and if there are any, what are the outcomes and insights. In the first chapter, we study the problem of assigning and scheduling minor league scouts for Major League Baseball (MLB) teams. There are multiple objectives in this problem. We formulate the problem as an integer program, use decomposition and both column-generation-based and problem-specific heuristics to solve it, and evaluate policies on multiple objective dimensions based on 100 bootstrapped season schedules. Our approach can allow teams to improve operationally by finding better scout schedules, to understand quantitatively the strategic trade-offs inherent in scout assignment policies, and to select the assignment policy whose strategic and operational performance best meets their needs. In the second chapter, we study the problem under uncertainty. In reality we observe that there are always disruptions to the schedules: players are injured, scouts become unavailable, games are delayed due to bad weather, etc. We presented a minor league baseball season simulator that generates random disruptions to the scout's schedules and uses optimization based heuristic models to recover the disrupted schedules. We evaluated the strategic benefits of different policies for team-to-scout assignment using the simulator. Our results demonstrate that the deterministic approach is insufficient for evaluating the benefits and costs of each policy, and that a simulation approach is also much more effective at determining the value of adding an additional scout to the network. The real scouting network design instances we solved in the first two chapters have several detailed complexities that can make them hard to study, such as idle day constraints, varying season lengths, off days for teams in the schedule, days where some teams play and others do not, etc. In the third chapter, we analyzed a simplified version of the Single Scout Problem (SSP), stripping away much of the real-world complexities that complicate SSP instances. Even for this stylized, archetypal version of SSP, we find that even small instances can be computationally difficult. We showed by reduction from Minimum Cost Hamiltonian Path Problem that archetypal version of SSP is NP-complete, even without all of the additional complexity introduced by real scheduling and scouting operations.

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23

Ūselis, Linas. "Tvarkaraščių analizės ir sudarymo sistema." Master's thesis, Lithuanian Academic Libraries Network (LABT), 2009. http://vddb.library.lt/obj/LT-eLABa-0001:E.02~2008~D_20090304_094445-21921.

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Anotacija Baigiamajame magistro darbe aptartas mokyklinių tvarkaraščių generavimas ir optimizavimas. Taip pat buvo išsiaiškinti keliami reikalavimai mokykliniams tvarkaraščiams. Šio darbo tikslas yra sukurti programinę įrangą, kurį sugeneruotų mokinių ir mokytojų tvarkaraščius. Sukurta vartotojų sąsaja tenkina visus jai keltus reikalavimus. Siekiant tikslo yra keliami šie uždaviniai: išanalizuoti mokyklinių tvarkaraščių generavimą, išsiaiškinti keliamus reikalavimus mokykliniams tvarkaraščiams, susipažinti su esama tvarkaraščių generavimo programine įranga, sugalvoti naują generavimo algoritmą, sukurti draugišką vartotojo sąsają. Darbo apimtis – 48 p. , 25 pav., 2 lentelės, bibliografinis šaltinis. Summary In this final work school schedule and optimization is described. Also analyzed requirements for school scheduling. Main purpose of the work was to develop user interface which create school schedule for teachers and schoolboys Developed user interface serves all requirements. There are several tasks to be achieved: to analyze schools scheduling; to find out raised requirements for school scheduling; to analyze software of school scheduling, to create new algorithm, to create friendly user interface. Work’s size: 48 pages, 25 fig., 2 tables, bibliographical sources.

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24

Pupeikienė, Lina. "Mokyklos tvarkaraščių optimizavimas." Master's thesis, Lithuanian Academic Libraries Network (LABT), 2004. http://vddb.library.lt/obj/LT-eLABa-0001:E.02~2004~D_20040525_184045-40469.

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In this work was created algorithm of SA – Simulated Annealing method and GMJ – Global Minimizer for Java. GMJ it’s solution of so called frames of optimised tasks. The method of SA is a technique that has attracted significant attention as suitable for optimization problems of large scale. For practical purposes, simulated annealing has effectively “solved” the famous travelling salesman. At the heart of the method of simulated annealing is an analogy with thermodynamics, specifically with the way that liquids freeze and crystallize, or metals cool and anneal. So the essence of the process is slow cooling, allowing ample time for redistribution of the atoms as they lose mobility. This is the technical definition of annealing, and it is essential for ensuring that a low energy state will be achieved. GMJ – it’s a software solution of so called frames of global optimisation tasks. This method realizes: · algorithms of global optimisation (methods), · functions, that’s can be optimised (tasks), · objects, that’s can be showed on display (analysis). After the program was created, exhaustive inquiry of in this work realized methods was done: analysed influence of teachers, students and others different restrains multipliers to school scheduler making. The research was done using the data of college of Marijampolė. There was accomplished theoretical and experimental comparison of SA and the school schedule programs of others firms.

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25

Cheraghchi, Fatemeh. "Maritime Transportation Optimization Using Evolutionary Algorithms in the Era of Big Data and Internet of Things." Thesis, Université d'Ottawa / University of Ottawa, 2019. http://hdl.handle.net/10393/39451.

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With maritime industry carrying out nearly 90% of the volume of global trade, the algorithms and solutions to provide quality of services in maritime transportation are of great importance to both academia and the industry. This research investigates an optimization problem using evolutionary algorithms and big data analytics to address an important challenge in maritime disruption management, and illustrates how it can be engaged with information technologies and Internet of Things. Accordingly, in this thesis, we design, develop and evaluate methods to improve decision support systems (DSSs) in maritime supply chain management. We pursue three research goals in this thesis. First, the Vessel Schedule recovery Problem (VSRP) is reformulated and a bi-objective optimization approach is proposed. We employ bi-objective evolutionary algorithms (MOEAs) to solve optimization problems. An optimal Pareto front provides a valuable trade-off between two objectives (minimizing delay and minimizing financial loss) for a stakeholder in the freight ship company. We evaluate the problem in three domains, namely scalability analysis, vessel steaming policies, and voyage distance analysis, and statistically validate their performance significance. According to the experiments, the problem complexity varies in different scenarios, while NSGAII performs better than other MOEAs in all scenarios. In the second work, a new data-driven VSRP is proposed, which benefits from the available Automatic Identification System (AIS) data. In the new formulation, the trajectory between the port calls is divided and encoded into adjacent geohashed regions. In each geohash, the historical speed profiles are extracted from AIS data. This results in a large-scale optimization problem called G-S-VSRP with three objectives (i.e., minimizing loss, delay, and maximizing compliance) where the compliance objective maximizes the compliance of optimized speeds with the historical data. Assuming that the historical speed profiles are reliable to trust for actual operational speeds based on other ships' experience, maximizing the compliance of optimized speeds with these historical data offers some degree of avoiding risks. Three MOEAs tackled the problem and provided the stakeholder with a Pareto front which reflects the trade-off among the three objectives. Geohash granularity and dimensionality reduction techniques were evaluated and discussed for the model. G-S-VSRPis a large-scale optimization problem and suffers from the curse of dimensionality (i.e. problems are difficult to solve due to exponential growth in the size of the multi-dimensional solution space), however, due to a special characteristic of the problem instance, a large number of function evaluations in MOEAs can still find a good set of solutions. Finally, when the compliance objective in G-S-VSRP is changed to minimization, the regular MOEAs perform poorly due to the curse of dimensionality. We focus on improving the performance of the large-scale G-S-VSRP through a novel distributed multiobjective cooperative coevolution algorithm (DMOCCA). The proposed DMOCCA improves the quality of performance metrics compared to the regular MOEAs (i.e. NSGAII, NSGAIII, and GDE3). Additionally, the DMOCCA results in speedup when running on a cluster.

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26

Vigeh, Arya. "Investigation of a Simulated Annealing Cooling Schedule used to Optimize the Estimation of the Fiber Diameter Distribution in a Peripheral Nerve Trunk." DigitalCommons@CalPoly, 2011. https://digitalcommons.calpoly.edu/theses/497.

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In previous studies it was determined that the fiber diameter distribution in a peripheral nerve could be estimated by a simulation technique known as group delay. These results could be further improved using a combinatorial optimization algorithm called simulated annealing. This paper explores the structure and behavior of simulated annealing for the application of optimizing the group delay estimated fiber diameter distribution. Specifically, a set of parameters known as the cooling schedule is investigated to determine its effectiveness in the optimization process. Simulated annealing is a technique for finding the global minimum (or maximum) of a cost function which may have many local minima. The set of parameters which comprise the cooling schedule dictate the rate at which simulated annealing reaches its final solution. Converging too quickly can result in sub-optimal solutions while taking too long to determine a solution can result in an unnecessarily large computational effort that would be impractical in a real-world setting. The goal of this study is to minimize the computational effort of simulated annealing without sacrificing its effectiveness at minimizing the cost function. The cost function for this application is an error value computed as the difference in the maximum compound evoked potentials between an empirically-determined template distribution of fiber diameters and an optimized set of fiber diameters. The resulting information will be useful when developing the group delay estimation and subsequent simulated annealing optimization in an experimental laboratory setting.

