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Dissertations / Theses on the topic 'Optimization metaheuristics'

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1

Skidmore, Gerald. "Metaheuristics and combinatorial optimization problems /." Online version of thesis, 2006. https://ritdml.rit.edu/dspace/handle/1850/2319.

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Ahmed, Abdel-Rahman Hedar A. "Studies on metaheuristics continuous global optimization problems." 京都大学 (Kyoto University), 2004. http://hdl.handle.net/2433/145313.

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3

Colak, Selcuk. "Neural networks based metaheuristics for solving optimization problems." [Gainesville, Fla.] : University of Florida, 2006. http://purl.fcla.edu/fcla/etd/UFE0013500.

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4

Blum, Christian. "Metaheuristics for Group Shop Scheduling." Doctoral thesis, Universite Libre de Bruxelles, 2002. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/211345.

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5

Höghäll, Anton. "Tuning of Metaheuristics for Systems Biology Applications." Thesis, Linköping University, Department of Electrical Engineering, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-58842.

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<p>In the field of systems biology the task of finding optimal model parameters is a common procedure. The optimization problems encountered are often multi-modal, i.e., with several local optima. In this thesis, a class of algorithms for multi-modal problems called metaheuristics are studied. A downside of metaheuristic algorithms is that they are dependent on algorithm settings in order to yield ideal performance.This thesis studies an approach to tune these algorithm settings using user constructed test functions which are faster to evaluate than an actual biological model. A statistical pr
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Munera, Ramirez Danny. "Solving Hard Combinatorial Optimization Problems using Cooperative Parallel Metaheuristics." Thesis, Paris 1, 2016. http://www.theses.fr/2016PA01E074.

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Les Problèmes d’Optimisation Combinatoire (COP) sont largement utilisés pour modéliser et résoudre un grand nombre de problèmes industriels. La résolution de ces problèmes pose un véritable défi en raison de leur inhérente difficulté, la plupart étant NP-difficiles. En effet, les COP sont difficiles à résoudre par des méthodes exactes car la taille de l’espace de recherche à explorer croît de manière exponentielle par rapport à la taille du problème. Les méta-heuristiques sont souvent les méthodes les plus efficaces pour résoudre les problèmes les plus difficiles. Malheureusement, bien des pro
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Almakhlafi, Ahmad. "The generator maintenance scheduling problem : benchmarks, local search and metaheuristics." Thesis, University of Manchester, 2016. https://www.research.manchester.ac.uk/portal/en/theses/the-generator-maintenance-scheduling-problembenchmarks-local-search-and-metaheuristics(b36d7f0f-93f7-4388-8ad9-4e84ae8fc245).html.

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Scheduling problems are common in a wide range of real-world industries and strategies for tackling them can impact on profits significantly. The careful planning and precise timing of industrial events and processes can maximize the utilization of resources, improve efficiency and reduce costs. One important type of scheduling problem from the domain of maintenance planning is the Generator Maintenance Scheduling Problem (GMSP) in the power industry. This thesis makes three broad contributions. First, we introduce a set of 23 real-world instances of the problem of different characteristics an
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Vianna, Neto Julio Xavier. "Wind turbine blade geometry design based on multi-objective optimization using metaheuristics." reponame:Repositório Institucional da UFPR, 2013. http://hdl.handle.net/1884/30337.

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Abstract: The application of Evolutionary Algorithms (EAs) to wind turbine blade design can be interesting, by reducing the number of aerodynamic-to-structural design loops in the conventional design process, hence reducing the design time and cost. Recent developments showed satisfactory results with this approach, mostly combining Genetic Algorithms (GAs) with the Blade Element Momentum (BEM) theory. The general objective of the present work is to define and evaluate a design methodology for the rotor blade geometry in order to maximize the energy production of wind turbines and minimize the
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Balaprakash, Prasanna. "Estimation-based metaheuristics for stochastic combinatorial optimization: case studies in sochastic routing problems." Doctoral thesis, Universite Libre de Bruxelles, 2010. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/210179.