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27

Dori, Gergö [Verfasser], André [Akademischer Betreuer] Borrmann, and Markus [Akademischer Betreuer] König. "Simulation-based methods for float time determination and schedule optimization for construction projects / Gergö Dori. Betreuer: André Borrmann. Gutachter: Markus König ; André Borrmann." München : Universitätsbibliothek der TU München, 2016. http://d-nb.info/108176788X/34.

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28

Abdallah, Fadel. "Optimization and Scheduling on Heterogeneous CPU/FPGA Architecture with Communication Delays." Thesis, Université de Lorraine, 2017. http://www.theses.fr/2017LORR0301.

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Le domaine de l'embarqué connaît depuis quelques années un essor important avec le développement d'applications de plus en plus exigeantes en calcul auxquels les architectures traditionnelles à base de processeurs (mono/multi cœur) ne peuvent pas toujours répondre en termes de performances. Si les architectures multiprocesseurs ou multi cœurs sont aujourd'hui généralisées, il est souvent nécessaire de leur adjoindre des circuits de traitement dédiés, reposant notamment sur des circuits reconfigurables, permettant de répondre à des besoins spécifiques et à des contraintes fortes particulièrement lorsqu'un traitement temps-réel est requis. Ce travail présente l'étude des problèmes d'ordonnancement dans les architectures hétérogènes reconfigurables basées sur des processeurs généraux (CPUs) et des circuits programmables (FPGAs). L'objectif principal est d'exécuter une application présentée sous la forme d'un graphe de précédence sur une architecture hétérogène CPU/FPGA, afin de minimiser le critère de temps d'exécution total ou makespan (Cmax). Dans cette thèse, nous avons considéré deux cas d'étude : un cas d'ordonnancement qui tient compte des délais d'intercommunication entre les unités de calcul CPU et FPGA, pouvant exécuter une seule tâche à la fois, et un autre cas prenant en compte le parallélisme dans le FPGA, qui peut exécuter plusieurs tâches en parallèle tout en respectant la contrainte surfacique. Dans un premier temps, pour le premier cas d'étude, nous proposons deux nouvelles approches d'optimisation, GAA (Genetic Algorithm Approach) et MGAA (Modified Genetic Algorithm Approach), basées sur des algorithmes génétiques. Nous proposons également de tester un algorithme par séparation et évaluation (méthode Branch & Bound). Les approches GAA et MGAA proposées offrent un très bon compromis entre la qualité des solutions obtenues (critère d'optimisation de makespan) et le temps de calcul nécessaire à leur obtention pour résoudre des problèmes à grande échelle, en comparant à la méthode par séparation et évaluation (Branch & Bound) proposée et l'autre méthode exacte proposée dans la littérature. Dans un second temps, pour le second cas d'étude, nous avons proposé et implémenté une méthode basée sur les algorithmes génétiques pour résoudre le problème du partitionnement temporel dans un circuit FPGA en utilisant la reconfiguration dynamique. Cette méthode fournit de bonnes solutions avec des temps de calcul raisonnables. Nous avons ensuite amélioré notre précédente approche MGAA afin d'obtenir une nouvelle approche intitulée MGA (Multithreaded Genetic Algorithm), permettent d'apporter des solutions au problème de partitionnement. De plus, nous avons également proposé un algorithme basé sur le recuit simulé, appelé MSA (Multithreaded Simulated Annealing). Ces deux approches proposées, basées sur les méthodes métaheuristiques, permettent de fournir des solutions approchées dans un intervalle de temps très raisonnable aux problèmes d'ordonnancement et de partitionnement sur système de calcul hétérogène The domain of the embedded systems becomes more and more attractive in recent years with the development of increasing computationally demanding applications to which the traditional processor-based architectures (either single or multi-core) cannot always respond in terms of performance. While multiprocessor or multicore architectures have now become generalized, it is often necessary to add to them dedicated processing circuits, based in particular on reconfigurable circuits, to meet specific needs and strong constraints, especially when real-time processing is required. This work presents the study of scheduling problems into the reconfigurable heterogeneous architectures based on general processors (CPUs) and programmable circuits (FPGAs). The main objective is to run an application presented in the form of a Data Flow Graph (DFG) on a heterogeneous CPU/FPGA architecture in order to minimize the total running time or makespan criterion (Cmax). In this thesis, we have considered two case studies: a scheduling case taking into account the intercommunication delays and where the FPGA device can perform a single task at a time, and another case taking into account parallelism in the FPGA, which can perform several tasks in parallel while respecting the constraint surface. First, in the first case, we propose two new optimization approaches GAA (Genetic Algorithm Approach) and MGAA (Modified Genetic Algorithm Approach) based on genetic algorithms. We also propose to compare these algorithms to a Branch & Bound method. The proposed approaches (GAA and MGAA) offer a very good compromise between the quality of the solutions obtained (optimization makespan criterion) and the computational time required to perform large-scale problems, unlike to the proposed Branch & Bound and the other exact methods found in the literature. Second, we first implemented an updated method based on genetic algorithms to solve the temporal partitioning problem in an FPGA circuit using dynamic reconfiguration. This method provides good solutions in a reasonable running time. Then, we improved our previous MGAA approach to obtain a new approach called MGA (Multithreaded Genetic Algorithm), which allows us to provide solutions to the partitioning problem. In addition, we have also proposed an algorithm based on simulated annealing, called MSA (Multithreaded Simulated Annealing). These two proposed approaches which are based on metaheuristic methods provide approximate solutions within a reasonable time period to the scheduling and partitioning problems on a heterogeneous computing system

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29

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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30

Hadded, Mohamed. "Design and optimization of access control protocols in Vehicular Ad Hoc Networks (VANETs)." Thesis, Evry, Institut national des télécommunications, 2016. http://www.theses.fr/2016TELE0023/document.