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Stochastic combinatorial optimization problems are combinatorial optimization problems where part of the problem data are probabilistic. The focus of this thesis is on stochastic routing problems, a class of stochastic combinatorial optimization problems that arise in distribution management. Stochastic routing problems involve finding the best solution to distribute goods across a logistic network. In the problems we tackle, we consider a setting in which the cost of a solution is described by a random variable; the goal is to find the solution that minimizes the expected cost. Solving such s
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10

Lomonaco, Marco. "Ant colony optimization metaheuristics to solve an assignment problem in urban freight transport context." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2017. http://amslaurea.unibo.it/12997/.

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In un mondo che deve necessariamente ambire a crescere in modo sostenibile, ogni attività umana ha il dovere di rispettare l'ambiente limitando gli sprechi: l'ottimizzazione delle risorse a disposizione è fondamentale. Ottimizzazione è la parola chiave di questo elaborato, dove viene esaminata l'innovativa possibilità di trasportare merci e persone contemporaneamente, sfruttando un'unica infrastruttura. Il trasporto merci in ambito urbano infatti oggi viene effettuato quasi esclusivamente tramite camion, comportando grandi svantaggi facilmente individuabili nell'aumento del traffico e dell'in
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Beume, Nicola Verfasser], Günter [Akademischer Betreuer] [Rudolph, and Christian [Akademischer Betreuer] Igel. "Hypervolume based metaheuristics for multiobjective optimization / Nicola Beume. Betreuer: Günter Rudolph. Gutachter: Christian Igel." Dortmund : Universitätsbibliothek Dortmund, 2012. http://d-nb.info/109831235X/34.

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12

Birattari, Mauro. "The problem of tuning metaheuristics as seen from the machine learning perspective." Berlin Aka, 2005. http://deposit.ddb.de/cgi-bin/dokserv?id=2677752&prov=M&dok_var=1&dok_ext=htm.

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13

Chu, Andrej. "Metaheuristická metóda mravčej kolónie pri riešení kombinatorických optimalizačných úloh." Doctoral thesis, Vysoká škola ekonomická v Praze, 2005. http://www.nusl.cz/ntk/nusl-76766.

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The Ant Colony Optimization belongs into the metaheuristic methods category and it has been developing quite recently. So far it has shown its capabalities to over-perform other metaheuristic methods in quality of the solutions. This work brings analysis of the possible applications of the method on the classical optimization combinatorial problems -- traveling salesman problem, vehicle routing problem, knapsack problem, generalized assignment problem and maximal clique problem. It also deals with the practical experiments with application on several optimization problems and analysis of the t
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14

Labidi, Mohamed Khalil. "Parallelisation of hybrid metaheuristics for COP solving." Thesis, Paris Sciences et Lettres (ComUE), 2018. http://www.theses.fr/2018PSLED029/document.

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L’Optimisation Combinatoire (OC) est un domaine de recherche qui est en perpétuel changement. Résoudre un problème d’optimisation combinatoire (POC) consiste essentiellement à trouver la ou les meilleures solutions dans un ensemble des solutions réalisables appelé espace de recherche qui est généralement de cardinalité exponentielle en la taille du problème. Pour résoudre des POC, plusieurs méthodes ont été proposées dans la littérature. On distingue principalement les méthodes exactes et les méthodes d’approximation. Ne pouvant pas viser une résolution exacte de problèmes NP-Complets lorsque
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15

Sghir, Inès. "A Multi-Agent based Optimization Method for Combinatorial Optimization Problems." Thesis, Angers, 2016. http://www.theses.fr/2016ANGE0009/document.

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Nous élaborons une approche multi-agents pour la résolution des problèmes d’optimisation combinatoire nommée MAOM-COP. Elle combine des métaheuristiques, les systèmes multi-agents et l’apprentissage par renforcement. Les heuristiques manquent d’une vue d’ensemble sur l’évolution de la recherche. Notre objectif consiste à utiliser les systèmes multi-agents pour créer des méthodes de recherche coopératives. Ces méthodes explorent plusieurs métaheuristiques. MAOM-COP est composée de plusieurs agents qui sont l’agent décideur, les agents intensificateurs et les agents diversificateurs (agents croi
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Calvet, Liñán Laura. "From metaheuristics to learnheuristics: Applications to logistics, finance, and computing." Doctoral thesis, Universitat Oberta de Catalunya, 2017. http://hdl.handle.net/10803/667118.