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Les accidents routiers et leurs dommages représentent un problème croissant dans le monde entier. Dans ce contexte, les réseaux véhiculaires (VANETs) peuvent être déployés pour réduire les risques et pour améliorer le confort. Ils permettent aux véhicules d'échanger différents types de données qui vont des applications de sécurité et de gestion du trafic aux applications de confort. De nos jours, les applications de sécurité sont l’objet de beaucoup d'attention des chercheurs ainsi que des fabricants d'automobiles. Dans cette thèse, nous étudierons les applications critiques pour la sécurité routière visant à fournir une assistance dans des situations dangereuses ou difficiles. Notre objectif principal sera de proposer de nouveaux protocoles de contrôle d'accès au support de transmission (MAC) et de routage, qui peuvent s’adapter dynamiquement aux changements fréquents de topologies des VANETs. Après un aperçu des protocoles d’accès sans contention dans les VANETs, nous proposons des solutions basées sur la technique de division du temps: Time Division Multiple Access (TDMA). D’abord, nous nous concentrons sur le développement d’un nouveau protocole distribué (DTMAC), qui ne repose pas sur l’utilisation d’infrastructure. DTMAC utilise les informations de localisation et un mécanisme de réutilisation des slots pour assurer que les véhicules accèdent au canal efficacement et sans collision. Les résultats obtenus ont confirmé l’efficacité de notre protocole, DTMAC se comporte très significativement mieux que VeMAC (protocole MAC basé sur TDMA.) Ensuite nous proposons TRPM, un protocole de routage basé sur une approche cross-layer. Dans TRPM, l’ordonnancement des slots TDMA construit par DTMAC et la position de la destination sont utilisés pour choisir le meilleur relais. Les résultats montrent que TRPM offre de meilleures performances, du nombre moyen de relais et de la fiabilité de livraison des messages comparé à d’autres protocoles. Dans la deuxième partie de cette thèse, nous nous focaliserons sur les mécanismes centralisés d’allocation de slots qui utilisent des coordinateurs. D’abord, nous proposons CTMAC, un protocole basé sur TDMA centralisé utilisant les RSUs (RoadSide Units) pour créer et maintenir les ordonnancements. CTMAC met en œuvre un mécanisme qui permet d’empêcher les “Access Collisions” de se produire plus que deux fois entre les véhicules qui tentent d’acquérir un même slot disponible. Les résultats ont montré que CTMAC permet de mieux minimiser les collisions, ainsi que le surcoût généré pour créer et maintenir les ordonnancements par rapport aux protocoles MAC, basés sur TDMA distribué. Cependant, dans CTMAC, les véhicules roulant vite devront acquérir des nouveaux slots après une courte période de temps à chaque fois qu’ils quittent les zones de leurs RSUs courants. Cette situation rend les protocoles centralisés inefficaces et couteux dans les réseaux à grande vitesse. Afin de pallier à ce problème inhérent à l’utilisation des RSUs, nous adaptons un algorithme d’ordonnancement basé sur le clustering dans lequel certains véhicules sont élus pour gérer l'accès au canal. Ceci permet aux véhicules de rester attachés à leurs clusters plus longtemps. Pour ce faire, nous proposons 1- un protocole de clustering nommé AWCP afin de former des clusters stables avec une longue durée de vie. AWCP est basé sur l’algorithme de clustering pour les réseaux mobiles WCA dans lequel les têtes des clusters sont élues en se basant sur une fonction de poids. 2- Nous formulons le réglage des paramètres de protocole AWCP comme un problème d’optimisation multi-objective et nous proposons un outil d’optimisation qui combine la version multi-objective de l’algorithme génétique appelé NSGA-II avec le simulateur de réseau ns-2 pour trouver les meilleurs paramètres du protocole AWCP. 3- Nous proposons ASAS, une stratégie adaptative pour l’attribution des slots temporels basée sur une approche cross-layer entre TDMA et AWCP Road crashes and their damages represent a serious issue and are one of the main causes of people death. In this context, Vehicular Ad hoc NETworks (VANETs) are deployed to reduce the risk of road accident as well as to improve passengers’ comfort by allowing vehicles to exchange different kinds of data which ranges widely from road safety and traffic management to infotainment. Nowadays, safety applications are receiving a great deal of attention from researchers as well as from automobile manufacturers. In this thesis, we particularly focus on safety-critical applications, designed to provide drivers assistance in dangerous situations and to avoid accidents in highway environments. Such applications must guarantee to the vehicles access to the medium and have strict requirements regarding end-to-end delay and packet loss ratio. Therefore, our main goal is to propose new medium access control and routing protocols, which can efficiently adapt to frequent changing VANET network topologies. After a comprehensive overview of free-contention MAC protocols, we propose several solutions, based on Time Division Multiple Access Technique (TDMA). We have designed DTMAC, a fully distributed TDMA-based MAC protocol, which does not rely on an expensive infrastructure. DTMAC uses vehicles’ locations and a slot reuse concept to ensure that vehicles in adjacent areas have collision-free schedule. Using simulations, we prove that DTMAC provides a lower rate of access and merging collisions than VeMAC, a well-known TDMA based MAC protocol in VANET. Then, in order to ensure that event-driven safety messages can be sent over a long distance, we propose TRPM, a TDMA aware Routing Protocol for Multi-hop communication. Our routing scheme is based on a cross layer approach between the MAC and the routing layers, in which the intermediate vehicles are selected using TDMA scheduling information. Simulation results show that TRPM provides better performances in terms of average end-to-end delay, average number of hops and average delivery ratio. In the second part, we focus on coordinator-based TDMA scheduling mechanisms. First, we propose the Centralized TDMA based MAC protocol (CTMAC) which uses Road Side Units (RSUs) as a central coordinator to create and maintain the TDMA schedules. CTMAC implements an Access Collision Avoidance mechanism that can prevent the access collision problem occurring more than twice between the same vehicles that are trying to access the channel at the same time. Using simulation we show an improvement in terms of access and merging collisions as well as the overhead required to create and maintain the TDMA schedules compared to distributed scheduling mechanisms. However, in the CTMAC protocol, fast moving vehicles will need to compete for new slots after a short period of time when they leave their current RSU area, which makes a centralized scheduling approach very expensive. In order to further improve the performance of coordinator-based TDMA scheduling mechanisms, we focus on cluster-based TDMA MAC protocols in which some vehicles in the network are elected to coordinate the channel access, allowing the vehicles to remain connected with their channel coordinator for a longer period of time. To this end, first we propose an adaptive weighted clustering protocol, named AWCP, which is road map dependent and uses road IDs and vehicle directions to make the clusters’ structure as stable as possible. Then, we formulate the AWCP parameter tuning as a multi-objective problem and we propose an optimization tool to find the optimal parameters of AWCP to ensure its QoS. Next, we propose ASAS, an adaptive slot assignment strategy for a cluster-based TDMA MAC protocol. This strategy is based on a cross layer approach involving TDMA and AWCP. The objective is to overcome the inter-cluster interference issue in overlapping areas by taking into account vehicles’ locations and directions when the cluster head assign slots

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31

Abdallah, Fadel. "Optimization and Scheduling on Heterogeneous CPU/FPGA Architecture with Communication Delays." Electronic Thesis or Diss., Université de Lorraine, 2017. http://www.theses.fr/2017LORR0301.

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Le domaine de l'embarqué connaît depuis quelques années un essor important avec le développement d'applications de plus en plus exigeantes en calcul auxquels les architectures traditionnelles à base de processeurs (mono/multi cœur) ne peuvent pas toujours répondre en termes de performances. Si les architectures multiprocesseurs ou multi cœurs sont aujourd'hui généralisées, il est souvent nécessaire de leur adjoindre des circuits de traitement dédiés, reposant notamment sur des circuits reconfigurables, permettant de répondre à des besoins spécifiques et à des contraintes fortes particulièrement lorsqu'un traitement temps-réel est requis. Ce travail présente l'étude des problèmes d'ordonnancement dans les architectures hétérogènes reconfigurables basées sur des processeurs généraux (CPUs) et des circuits programmables (FPGAs). L'objectif principal est d'exécuter une application présentée sous la forme d'un graphe de précédence sur une architecture hétérogène CPU/FPGA, afin de minimiser le critère de temps d'exécution total ou makespan (Cmax). Dans cette thèse, nous avons considéré deux cas d'étude : un cas d'ordonnancement qui tient compte des délais d'intercommunication entre les unités de calcul CPU et FPGA, pouvant exécuter une seule tâche à la fois, et un autre cas prenant en compte le parallélisme dans le FPGA, qui peut exécuter plusieurs tâches en parallèle tout en respectant la contrainte surfacique. Dans un premier temps, pour le premier cas d'étude, nous proposons deux nouvelles approches d'optimisation, GAA (Genetic Algorithm Approach) et MGAA (Modified Genetic Algorithm Approach), basées sur des algorithmes génétiques. Nous proposons également de tester un algorithme par séparation et évaluation (méthode Branch & Bound). Les approches GAA et MGAA proposées offrent un très bon compromis entre la qualité des solutions obtenues (critère d'optimisation de makespan) et le temps de calcul nécessaire à leur obtention pour résoudre des problèmes à grande échelle, en comparant à la méthode par séparation et évaluation (Branch & Bound) proposée et l'autre méthode exacte proposée dans la littérature. Dans un second temps, pour le second cas d'étude, nous avons proposé et implémenté une méthode basée sur les algorithmes génétiques pour résoudre le problème du partitionnement temporel dans un circuit FPGA en utilisant la reconfiguration dynamique. Cette méthode fournit de bonnes solutions avec des temps de calcul raisonnables. Nous avons ensuite amélioré notre précédente approche MGAA afin d'obtenir une nouvelle approche intitulée MGA (Multithreaded Genetic Algorithm), permettent d'apporter des solutions au problème de partitionnement. De plus, nous avons également proposé un algorithme basé sur le recuit simulé, appelé MSA (Multithreaded Simulated Annealing). Ces deux approches proposées, basées sur les méthodes métaheuristiques, permettent de fournir des solutions approchées dans un intervalle de temps très raisonnable aux problèmes d'ordonnancement et de partitionnement sur système de calcul hétérogène The domain of the embedded systems becomes more and more attractive in recent years with the development of increasing computationally demanding applications to which the traditional processor-based architectures (either single or multi-core) cannot always respond in terms of performance. While multiprocessor or multicore architectures have now become generalized, it is often necessary to add to them dedicated processing circuits, based in particular on reconfigurable circuits, to meet specific needs and strong constraints, especially when real-time processing is required. This work presents the study of scheduling problems into the reconfigurable heterogeneous architectures based on general processors (CPUs) and programmable circuits (FPGAs). The main objective is to run an application presented in the form of a Data Flow Graph (DFG) on a heterogeneous CPU/FPGA architecture in order to minimize the total running time or makespan criterion (Cmax). In this thesis, we have considered two case studies: a scheduling case taking into account the intercommunication delays and where the FPGA device can perform a single task at a time, and another case taking into account parallelism in the FPGA, which can perform several tasks in parallel while respecting the constraint surface. First, in the first case, we propose two new optimization approaches GAA (Genetic Algorithm Approach) and MGAA (Modified Genetic Algorithm Approach) based on genetic algorithms. We also propose to compare these algorithms to a Branch & Bound method. The proposed approaches (GAA and MGAA) offer a very good compromise between the quality of the solutions obtained (optimization makespan criterion) and the computational time required to perform large-scale problems, unlike to the proposed Branch & Bound and the other exact methods found in the literature. Second, we first implemented an updated method based on genetic algorithms to solve the temporal partitioning problem in an FPGA circuit using dynamic reconfiguration. This method provides good solutions in a reasonable running time. Then, we improved our previous MGAA approach to obtain a new approach called MGA (Multithreaded Genetic Algorithm), which allows us to provide solutions to the partitioning problem. In addition, we have also proposed an algorithm based on simulated annealing, called MSA (Multithreaded Simulated Annealing). These two proposed approaches which are based on metaheuristic methods provide approximate solutions within a reasonable time period to the scheduling and partitioning problems on a heterogeneous computing system