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Un gran nombre de processos de presa de decisions en sectors estratègics com el transport i la producció representen problemes NP-difícils. Sovint, aquests processos es caracteritzen per alts nivells d'incertesa i dinamisme. Les metaheurístiques són mètodes populars per a resoldre problemes d'optimització difícils en temps de càlcul raonables. No obstant això, sovint assumeixen que els inputs, les funcions objectiu, i les restriccions són deterministes i conegudes. Aquests constitueixen supòsits forts que obliguen a treballar amb problemes simplificats. Com a conseqüència, les solucions poden
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17

Ghaffari, Mejlej Vahid [Verfasser]. "Adaptive search approach in the multidisciplinary optimization of lightweight structures using hybrid metaheuristics / Vahid Ghaffari Mejlej." München : Verlag Dr. Hut, 2019. http://d-nb.info/1202169643/34.

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18

Di, Cesare Noëlie. "Développement d'une nouvelle méthode metaheuristique pour l'optimisation topologique des structures et des metamatériaux." Thesis, Belfort-Montbéliard, 2016. http://www.theses.fr/2016BELF0299/document.

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L’optimisation offre la possibilité, dans de nombreux domaines, d’améliorer les performances d’unsystème donné, qu’il soit physique ou mathématique. Depuis quelques décennies, les méthodesd’optimisation metaheuristiques ont fait leurs preuves, notamment dans le domaine de la mécanique.Du grec meta signifiant "un niveau au dessus", les metaheuristiques permettent de s’affranchir ducalcul des sensibilités souvent problématique quant à la résolution de problèmes d’optimisationcomplexes et/ou NP difficiles. En outre, elles ont la capacité à analyser simultanément l’ensemble dudomaine des solutions
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19

Kafafy, Ahmed. "Hybrid Evolutionary Metaheuristics for Multiobjective Decision Support." Thesis, Lyon 1, 2013. http://www.theses.fr/2013LYO10184/document.

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La prise de décision est une partie intégrante de notre vie quotidienne où le décideur est confronté à des problèmes composés de plusieurs objectifs habituellement contradictoires. Dans ce travail, nous traitons des problèmes d'optimisation multiobjectif dans des espaces de recherche continus ou discrets. Nous avons développé plusieurs nouveaux algorithmes basés sur les métaheuristiques hybrides évolutionnaires, en particulier sur l'algorithme MOEA/D. Nous avons proposé l'algorithme HEMH qui utilise l'algorithme DM-GRASP pour construire une population initiale de solutions de bonne qualité dis
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20

Younes, Abdunnaser. "Adapting Evolutionary Approaches for Optimization in Dynamic Environments." Thesis, University of Waterloo, 2006. http://hdl.handle.net/10012/2835.

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Many important applications in the real world that can be modelled as combinatorial optimization problems are actually dynamic in nature. However, research on dynamic optimization focuses on continuous optimization problems, and rarely targets combinatorial problems. Moreover, dynamic combinatorial problems, when addressed, are typically tackled within an application context. <br /><br /> In this thesis, dynamic combinatorial problems are addressed collectively by adopting an evolutionary based algorithmic approach. On the plus side, their ability to manipulate several solutions at a
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21

Consoli, Sergio. "The development and application of metaheuristics for problems in graph theory : a computational study." Thesis, Brunel University, 2008. http://bura.brunel.ac.uk/handle/2438/3061.

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It is known that graph theoretic models have extensive application to real-life discrete optimization problems. Many of these models are NP-hard and, as a result, exact methods may be impractical for large scale problem instances. Consequently, there is a great interest in developing e±cient approximate methods that yield near-optimal solutions in acceptable computational times. A class of such methods, known as metaheuristics, have been proposed with success. This thesis considers some recently proposed NP-hard combinatorial optimization problems formulated on graphs. In particular, the min-
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22

Esseghir, Mohamed Amir. "Metaheuristics for the feature selection problem : adaptive, memetic and swarm approaches." Thesis, Artois, 2011. http://www.theses.fr/2011ARTO0206/document.

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Afin d’améliorer la qualité de prédiction des techniques de classification automatique et de fouilles de données, plusieurs modèles ont été proposés dans la littérature en vue d’extraire des connaissances à partir des données. Toutefois, avec l’expansion des systèmes d’information et des technologies associées, ces techniques d’apprentissage s’avèrent de moins en moins adaptées aux nouvelles tailles et dimensions des données. On s’intéresse dans cette étude aux problèmes de grande dimensionnalité et à l’amélioration du processus d’apprentissage des méthodes de classification à travers les tech
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Bullnheimer, Bernd, Richard F. Hartl, and Christine Strauß. "A new rank based version of the Ant System. A computational study." SFB Adaptive Information Systems and Modelling in Economics and Management Science, WU Vienna University of Economics and Business, 1997. http://epub.wu.ac.at/616/1/document.pdf.

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The ant system is a new meta-heuristic for hard combinatorial optimization problems. It is a population-based approach that uses exploitation of positive feedback as well as greedy search. It was first proposed for tackling the well known Traveling Salesman Problem (TSP), but has been also successfully applied to problems such as quadratic assignment, job-shop scheduling, vehicle routing and graph coloring.In this paper we introduce a new rank based version of the ant system and present results of a computational study, where we compare the ant system with simulated annealing and a genetic alg
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Gustavsson, Jonas. "Automated Performance Optimization of GSM/EDGE Network Parameters." Thesis, Linköping University, Linköping University, Communication Systems, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-52565.

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<p>The GSM network technology has been developed and improved during several years which have led to an increased complexity. The complexity results in more network parameters and together with different scenarios and situations they form a complex set of configurations. The definition of the network parameters is generally a manual process using static values during test execution. This practice can be costly, difficult and laborious and as the network complexity continues to increase, this problem will continue to grow.This thesis presents an implementation of an automated performance optimi
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Shahadat, Sharif. "Improving a Particle Swarm Optimization-based Clustering Method." ScholarWorks@UNO, 2017. http://scholarworks.uno.edu/td/2357.

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This thesis discusses clustering related works with emphasis on Particle Swarm Optimization (PSO) principles. Specifically, we review in detail the PSO clustering algorithm proposed by Van Der Merwe & Engelbrecht, the particle swarm clustering (PSC) algorithm proposed by Cohen & de Castro, Szabo’s modified PSC (mPSC), and Georgieva & Engelbrecht’s Cooperative-Multi-Population PSO (CMPSO). In this thesis, an improvement over Van Der Merwe & Engelbrecht’s PSO clustering has been proposed and tested for standard datasets. The improvements observed in those experiments vary from slight to moderate
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Guo, Yuhan. "Metaheuristics for solving large size long-term car pooling problem and an extension." Thesis, Artois, 2012. http://www.theses.fr/2012ARTO0206/document.

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La dispersion spatiale de l'habitat et des activités de ces dernières décennies a fortement contribué à un allongement des distances et des temps de trajets domicile-travail. Cela a pour conséquence un accroissement de l'utilisation des voitures particulières, notamment au sein et aux abords des grandes agglomérations. Afin de réduire les impacts dus à l'augmentation du trafic routier, des services de covoiturage, où des usagers ayant la même destination se regroupent en équipage pour se déplacer, ont été mis en place partout dans le monde. Nous présentons ici nos travaux sur le problème de co
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Birattari, Mauro. "The problem of tuning metaheuristics as seen from a machine learning perspective." Doctoral thesis, Universite Libre de Bruxelles, 2004. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/211128.

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<p>A metaheuristic is a generic algorithmic template that, once properly instantiated, can be used for finding high quality solutions of combinatorial optimization problems.<p>For obtaining a fully functioning algorithm, a metaheuristic needs to be configured: typically some modules need to be instantiated and some parameters need to be tuned. For the sake of precision, we use the expression <em>parametric tuning</em> for referring to the tuning of numerical parameters, either continuous or discrete but in any case ordinal. <p>On the other hand, we use the expression <em>structural tuning</em>
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Ghaffari, Majlej Vahid Verfasser], Thomas [Akademischer Betreuer] [Vietor, and Axel [Akademischer Betreuer] Schumacher. "Adaptive search approach in the multidisciplinary optimization of lightweight structures using hybrid metaheuristics / Vahid Ghaffari Majlej ; Thomas Vietor, Axel Schumacher." Braunschweig : Technische Universität Braunschweig, 2019. http://d-nb.info/1202919847/34.