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Hadded, Mohamed. "Design and optimization of access control protocols in Vehicular Ad Hoc Networks (VANETs)." Electronic Thesis or Diss., Evry, Institut national des télécommunications, 2016. http://www.theses.fr/2016TELE0023.

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Les accidents routiers et leurs dommages représentent un problème croissant dans le monde entier. Dans ce contexte, les réseaux véhiculaires (VANETs) peuvent être déployés pour réduire les risques et pour améliorer le confort. Ils permettent aux véhicules d'échanger différents types de données qui vont des applications de sécurité et de gestion du trafic aux applications de confort. De nos jours, les applications de sécurité sont l’objet de beaucoup d'attention des chercheurs ainsi que des fabricants d'automobiles. Dans cette thèse, nous étudierons les applications critiques pour la sécurité routière visant à fournir une assistance dans des situations dangereuses ou difficiles. Notre objectif principal sera de proposer de nouveaux protocoles de contrôle d'accès au support de transmission (MAC) et de routage, qui peuvent s’adapter dynamiquement aux changements fréquents de topologies des VANETs. Après un aperçu des protocoles d’accès sans contention dans les VANETs, nous proposons des solutions basées sur la technique de division du temps: Time Division Multiple Access (TDMA). D’abord, nous nous concentrons sur le développement d’un nouveau protocole distribué (DTMAC), qui ne repose pas sur l’utilisation d’infrastructure. DTMAC utilise les informations de localisation et un mécanisme de réutilisation des slots pour assurer que les véhicules accèdent au canal efficacement et sans collision. Les résultats obtenus ont confirmé l’efficacité de notre protocole, DTMAC se comporte très significativement mieux que VeMAC (protocole MAC basé sur TDMA.) Ensuite nous proposons TRPM, un protocole de routage basé sur une approche cross-layer. Dans TRPM, l’ordonnancement des slots TDMA construit par DTMAC et la position de la destination sont utilisés pour choisir le meilleur relais. Les résultats montrent que TRPM offre de meilleures performances, du nombre moyen de relais et de la fiabilité de livraison des messages comparé à d’autres protocoles. Dans la deuxième partie de cette thèse, nous nous focaliserons sur les mécanismes centralisés d’allocation de slots qui utilisent des coordinateurs. D’abord, nous proposons CTMAC, un protocole basé sur TDMA centralisé utilisant les RSUs (RoadSide Units) pour créer et maintenir les ordonnancements. CTMAC met en œuvre un mécanisme qui permet d’empêcher les “Access Collisions” de se produire plus que deux fois entre les véhicules qui tentent d’acquérir un même slot disponible. Les résultats ont montré que CTMAC permet de mieux minimiser les collisions, ainsi que le surcoût généré pour créer et maintenir les ordonnancements par rapport aux protocoles MAC, basés sur TDMA distribué. Cependant, dans CTMAC, les véhicules roulant vite devront acquérir des nouveaux slots après une courte période de temps à chaque fois qu’ils quittent les zones de leurs RSUs courants. Cette situation rend les protocoles centralisés inefficaces et couteux dans les réseaux à grande vitesse. Afin de pallier à ce problème inhérent à l’utilisation des RSUs, nous adaptons un algorithme d’ordonnancement basé sur le clustering dans lequel certains véhicules sont élus pour gérer l'accès au canal. Ceci permet aux véhicules de rester attachés à leurs clusters plus longtemps. Pour ce faire, nous proposons 1- un protocole de clustering nommé AWCP afin de former des clusters stables avec une longue durée de vie. AWCP est basé sur l’algorithme de clustering pour les réseaux mobiles WCA dans lequel les têtes des clusters sont élues en se basant sur une fonction de poids. 2- Nous formulons le réglage des paramètres de protocole AWCP comme un problème d’optimisation multi-objective et nous proposons un outil d’optimisation qui combine la version multi-objective de l’algorithme génétique appelé NSGA-II avec le simulateur de réseau ns-2 pour trouver les meilleurs paramètres du protocole AWCP. 3- Nous proposons ASAS, une stratégie adaptative pour l’attribution des slots temporels basée sur une approche cross-layer entre TDMA et AWCP Road crashes and their damages represent a serious issue and are one of the main causes of people death. In this context, Vehicular Ad hoc NETworks (VANETs) are deployed to reduce the risk of road accident as well as to improve passengers’ comfort by allowing vehicles to exchange different kinds of data which ranges widely from road safety and traffic management to infotainment. Nowadays, safety applications are receiving a great deal of attention from researchers as well as from automobile manufacturers. In this thesis, we particularly focus on safety-critical applications, designed to provide drivers assistance in dangerous situations and to avoid accidents in highway environments. Such applications must guarantee to the vehicles access to the medium and have strict requirements regarding end-to-end delay and packet loss ratio. Therefore, our main goal is to propose new medium access control and routing protocols, which can efficiently adapt to frequent changing VANET network topologies. After a comprehensive overview of free-contention MAC protocols, we propose several solutions, based on Time Division Multiple Access Technique (TDMA). We have designed DTMAC, a fully distributed TDMA-based MAC protocol, which does not rely on an expensive infrastructure. DTMAC uses vehicles’ locations and a slot reuse concept to ensure that vehicles in adjacent areas have collision-free schedule. Using simulations, we prove that DTMAC provides a lower rate of access and merging collisions than VeMAC, a well-known TDMA based MAC protocol in VANET. Then, in order to ensure that event-driven safety messages can be sent over a long distance, we propose TRPM, a TDMA aware Routing Protocol for Multi-hop communication. Our routing scheme is based on a cross layer approach between the MAC and the routing layers, in which the intermediate vehicles are selected using TDMA scheduling information. Simulation results show that TRPM provides better performances in terms of average end-to-end delay, average number of hops and average delivery ratio. In the second part, we focus on coordinator-based TDMA scheduling mechanisms. First, we propose the Centralized TDMA based MAC protocol (CTMAC) which uses Road Side Units (RSUs) as a central coordinator to create and maintain the TDMA schedules. CTMAC implements an Access Collision Avoidance mechanism that can prevent the access collision problem occurring more than twice between the same vehicles that are trying to access the channel at the same time. Using simulation we show an improvement in terms of access and merging collisions as well as the overhead required to create and maintain the TDMA schedules compared to distributed scheduling mechanisms. However, in the CTMAC protocol, fast moving vehicles will need to compete for new slots after a short period of time when they leave their current RSU area, which makes a centralized scheduling approach very expensive. In order to further improve the performance of coordinator-based TDMA scheduling mechanisms, we focus on cluster-based TDMA MAC protocols in which some vehicles in the network are elected to coordinate the channel access, allowing the vehicles to remain connected with their channel coordinator for a longer period of time. To this end, first we propose an adaptive weighted clustering protocol, named AWCP, which is road map dependent and uses road IDs and vehicle directions to make the clusters’ structure as stable as possible. Then, we formulate the AWCP parameter tuning as a multi-objective problem and we propose an optimization tool to find the optimal parameters of AWCP to ensure its QoS. Next, we propose ASAS, an adaptive slot assignment strategy for a cluster-based TDMA MAC protocol. This strategy is based on a cross layer approach involving TDMA and AWCP. The objective is to overcome the inter-cluster interference issue in overlapping areas by taking into account vehicles’ locations and directions when the cluster head assign slots

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Jacobs, Roger S. "Optimization of daily flight training schedules." Thesis, Monterey, California: Naval Postgraduate School, 2014. http://hdl.handle.net/10945/41396.