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Ren, Jintong. "Optimization algorithms for graph layout problems." Thesis, Angers, 2020. https://tel.archives-ouvertes.fr/tel-03178385.

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Cette thèse considère deux problèmes de disposition des graphes : le problème de la bande passante cyclique (CBP) et le problème de l’agencement linéaire minimum (MinLA). Le CBP est une extension naturelle du problème de minimisation de la bande passante (BMP) et le MinLA est un problème de somme minimale. Ces problèmes sont largement appliqués dans la vie réelle. Puisqu’ils sont NP-difficile, il est difficile de les résoudre dans le cas général. Par conséquent, cette thèse est consacrée au développement d’algorithmes heuristiques efficaces pour faire face à ces problèmes. Plus précisément, no
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Zhou, Yi. "Optimization Algorithms for Clique Problems." Thesis, Angers, 2017. http://www.theses.fr/2017ANGE0013/document.

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Cette thèse présente des algorithmes de résolution de quatre problèmes de clique : clique de poids maximum (MVWCP), s-plex maximum (MsPlex), clique maximum équilibrée dans un graphe biparti (MBBP) et clique partition (CPP). Les trois premiers problèmes sont des généralisations ou relaxations du problème de la clique maximum, tandis que le dernier est un problème de couverture. Ces problèmes, ayant de nombreuses applications pratiques, sont NP-difficiles, rendant leur résolution ardue dans le cas général. Nous présentons ici des algorithmes de recherche locale, principalement basés sur la reche
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Guimarães, Marcos Antonio do Nascimento. "Plataforma integrada para o planejamento de sistemas de distribuição de energia eletrica utilizando metaheuristicas." [s.n.], 2009. http://repositorio.unicamp.br/jspui/handle/REPOSIP/260658.

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Orientadores: Carlos Alberto de Castro Junior, Ruben Augusto Romero Lazaro<br>Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Eletrica e de Computação<br>Made available in DSpace on 2018-08-14T21:34:08Z (GMT). No. of bitstreams: 1 Guimaraes_MarcosAntoniodoNascimento_D.pdf: 1387088 bytes, checksum: 36029ed51311645d24da08d56bb91409 (MD5) Previous issue date: 2009<br>Resumo: O objetivo desse trabalho de pesquisa é desenvolver ferramentas computacionais eficientes para a otimização da operação de sistemas de distribuição de energia elétrica. A principal contribuição
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Mohi, El Din Hatem. "Comparative Analysis of Ant Colony Optimization and Genetic Algorithm in Solving the Traveling Salesman Problem." Thesis, Blekinge Tekniska Högskola, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-21520.

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Metaheuristics is a term for optimization procedures/algorithms that can be applied to a wide range of problems. These problems for which metaheuristics are used usually fall in the NP-hard category, meaning that they cannot be solved in polynomial time. This means that as the input dataset gets larger the time to solve increases exponentially. One such problem is the traveling salesman problem (TSP) which is and has been widely used as a benchmark problem to test optimization algorithms. This study focused on two such algorithms called ant colony optimization (ACO) and genetic algorithm (GA)
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Rivera, Agudelo Juan Carlos. "Logistic optimization in disaster response operations." Thesis, Troyes, 2014. http://www.theses.fr/2014TROY0031/document.

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Les problèmes de tournées de véhicules cumulatives avec capacité (CCVRP) sont étudiés dans cette thèse, où la minimisation de la somme des temps d'arrivée reflète mieux les objectifs stratégiques de la logistique humanitaire.Dans le problème de multiples tournées d’un véhicule cumulatif avec capacité (mt-CCSVRP), un seul véhicule est disponible et il peut effectuer plusieurs voyages. Un algorithme du plus court chemin avec contrainte de ressources est proposé pour résoudre ce problème, dans lequel les tournées deviennent des nœuds et les sites sont des ressources. Le réseau est orienté et acyc
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Rodríguez, Molins Mario. "Optimization and Robustness in Planning and Scheduling Problems. Application to Container Terminals." Doctoral thesis, Universitat Politècnica de València, 2015. http://hdl.handle.net/10251/48545.

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Despite the continuous evolution in computers and information technology, real-world combinatorial optimization problems are NP-problems, in particular in the domain of planning and scheduling. Thus, although exact techniques from the Operations Research (OR) field, such as Linear Programming, could be applied to solve optimization problems, they are difficult to apply in real-world scenarios since they usually require too much computational time, i.e: an optimized solution is required at an affordable computational time. Furthermore, decision makers often face different and typically op
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Menasri, Riad. "Métaheuristiques pour la planification de trajectoire des bras manipulateurs redondants : application à l'assistance au geste chirurgical en craniotomie." Thesis, Paris Est, 2015. http://www.theses.fr/2015PESC1135/document.

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Le problème de planification de trajectoire des bras manipulateurs redondants est largement étudié dans la littérature. Sa résolution nécessite la prise en compte d'un certain nombre de contraintes, qui sont : • le calcul des différentes configurations par lesquelles le robot doit passer ; • l'obtention de courbes lisses (vitesses, accélérations, jerks).La prise en compte de ces deux contraintes dans la démarche de résolution peut se faire de deux manières différentes. La première consiste à supposer au préalable que les différentes courbes suivent des trajectoires lisses (utilisation de fonct
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Fabri, Lima Marcelus. "Internal logistics optimization in the automotive industry." Doctoral thesis, Universitat Pompeu Fabra, 2020. http://hdl.handle.net/10803/668492.

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This thesis focus on internal logistics flows (ILF), which is defined as the flows of materials inside the same business or the same plant. Precisely, this work approaches the ILF of SEAT, a company in the Volkswagen group. So, a set of Operational Research or Business Analytics based methods is presented. These methods contribute both to enrich the literature and provide useful techniques to the industry. Those methods refer to new mathematical formulations, Iterated Local Search metaheuristics, simulation models applications as well as a data set. So, the main purpose of this work is p
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Guerrero, Rueda William Javier. "Models and optimization methods for the inventory-location-routing problem." Thesis, Troyes, 2014. http://www.theses.fr/2014TROY0002/document.

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Cette thèse considère le problème consistant à intégrer les décisions de routage et stockage lors de la conception de la chaîne logistique. Le but est de sélectionner des dépôts parmi un ensemble de candidats pour desservir un ensemble de détaillants à l’aide d’une flotte de véhicules de capacité permettant visiter plus d’un détaillant par route. On cherche à déterminer la localisation de ces dépôts et les tournées des véhicules afin de maintenir leurs niveaux optimaux de stocks. La demande chez les détaillants est connue à l’avance. Des applications dans les domaines de la logistique humanitair
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Solano, Charris Elyn Lizeth. "Optimization methods for the robust vehicle routing problem." Thesis, Troyes, 2015. http://www.theses.fr/2015TROY0026/document.

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Cette thèse aborde le problème de tournées de véhicules (VRP) adressant des incertitudes via l'optimisation robuste, en donnant le VRP Robuste (RVRP). D'abord, les incertitudes sont intégrées sur les temps de trajet. Ensuite, une version bi-objectif du RVRP (bi-RVRP) est considérée en prenant en compte les incertitudes sur les temps de trajet et les demandes. Pour résoudre le RVRP et le bi-RVRP, différentes méthodes sont proposées pour déterminer des solutions robustes en minimisant le pire cas. Un Programme Linéaire à Variables Mixtes Entières (MILP), six heuristiques constructives, un algori
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Demirtas, Kerem. "An Interactive Preference Based Multiobjective Evolutionary Algorithm For The Clustering Problem." Master's thesis, METU, 2011. http://etd.lib.metu.edu.tr/upload/12613290/index.pdf.

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We propose an interactive preference-based evolutionary algorithm for the clustering problem. The problem is highly combinatorial and referred to as NP-Hard in the literature. The goal of the problem is putting similar items in the same cluster and dissimilar items into different clusters according to a certain similarity measure, while maintaining some internal objectives such as compactness, connectivity or spatial separation. However, using one of these objectives is often not sufficient to detect different underlying structures in different data sets with clusters having arbitrary shapes a
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Bianchi, Leonora. "Ant colony optimization and local search for the probabilistic traveling salesman problem: a case study in stochastic combinatorial optimization." Doctoral thesis, Universite Libre de Bruxelles, 2006. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/210877.