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Approved for public release; distribution is unlimited. The daily flight schedule at Training Air Wing-Two (TW-2) is built manually each day by squadron scheduling officers (SKEDSOs). They rely on their intuition, experience and sound judgment to output a flight schedule. Each SKEDSO spends eight hours a day on this task, but currently there is no measure of the efficiency a given flight schedule. Our goal is to enhance the current planning process by alleviating many of the tedious tasks through an automated optimization program. To that end, this research develops Flight Training Scheduler (FTS), an optimization-based tool, to aid the SKEDSO in production of daily flight schedules. FTS allows the SKEDSO to place an objective, value-oriented metric on the total events scheduled. A typical instance of this problem for TW-2's Phase II students consists of approximately 30 students, 65 flight events and 35 instructor pilots. FTS provides fast, automated guidance to the SKEDSOs that can help them increase throughput of students in the advanced strike training syllabus.

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Pedraz, Ana Mana. "Stochastic optimization of aero-engine maintenance schedules." Thesis, Kingston University, 2010. http://eprints.kingston.ac.uk/20875/.

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In this thesis the maintenance scheduling optimization problem of a multi-component system is formulated as a multi-objective stochastic dynamic problem, which is solved by first transforming the multi-objective formulation into a single-objective one via the weighted-sum method, and then using an iterated two-stage stochastic linear programming approach to solve the stochastic problem. The main application is the maintenance of a commercial gas turbine aero-engine. The model determines optimal opportunistic replacement schedules considering both deterministic and stochastic engine configurations. The proposed methodology provides maintenance planners with a decision tool that simultaneously minimizes the expected total cost of providing the maintenance service, and the expected total number of service interruptions due to maintenance during a finite horizon. The analysis presented in this thesis considers the indentured configuration of a modular aero-engine and investigates the sensitivity of the solutions to variations in a number of critical parameters.

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Lemos, Julia Coelho. "Otimização da programação das limpezas em redes de trocadores de calor utilizando técnicas de programação matemática." Universidade do Estado do Rio de Janeiro, 2014. http://www.bdtd.uerj.br/tde_busca/arquivo.php?codArquivo=8676.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior Redes de trocadores de calor são bastante utilizadas na indústria química para promover a integração energética do processo, recuperando calor de correntes quentes para aquecer correntes frias. Estas redes estão sujeitas à deposição, o que causa um aumento na resistência à transferência de calor, prejudicando-a. Uma das principais formas de diminuir o prejuízo causado por este fenômeno é a realização periódica de limpezas nos trocadores de calor. O presente trabalho tem como objetivo desenvolver um novo método para encontrar a programação ótima das limpezas em uma rede de trocadores de calor. O método desenvolvido utiliza o conceito de horizonte deslizante associado a um problema de programação linear inteira mista (MILP). Este problema MILP é capaz de definir o conjunto ótimo de trocadores de calor a serem limpos em um determinado instante de tempo (primeiro instante do horizonte deslizante), levando em conta sua influência nos instantes futuros (restante do horizonte deslizante). O problema MILP utiliza restrições referentes aos balanços de energia, equações de trocadores de calor e número máximo de limpezas simultâneas, com o objetivo de minimizar o consumo de energia da planta. A programação ótima das limpezas é composta pela combinação dos resultados obtidos em cada um dos instantes de tempo.O desempenho desta abordagem foi analisado através de sua aplicação em diversos exemplos típicos apresentados na literatura, inclusive um exemplo de grande porte de uma refinaria brasileira. Os resultados mostraram que a abordagem aplicada foi capaz de prover ganhos semelhantes e, algumas vezes, superiores aos da literatura, indicando que o método desenvolvido é capaz de fornecer bons resultados com um baixo esforço computacional Heat exchanger networks are widely used in industry to promote heat recoveryby making hot and cold streams to exchange heat, however these networks are subjected to fouling, which causes an increase in heat transfer resistance, jeopardizing it. One of the main techniques used to diminish the effects of fouling is to perform periodical cleanings in the heat exchangers. This works goal is to develop a new method to find the optimal cleaning schedule for a heat exchanger network. The developed method uses a sliding horizon concept associated with a mixed integer linear programming problem. This MILP problem is capable of finding the optimal set of heat exchangers that must be cleaned at a certain instant (first instant of the sliding horizon), considering its influence on the further instants (the rest of the sliding horizon). The MILP problem consists of constraints corresponding to energy balances, heat exchanger equations and maximum number of cleanings.The problem objective function represents the energy consumption that must be minimized. The optimal cleaning schedule is formed by the combination of the results to each one of the time instants. The proposed approach was evaluated through its application in several cases presented in literature, including a large size example from a Brazilian refinery. The results show that the proposed approach was capable of finding similar and, sometimes, superior results compared to the literature ones, concluding that the developed method was capable of providing good results with low computational efforts

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Gonçalves, Caroline de Oliveira. "Desenvolvimento de técnicas de otimização da programação das limpezas de redes de trocadores de calor." Universidade do Estado do Rio de Janeiro, 2013. http://www.bdtd.uerj.br/tde_busca/arquivo.php?codArquivo=6540.

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Conselho Nacional de Desenvolvimento Científico e Tecnológico Trocadores de calor são equipamentos muito utilizados na indústria de processos com o objetivo de modificar a temperatura e/ou o estado físico de correntes materiais. Uma rede de trocadores de calor pode ser definida como um grupo de trocadores de calor interligados, a fim de reduzir as necessidades de energia de um sistema. No entanto, durante a operação de uma rede, a eficiência térmica dos trocadores de calor diminui devido à deposição. Esse efeito promove o aumento dos custos de combustível e das emissões de carbono. Uma alternativa para mitigar este problema baseia-se no estabelecimento de uma programação das limpezas dos trocadores de calor durante a operação de rede. Este tipo de abordagem ocasiona uma situação na qual ocorre um conflito de escolha: a limpeza de um trocador de calor pode recuperar a sua eficiência térmica, mas implica custos adicionais, tais como, mão-de-obra, produtos químicos, etc. Além disso, durante a limpeza, o trocador de calor tem de ser contornado por uma corrente de by-pass, o que aumenta temporariamente o consumo de energia. Neste contexto, o presente trabalho tem como objetivo explorar diferentes técnicas de otimização envolvendo métodos estocásticos e heurísticos. Com este objetivo foi desenvolvido um conjunto de códigos computacionais integrados que envolvem a simulação pseudo-estacionária do comportamento da rede relacionado com incrustações e a otimização da programação das limpezas deste tipo de sistema. A solução do problema indica os períodos de tempo para a limpeza de cada trocador de calor. Na abordagem estocástica empregada, os parâmetros do algoritmo genético, como probabilidade de crossover e probabilidade de mutação, foram calibrados para o presente problema. A abordagem heurística desenvolvida se deu através da sequência do conjunto de movimentos zero, um e dois. De forma alternativa, desenvolveu-se a metodologia heurística recursiva na qual os conjuntos de movimentos um e dois foram empregados recursivamente. Também foi desenvolvida a abordagem híbrida que consistiu em diferentes combinações da metodologia estocástica e heurística. A análise comparativa entre as metodologias empregadas teve como objetivo avaliar a abordagem mais adequada para o presente problema da programação das limpezas em termos de função objetivo e esforço computacional. O desempenho da abordagem proposta foi explorado através de uma série de exemplos, incluindo uma refinaria real brasileira. Os resultados foram promissores, indicando que as técnicas de otimização analisadas neste trabalho podem ser abordagens interessantes para operações que envolvam redes de trocadores de calor. Dentre as abordagens de otimização analisadas, a metodologia heurística desenvolvida no presente trabalho apresentou os melhores resultados se mostrando competitiva frente às abordagens comparadas da literatura Heat exchangers are devices widely used in many processes with the goal of changing the temperature and/or the physical state of the streams. A heat exchanger network (HEN) can be defined as a group of interconnected heat exchangers in order to reduce the energy requirements of a system and is widely used in process industries. However, during the operation of a HEN, the thermal effectiveness of the heat exchangers decreases due to fouling. This effect brings an increase of the fuel costs and carbon emissions. A possible approach to mitigate this problem is based on the establishment of a heat exchanger cleaning schedule during the refinery operation. This kind of intervention brings a tradeoff: the cleaning of a heat exchanger can restore its thermal effectiveness, but implies in additional costs, such as, manpower, chemicals, etc. Additionally, during the cleaning, the heat exchanger must be bypassed which temporally increases the energy consumption. In this context, the present work aims to explore different optimization techniques involving stochastic and heuristic methods. For this purpose, it was developed a set of integrated computational codes involving a pseudo-stationary simulation of HEN behavior related to fouling and schedule optimization of cleaning this type of system. The solution of the problem indicates for the operating staff the time periods for the cleaning of each heat exchanger in the crude preheat train. In the stochastic approach used, the parameters of the genetic algorithm, as the probability of crossover and mutation, have been calibrated to the present problem. The developed heuristic approach was made through the sequence of motions set of zero, one and two. Alternatively, the methodology developed in which the recursive heuristic move sets one and two were used recursively. The hybrid approach consisting of different combinations of stochastic and heuristic methodology was also developed. A comparative analysis of methodologies aimed at assessing the most appropriate approach to this problem of scheduling the cleaning in terms of computational effort and objective function. The performance of the proposed approach was explored by a series of examples including a real Brazilian refinery. The results were promising, suggesting that the optimization techniques of this work may be interesting approaches to operations involving HENs. Among the analyzed optimization approaches, the heuristic methodology developed in this work showed the best results showing competitive front approaches compared to the literature