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In this thesis we focus on Stochastic combinatorial Optimization Problems (SCOPs), a wide class of combinatorial optimization problems under uncertainty, where part of the information about the problem data is unknown at the planning stage, but some knowledge about its probability distribution is assumed.<p><p>Optimization problems under uncertainty are complex and difficult, and often classical algorithmic approaches based on mathematical and dynamic programming are able to solve only very small problem instances. For this reason, in recent years metaheuristic algorithms such as Ant Colony Op
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41

Tangpattanakul, Panwadee. "Multi-objective optimization of earth observing satellite missions." Thesis, Toulouse, INSA, 2013. http://www.theses.fr/2013ISAT0023/document.

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Cette thèse considère le problème de sélection et d’ordonnancement des prises de vue d’un satellite agile d’observation de la Terre. La mission d’un satellite d’observation est d’obtenir des photographies de la surface de la Terre afin de satisfaire des requêtes d’utilisateurs. Les demandes, émanant de différents utilisateurs, doivent faire l’objet d’un traitement avant transmission d’un ordre vers le satellite, correspondant à une séquence d’acquisitions sélectionnées. Cette séquence doit optimiser deux objectifs sous contraintes d’exploitation. Le premier objectif est de maximiser le profit
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Correa, Leonardo de Lima. "Uma proposta de algoritmo memético baseado em conhecimento para o problema de predição de estruturas 3-D de proteínas." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2017. http://hdl.handle.net/10183/156640.

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Algoritmos meméticos são meta-heurísticas evolutivas voltadas intrinsecamente à exploração e incorporação de conhecimentos relacionados ao problema em estudo. Nesta dissertação, foi proposto um algoritmo memético multi populacional baseado em conhecimento para lidar com o problema de predição de estruturas tridimensionais de proteínas voltado à modelagem de estruturas livres de similaridades conformacionais com estruturas de proteínas determinadas experimentalmente. O algoritmo em questão, foi estruturado em duas etapas principais de processamento: (i) amostragem e inicialização de soluções; e
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Kesler, René. "Optimalizace metaheuristikami v Pythonu pomocí knihovny DEAP." Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2019. http://www.nusl.cz/ntk/nusl-401489.

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{This thesis deals with optimization by means of metaheuristics, which are used for complicated engineering problems that cannot be solved by classical methods of mathematical programming. At the beginning, choosed metaheuristics are described: simulated annealing, particle swarm optimization and genetic algorithm; and then they are compared with use of test functions. These algorithms are implemented in Python programming language with use of package called DEAP, which is also described in this thesis. Algorithms are then applied for optimization of design parameters of the heat storage unit.
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Álvarez, Serrano José Fernando. "Optimization algorithms for maritime terminal and fleet management." Doctoral thesis, Universitat Pompeu Fabra, 2008. http://hdl.handle.net/10803/7366.

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El plan de carga del buque debe adherirse a las instrucciones de estiba del operador del buque. Estas instrucciones especifican las características generales de cada contenedor que habrá de ccargarse. El plan de carga también debe agilizar las operaciones de transporte en la explanada de la terminal. Presentamos dos algoritmos para generar el plan de carga. El primero utiliza el método de descomposición Lagrangeana. El segundo utiliza la metaheurística tabú. <br/><br/>Las companías navieras se enfrentan a un problema extremadamente complejo cuando intentan determinar la composición y ruteo ópt
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Copado, Méndez Pedro Jesús. "Contribution to the development of efficient algorithms for solving complex single-objective and multi-objective optimization models." Doctoral thesis, Universitat Rovira i Virgili, 2014. http://hdl.handle.net/10803/284089.