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Ramakrishnan, Jagdish. "Dynamic optimization of fractionation schedules in radiation therapy." Thesis, Massachusetts Institute of Technology, 2013. http://hdl.handle.net/1721.1/82181.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2013. This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections. Cataloged from student-submitted PDF version of thesis. Includes bibliographical references (p. 145-156). In this thesis, we investigate the improvement in treatment effectiveness when dynamically optimizing the fractionation scheme in radiation therapy. In the first part of the thesis, we consider delivering a different dose each day depending on the observed patient anatomy. Given that a fixed prescribed dose must be delivered to the tumor over the course of the treatment, such an approach results in a lower cumulative dose to a radio-sensitive organ-at-risk when compared to that resulting from standard fractionation. We use the dynamic programming algorithm to solve the problem exactly. Next, we suggest an approach which optimizes the fraction size and selects a treatment plan from a plan library. Computational results from patient datasets indicate this approach is beneficial. In the second part of the thesis, we analyze the effect of repopulation on the optimal fractionation scheme. A dynamic programming framework is developed to determine an optimal fractionation scheme based on a model of cell kill due to radiation and tumor growth in between treatment days. We prove that the optimal dose fractions are increasing over time. We find that the presence of accelerated tumor repopulation suggests larger dose fractions later in the treatment to compensate for the increased tumor proliferation. by Jagdish Ramakrishnan. Ph.D.

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Sendil, Halil. "Operation Of Water Distribution Networks." Master's thesis, METU, 2013. http://etd.lib.metu.edu.tr/upload/12615484/index.pdf.

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With continuously increasing urbanization, consumer demands and expansion of water supply systems, determination of efficient pump schedules became a more difficult task. Pumping energy costs constitute a significant part of the operational cost of the water distribution networks. This study aims to provide an effective daily pump schedule by minimizing the energy costs for constant and also for multi tariff of electricity (3 Kademeli Elektrik Tarifesi) in water distribution network. A case study has been performed in an area covering N8.3 and N7 pressure zones which are parts of Ankara water distribution network. Both pressure zones consists of 3 multiple pumps in pump station and one tank having 5000 m3 storage volume each. By using genetic algorithm based software (WaterCAD Darwin Scheduler) least-cost pump scheduling and operation policy for each pump station has been determined while satisfying target hydraulic performance requirements such as minimum and maximum service pressures, final water level of storage tank and maximum velocity in pipeline. 32 different alternative scenarios have been created which include multi tariff energy prices, constant tariff energy price, insulated system condition, uninsulated system condition and different pump combinations. The existing base scenario and alternative scenarios which were prepared by using optimal pump schedules have been compared and the achievements of optimizing pump operation have been analyzed. At the end of the study, a satisfying result has been observed that by using determined optimal pump schedule, minimum % 14 of total energy cost can be saved in existing water supply system.

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Страмко, С. М. "Створення програмного забезпечення для складання розкладу університету". Thesis, Чернігів, 2020. http://ir.stu.cn.ua/123456789/23533.

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Страмко, С. М. Створення програмного забезпечення для складання розкладу університету : випускна кваліфікаційна робота : 123 "Комп’ютерна інженерія" / С. М. Страмко ; керівник роботи П. Г. Бивойно ; НУ "Чернігівська політехніка", кафедра інформаційних та комп’ютерних систем. – Чернігів, 2020. – 71 с. Дана дипломна робота присвячена розробці програмного продукту для формування розкладу навчальних занять з використанням суб’єктивних переваг. Метою роботи є розробка програмного модуля, що базується на генетичних алгоритмах. Запропоновано використання цільових функцій при визначенні якості розкладу. Розроблено метод генерації потенційних розкладів на основі використання генетичного алгоритму. Визначено структурні особливості та конструктивні елементи цільової функції. This project is devoted to developing software to form the schedule of training sessions with the use of subjective preferences. The aim is to develop a software module based on genetic algorithms. The use of target functions in determining the quality of the schedule. The method of generating the potential schedules based on genetic algorithm. The structural features and structural elements of the objective function.

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Joborn, Martin. "Optimization of empty freight car distribution in scheduled railways /." Linköping : Univ, 2001. http://www.bibl.liu.se/liupubl/disp/disp2001/tek671s.pdf.

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Hariharan, Rema. "Bicriteria optimization of schedules on one and two machines." Thesis, Virginia Polytechnic Institute and State University, 1988. http://hdl.handle.net/10919/80042.

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The practical applications of scheduling generally involve the optimization of more than one criterion. This thesis focuses on the bicriteria optimization problem of scheduling jobs on single and two machines. The optimization criteria that are considered are those of minimization of maximum tardiness and minimization of the total number of tardy jobs in the schedule. The former is considered as the primary criterion while the latter is considered as the secondary criterion. For the single machine problem, a search tree method is presented which is based on the implementation of some new dominance rules. Computational results presented show that the performance of this algorithm is better than that of an earlier work reported in the literature. For the two machine problem, a heuristic algorithm is developed to minimize maximum tardiness. Computational results are presented regarding the performance of this heuristic. A search tree method is developed for the optimization of the secondary criterion. This search tree method is similar to that for the single machine problem except that it does not use the dominance rules that were developed for the single machine case. Computational experience is presented for this algorithm. Master of Science

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Pupeikienė, Lina. "Investigation and Applikation of Profilled Schools Schedulling Tasks Optimimization Methods." Doctoral thesis, Lithuanian Academic Libraries Network (LABT), 2009. http://vddb.library.lt/obj/LT-eLABa-0001:E.02~2009~D_20090608_173743-06877.

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The problem of profiled school scheduling is important for Lithuanian schools and for similar schools in many other countries. No polynomial time methods are known for this problem. The objective of this PhD thesis is to investigate heuristic methods for optimization of profiled school schedules. The convenience of application in real-life situations is provided by the vector optimization approach using platform-independent software implementation. The task of experimental investigation is to select such parameters of heuristic methods that minimize expected deviation from the optimum. Four optimization methods were regarded: Local Deterministic (LD), Local Randomized (LR), Simulated Annealing (SA), and SA with parameters optimized using the Bayesian approach (BA). The composite method of AM and BA provided the best results. In Chapter 1 of the dissertation, various aspects of work of optimization methods as well as popular program languages suitable for school schedule optimization are analyzed. Literature about school scheduling is analysed. In Chapter 2, conclusions are drawn how the optimization of heuristic parameters influences the speed and accuracy of finding the optimal solution. A technical rating analysis of popular schedule programs is made and technical disadvantages are listed. Criteria for evaluating the quality of results are proposed that include heuristic parameters in search of optimal schedules. Recommendations are states how to assess the choice and... [to full text] Profiliuotos mokyklos tvarkaraščio kūrimas yra aktualus uždavinys tiek Lietuvoje, tiek kitose šalyse. Nėra žinoma polinominių būdų šiai problemai spręsti. Pagrindinis šios daktaro disertacijos objektas yra ištirti euristinius metodus, skirtus profiliuotos mokyklos tvarkaraščio optimizavimui. Tvarkaraščio formavimo kriterijai, kurie yra reikalingi realiame gyvenime, nustatomi vektorinio optimizavimo metodais bei realizuojami nuo operacinės sistemos nepriklausoma programine įranga. Eksperimentinių tyrimų uždavinys – surasti tokius euristinių metodų parametrus, kurie minimizuotų numatytą nuokrypį. Disertacijoje aprašomi keturi optimizavimo metodai: lokalus determinuotas (LD), lokalus atsitiktinis (LA), atkaitinimo modeliavimo (AM) ir AM parametrų optimizavimas naudojant Bayes (BA) metodą. Kombinuotas AM ir Bayes metodas duoda geriausius rezultatus. Pirmajame apžvelgiama su mokyklos tvarkaraščių formavimu susijusi literatūra. Analizuojami tinkamiausi optimizavimo metodų darbo aspektai. Analizuojamos populiariausios programavimo kalbos, tinkančios kurti mokyklų tvarkaraščių optimizavimo programą. Antrajame skyriuje formuluojamas profiliuotų mokyklų tvarkaraščio kūrimo matematinis modelis. Analizuojami profiliuotose mokyklose naudojami euristiniai parametrai. Atlikti populiarių tvarkaraščių programų vertinimai ir analizės. Įvardijami šių programų trūkumai. Trečiajame skyriuje, remiantis 2 skyriaus analize ir išvadomis, pateiktas profiliuotos mokyklos lanksčios tvarkaraščio... [toliau žr. visą tekstą]

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Pupeikienė, Lina. "Optimizavimo metodų tyrimas ir taikymas profiliuotų mokyklų tvarkaraščių sudarymo uždaviniuose." Doctoral thesis, Lithuanian Academic Libraries Network (LABT), 2009. http://vddb.library.lt/obj/LT-eLABa-0001:E.02~2009~D_20090608_180419-54501.

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Profiliuotos mokyklos tvarkaraščio kūrimas yra aktualus uždavinys tiek Lietuvoje, tiek kitose šalyse. Nėra žinoma polinominių būdų šiai problemai spręsti. Pagrindinis šios daktaro disertacijos objektas yra ištirti euristinius metodus, skirtus profiliuotos mokyklos tvarkaraščio optimizavimui. Tvarkaraščio formavimo kriterijai, kurie yra reikalingi realiame gyvenime, nustatomi vektorinio optimizavimo metodais bei realizuojami nuo operacinės sistemos nepriklausoma programine įranga. Eksperimentinių tyrimų uždavinys – surasti tokius euristinių metodų parametrus, kurie minimizuotų numatytą nuokrypį. Disertacijoje aprašomi keturi optimizavimo metodai: lokalus determinuotas (LD), lokalus atsitiktinis (LA), atkaitinimo modeliavimo (AM) ir AM parametrų optimizavimas naudojant Bayes (BA) metodą. Kombinuotas AM ir Bayes metodas duoda geriausius rezultatus. Pirmajame apžvelgiama su mokyklos tvarkaraščių formavimu susijusi literatūra. Analizuojami tinkamiausi optimizavimo metodų darbo aspektai. Analizuojamos populiariausios programavimo kalbos, tinkančios kurti mokyklų tvarkaraščių optimizavimo programą. Antrajame skyriuje formuluojamas profiliuotų mokyklų tvarkaraščio kūrimo matematinis modelis. Analizuojami profiliuotose mokyklose naudojami euristiniai parametrai. Atlikti populiarių tvarkaraščių programų vertinimai ir analizės. Įvardijami šių programų trūkumai. Trečiajame skyriuje, remiantis 2 skyriaus analize ir išvadomis, pateiktas profiliuotos mokyklos lanksčios tvarkaraščio... [toliau žr. visą tekstą] The problem of profiled school scheduling is important for Lithuanian schools and for similar schools in many other countries. No polynomial time methods are known for this problem. The objective of this PhD thesis is to investigate heuristic methods for optimization of profiled school schedules. The convenience of application in real-life situations is provided by the vector optimization approach using platform-independent software implementation. The task of experimental investigation is to select such parameters of heuristic methods that minimize expected deviation from the optimum. Four optimization methods were regarded: Local Deterministic (LD), Local Randomized (LR), Simulated Annealing (SA), and SA with parameters optimized using the Bayesian approach (BA). The composite method of AM and BA provided the best results. In Chapter 1 of the dissertation, various aspects of work of optimization methods as well as popular program languages suitable for school schedule optimization are analyzed. Literature about school scheduling is analysed. In Chapter 2, conclusions are drawn how the optimization of heuristic parameters influences the speed and accuracy of finding the optimal solution. A technical rating analysis of popular schedule programs is made and technical disadvantages are listed. Criteria for evaluating the quality of results are proposed that include heuristic parameters in search of optimal schedules. Recommendations are states how to assess the choice and... [to full text]

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Зінченко, Людмила Вікторівна. "Інформаційна рекомендаційна система в сфері освітніх послуг". Master's thesis, КПІ ім. Ігоря Сікорського, 2019. https://ela.kpi.ua/handle/123456789/31409.

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Магістерська дисертація: 85 с., 7 рис., 23 табл., 29 джерел, 1 додаток. Актуальність. Сьогодні є актуальною онлайн-освіта. На жаль, в Україні мало альтернативних ресурсів, де б можна було отримати онлайн-допомогу з різних предметних областей. Все більше учнів, студентів, людей, які перекваліфіковуючись чи просто хочуть розвиватися шукають способи отримати нові теоретичні знання та практичні навички онлайн. Надзвичайно важко самостійно опанувати великий потік інформації, яку б предметну область не вивчали учні, і тому необхідна допомога професіоналів. Тож великою цінністю представляється функціонал щодо розкладу. Для вирішення проблеми, як реалізувати цю частину функціоналу, буде поставлена і розв’язана нова математична задача, яка дасть можливість і підґрунтя вирішувати подібні проблеми. Зв'язок роботи з науковими програмами, планами, темами. Робота виконувалась на філії кафедри автоматизованих систем обробки інформації та управління Національного технічного університету України «Київський політехнічний інститут ім. Ігоря Сікорського» у рамках науково-дослідницької теми Інституту кібернетики ім. В. М. Глушкова НАН України ВФ.180.11 «Розробити математичний апарат, орієнтований на створення інтелектуальних інформаційних технологій розв'язування проблем комбінаторної оптимізації та інформаційної безпеки» (2017-2021 рр.), що виконується за Постановою бюро Відділення інформатики НАН України від 23.06.2016 р. № 2. Мета роботи – підвищення якості інформування потенційних споживачів та інтелектуалізація процесів надання освітніх послуг онлайн, шляхом розробки оригінального програмно-алгоритмічного забезпечення та реалізації його у вигляді спеціалізованої програмної системи. Для досягнення мети необхідно виконати наступні завдання:  виконати огляд існуючих постановок задач у сфері освіти;  виконати огляд існуючих методів розв’язання задач складання розкладу;  здійснити порівняльний аналіз різних методів та моделей та класифікувати їх;  формалізувати задачу складання розкладу для менторів та учнів;  розробити алгоритм локального пошуку і мурашиний алгоритм;  виконати аналіз експериментальних досліджень;  розробити програмне забезпечення для надання послуг у сфері освіти;  розробити стартап-проект. Об’єкт дослідження – процес побудови розкладу для менторів і учнів, який задовольняє певним критеріям. Предмет дослідження – методи та моделі задач комбінаторної оптимізації в задачах теорії розкладів. Наукова новизна одержаних результатів полягає у постановці та аналізі нової задачі, а також у дослідження методів розв’язання цієї задачі, розробці методів локального пошуку та мурашиного алгоритму для поставленої задачі складання розкладу онлайн занять. Публікації. Матеріали роботи опубліковані в міжнародних наукових журналах «INNOVATIVE SOLUTIONS IN MODERN SCIENCE» (№6 (33), 2019), та «POLISH JOURNAL OF SCIENCE» (№16, 2019), а також у тезах міжнародних науково-практичних конференцій «Математичне та імітаційне моделювання систем» (МОДС 2019), «Інформаційні системи та технології управління» (ІСТУ-2019). Master's thesis: 85 p., 7 figures, 23 tables, 29 sources, 1 applications. Relevance: Online education is relevant today. Unfortunately, there are few alternative resources in Ukraine where online help can be obtained from various subject areas. More and more students from schools and universities, people who are retraining or just looking to develop are looking for ways to gain new theoretical knowledge and practical skills online. It is extremely difficult to master a large flow of information on your own, whatever the subject area is not learned by students, and therefore requires the help of professionals. Therefore, scheduling functionality is of great value. To solve the problem of how to implement this part of the functionality, a new mathematical problem will be posed and solved, which will give the opportunity and the basis for solving such problems. Connection of the thesis with scientific programs, plans, topics. The thesis was written at the branch of The Department of Computer-aided management and data processing systems of the National Technical University of Ukraine «Igor Sikorsky Kyiv Polytechnic Institute» at the V. M. Glushkov Institute of Cybernetics of the National Academy of Sciences of Ukraine under the topic VF.180.11 «To develop a mathematical apparatus focused on the creation of intelligent information technologies for solving combinatorial optimization and information security problems» (2017-2021 biennium), which is executed by the Resolution of the Bureau of Informatics of the National Academy of Sciences of Ukraine from 23.06.2016 р. № 2. The purpose of the study is improving the quality of informing potential consumers and intellectualizing the processes of providing educational services online, by developing original software and algorithmic software and implementing it in the form of a specialized software system.. To achieve this goal, you must complete the following tasks: − review the existing formulations of educational tasks; − review existing methods for scheduling tasks; − carry out comparative analysis of different methods and models and classify them; − formalize the timetable for mentors and students; − develop a local search algorithm and an ant algorithm; − carry out the analysis of experimental studies; − develop software to provide educational services; − develop a startup project. The object of study is a process for scheduling mentors and students that meets certain criteria. The subject of study is methods and models of combinatorial optimization problems in scheduling theory problems. The scientific novelty of the results is the formulation and analysis of a new task, as well as the study of methods for solving this problem, the development of methods of local search and ant algorithm for the task of scheduling online classes. Publications. Work materials have been published in the international scientific journals «INNOVATIVE SOLUTIONS IN MODERN SCIENCE» (№6 (33), 2019) and «POLISH JOURNAL OF SCIENCE» (№16, 2019), as well as in theses of international scientific and practical conferences «Mathematical and systems simulation» (MODS 2019), «Information systems and control technologies» (ISTU-2019).