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L’optimització en enginyeria de processos és un àrea molt estesa que ha anat evolucionant al llarg del temps i ha passat de ser una metodologia d'interès purament acadèmic a una tecnologia que té, i que contínua tenint, gran impacte en la indústria. En aquesta tesi ens hem centrat en el desenvolupament mètodes basats en dues eines típiques d'optimització: programació matemàtica i metaheurístiques. Els objectius d'aquesta tesi són: el primer és desenvolupar una metaheuristica híbrida per a l'optimització del disseny de cadenes de subministrament, d'un sol objectiu (cost o benefici), on tots els
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Santos, Raphael Gomes. "Metaheurísticas para geração de alvos para robôs exploratórios autônomos." Universidade Federal do Maranhão, 2016. http://tedebc.ufma.br:8080/jspui/handle/tede/1760.

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Submitted by Rosivalda Pereira (mrs.pereira@ufma.br) on 2017-07-25T17:21:34Z No. of bitstreams: 1 RaphaelSantos.pdf: 3718930 bytes, checksum: df335fd5562e8156000972c282fe9724 (MD5)<br>Made available in DSpace on 2017-07-25T17:21:34Z (GMT). No. of bitstreams: 1 RaphaelSantos.pdf: 3718930 bytes, checksum: df335fd5562e8156000972c282fe9724 (MD5) Previous issue date: 2016-08-17<br>Autonomous exploration, in robotics, can be defined as the act of moving into an unknown environment, at priori, while building up a map of the environment. A great deal of literature describes several problems that are
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Blum, Christian. "Theoretical and practical aspects of ant colony optimization." Doctoral thesis, Universite Libre de Bruxelles, 2004. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/211187.

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Combinatorial optimization problems are of high academical as well as practical importance. Many instances of relevant combinatorial optimization problems are, due to their dimensions, intractable for complete methods such as branch and bound. Therefore, approximate algorithms such as metaheuristics received much attention in the past 20 years. Examples of metaheuristics are simulated annealing, tabu search, and evolutionary computation. One of the most recent metaheuristics is ant colony optimization (ACO), which was developed by Prof. M. Dorigo (who is the supervisor of this thesis) and coll
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Jin, Yan. "Hybrid metaheuristic algorithms for sum coloring and bandwidth coloring." Thesis, Angers, 2015. http://www.theses.fr/2015ANGE0062/document.

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Le problème de somme coloration minimum (MSCP) et le problème de coloration de bande passante (BCP) sont deux généralisations importantes du problème de coloration des sommets classique avec de nombreuses applications dans divers domaines, y compris la conception de circuits imprimés, la planication, l’allocation de ressource, l’affectation de fréquence dans les réseaux mobiles, etc. Les problèmes MSCP et BCP étant NP-difficiles, les heuristiques et métaheuristiques sont souvent utilisées en pratique pour obtenir des solutions de bonne qualité en un temps de calcul acceptable. Cette thèse est
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Garcia, Vinicius Jacques. "Metaheuristicas multiobjetivo para o problema de restauração do serviço em redes de distribuição de energia eletrica." [s.n.], 2005. http://repositorio.unicamp.br/jspui/handle/REPOSIP/260561.

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Orientador: Paulo Morelato França<br>Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Eletrica e de Computação<br>Made available in DSpace on 2018-08-05T20:11:19Z (GMT). No. of bitstreams: 1 Garcia_ViniciusJacques_D.pdf: 1756755 bytes, checksum: e845cc09a5de807da958e9792684e777 (MD5) Previous issue date: 2005<br>Resumo: Depois da regulamentação do setor elétrico brasileiro, a qualidade no fornecimento de energia ganhou maior importância por parte das concessionárias. Neste contexto, o problema de restauração do serviço tem particular relevância pela relação com a
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Lu, Zhi. "Optimization approaches for minimum conductance graph partitioning." Thesis, Angers, 2020. http://www.theses.fr/2020ANGE0013.

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Le problème de partitionnement de graphe de conductance minimale (MCGPP) est un problème d’optimisation combinatoire NP-difficile avec de nombreuses applications pratiques dans divers domaines tels que la détection communautaire, la bioinformatique et la vision par ordinateur. Etant donnée sa complexité intrinsèque, des approches heuristiques et métaheuristiques constituent un moyen convenable pour résoudre des instances de grande taille. Cette thèse est consacrée au développement d’algorithmes métaheuristiques performants pour le MC-GPP. Plus précisément, nous proposons un algorithme «Stagnat
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