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Lichei, Andre. "Analysis and Optimization of the Packet Scheduler in Open MPI." Master's thesis, Universitätsbibliothek Chemnitz, 2006. http://nbn-resolving.de/urn:nbn:de:swb:ch1-200601910.

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We compared well known measurement methods for LogGP parameters and discuss their accuracy and network contention. Based on this, a new theoretically exact measurement method that does not saturate the network is derived and explained in detail. The applicability of our method is shown for the low level communication API of Open MPI across several interconnection networks. Based on the LogGP model, we developed a low overhead packet scheduling algorithm. It can handle different types of interconnects with different characteristics. It is able to produce schedules which are very close to the optimum for both small and large messages. The efficiency of the algorithm for small messages is show for a Open MPI implementation. The implementation uses the LogGP benchmark to obtain the LogGP parameters of the available interconnects and can so adapt to any given system.

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Harunuzzaman, Mohammad. "Optimization of standby safety system maintenance schedules under reliability constraints /." The Ohio State University, 1994. http://rave.ohiolink.edu/etdc/view?acc_num=osu1487850665559726.

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Berrebi, Simon Jonas Youna. "A real-time bus dispatching policy to minimize headway variance." Thesis, Georgia Institute of Technology, 2014. http://hdl.handle.net/1853/51899.

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Transit agencies include buffer time in their schedules to maintain stable headways and avoid bus bunching. In this work, a real-time holding mechanism is proposed to dispatch buses on a loop-shaped route, solely based on operating conditions in real-time. Holds are applied at the terminal station to minimize the expected variance of bus headways at departure. The bus-dispatching problem is formulated as a stochastic decision process. The optimality equations are derived and structural properties of the optimal policy are inferred by backward induction. The exact optimal holding policy is then found in closed form, as a function of the expected travel time of buses currently running. A simulation assuming stochastic operating conditions and unstable headway dynamics is performed to assess the expected average waiting time of passengers at stations. The proposed control strategy is found to provide lower passenger waiting time and better resiliency than methods recommended in the literature and used in practice.

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Shu, Yan. "Future aircraft networks and schedules." Diss., Georgia Institute of Technology, 2011. http://hdl.handle.net/1853/41221.

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This thesis has focused on an aircraft schedule and network design problem that involves multiple types of aircraft and flight service. First, this thesis expands a business model for integrating on-demand flight services with the traditional scheduled flight services. Then, this thesis proposes a three-step approach to the design of aircraft schedules and networks from scratch. After developing models in the three steps and creating large-scale instances of these models, this dissertation develops iterative algorithms and subproblem approaches to solving these instances, and it presents computational results of these large-scale instances. To validate the models and solution algorithms developed, this thesis compares the daily flight schedules that it designed with the schedules of the existing airlines. In addition, it discusses the implication of using new aircraft in the future flight schedules. Finally, future research in three areas--model, computational method, and simulation for validation--is proposed.

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Andersson, Viktor. "Optimerad schemaläggning av mötesbokningar." Thesis, Mittuniversitetet, Institutionen för informationssystem och –teknologi, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-39342.

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Kommunikation är en grundpelare för alla verksamheter och företag där möten är ett av de primära sätten för att samtala och fatta gemensamma beslut. Problemet som kan uppstå i samband med att en bokning av ett möte ska utföras är att försöka finna en tid då alla önskade mötesdeltagare kan delta vilket kan vara en tröttsam och tidskrävande process om många deltagare ska ingå i mötet. Detta är ett bekymmer som uppstår hos IT-företaget Easit som fokuserar på mjukvarulösningar åt företag och myndigheter. Arbetet syftar till att undersöka de anställdas uppfattning kring mötesbokningar, vilka verktyg de använder i dagsläget för att boka möten och slutligen formulera och implementera en byggsten i form av en målfunktion för att förhindra de problem som beskrivs i undersökningen. Konstruktionen sker i form av en webbapplikation skapat med främst programmeringsspråket Java men också olika ramverk och verktyg för att förenkla processen i att uppnå en dynamisk applikation. Applikationen upprättar koppling till Microsoft Outlooks API där data sedan extraheras från kalendrar baserat på delvis modifierad data från en anställds schema på företaget. Målfunktionen tillämpas på den data som extraherats för villkor som användaren fyllt i, på det vis beräkna ett slags betyg för potentiella mötesbokningar. Målfunktionen som är en optimerad algoritm jämförs med en greedy-algoritm för att presentera den optimerade algoritmens potential för problembeskrivningen. Den fortsatta utvecklingen utförs genom att formulera bivillkor vars syfte är att bredda den optimerade algoritmens flexibilitet och djup. Resultatet för arbetet är en grund för optimering av scheman med potential för fortsatt utveckling. Communication is a foundation pillar for all businesses and companies where meetings is one of the primary ways to converse and take collective decisions. The problem which can arise in the procedure of booking a meeting is trying to find a suitable time for every desired participant which could be a tedious and time-consuming task if many participants are to be included in the meeting. This is an issue that has risen at an IT company named Easit which focuses on software solutions for other companies and authorities. The aim of the project is to investigate the employees opinion of this issue, the tools they use today for the process of booking a meeting and finally formulate and implement a building block in the form of a target function which will be used to prevent the problems that are stated in the investigation. The construction is to be performed in the form of a web application created with the programming language Java together with different frameworks and tools to simplify the process of achieving a dynamic application. The application establishes a connection to the Microsoft Outlook API which will then be used to extract data from different calendars based of partly modified data from an employee’s schedule. The target function will be applied to the data extracted dependent on the conditions stated by the user and based on that; a kind of grade will be applied to every possible meeting time found. The target function which is an optimized algorithm is compared to a greedy-algorithm to present the optimized functions potential for the problem specified. If future work is to be done on the project, the main focus should lie on formulating additional constraints and parameters which can widen the optimized algorithm flexibility and depth. The result for this project is a foundation for optimizing schedules depending on multiple calendars together with potential for future work.

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Li, Fengfeng. "Multi-criteria optimization of group replacement schedules for distributed water pipeline assets." Thesis, Queensland University of Technology, 2014. https://eprints.qut.edu.au/66195/1/Fengfeng_Li_Thesis.pdf.

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This thesis presents a multi-criteria optimisation study of group replacement schedules for water pipelines, which is a capital-intensive and service critical decision. A new mathematical model was developed, which minimises total replacement costs while maintaining a satisfactory level of services. The research outcomes are expected to enrich the body of knowledge of multi-criteria decision optimisation, where group scheduling is required. The model has the potential to optimise replacement planning for other types of linear asset networks resulting in bottom-line benefits for end users and communities. The results of a real case study show that the new model can effectively reduced the total costs and service interruptions.

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Dissertations / Theses on the topic 'The schedule optimization'

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