Metaheuristics and Optimization in Civil Engineering, Xin-She Yang; Gebrail Bekda?; Sinan Melih Nigdeli

Автор: Gendreau
Название: Handbook of Metaheuristics
ISBN: 1441916636 ISBN-13(EAN): 9781441916631
Издательство: Springer
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Описание: Metaheuristics have grown into one of the most prominent areas of operations research. This update of a trailblazing volume examines the latest developments in the field.

Автор: Patrick Siarry; Zbigniew Michalewicz
Название: Advances in Metaheuristics for Hard Optimization
ISBN: 3642092063 ISBN-13(EAN): 9783642092060
Издательство: Springer
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Цена: 23058.00 р.
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Описание: The editors, both leading experts in this field, have assembled a team of researchers to contribute 21 chapters organized into parts on simulated annealing, tabu search, ant colony algorithms, general purpose studies of evolutionary algorithms, applications of evolutionary algorithms, and metaheuristics.

Автор: Mauro Birattari
Название: Tuning Metaheuristics
ISBN: 3642101496 ISBN-13(EAN): 9783642101496
Издательство: Springer
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Цена: 20962.00 р.
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Описание: Metaheuristics are a relatively new but already established approachto c- binatorial optimization. A metaheuristic is a generic algorithmic template that can be used for ?nding high quality solutions of hard combinatorial - timization problems. To arrive at a functioning algorithm, a metaheuristic needs to be con?gured: typically some modules need to be instantiated and someparametersneedto betuned.Icallthese twoproblems"structural"and "parametric" tuning, respectively. More generally, I refer to the combination of the two problems as "tuning." Tuning is crucial to metaheuristic optimization both in academic research andforpracticalapplications.Nevertheless, relativelylittle researchhasbeen devoted to the issue. This book shows that the problem of tuning a me- heuristic can be described and solved as a machine learning problem. Using the machine learning perspective, it is possible to give a formal de?nitionofthetuningproblemandtodevelopagenericalgorithmfortuning metaheuristics.Moreover, fromthemachinelearningperspectiveitispossible tohighlightsome?awsinthecurrentresearchmethodologyandtostatesome guidelines for future empirical analysis in metaheuristics research. This book is based on my doctoral dissertation and contains results I have obtained starting from 2001 while working within the Metaheuristics Net- 1 work. During these years I have been a?liated with two research groups: INTELLEKTIK, Technische Universit t Darmstadt, Darmstadt, Germany and IRIDIA, Universit Libre de Bruxelles, Brussels, Belgium. I am the- fore grateful to the research directors of these two groups: Prof. Wolfgang Bibel, Dr. Thomas St tzle, Prof. Philippe Smets, Prof. Hugues Bersini, and Prof. Marco Dorigo.

Автор: Patrick Siarry
Название: Metaheuristics
ISBN: 3319454013 ISBN-13(EAN): 9783319454016
Издательство: Springer
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Цена: 19564.00 р.
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Описание: Introduction.- Simulated Annealing.- Tabu Search.- Search in Variable Neighborhoods.- The GRASP Search Algorithm.- Evolutionary Algorithms.- Artificial Ants.- Particle Swarms.- Other Metaheuristics.- Other Social Insect Algorithms.- Extending Evolutionary Algorithms for Multiobjective Optimization.- Extending Evolutionary Algorithms for Optimization Under Constraints.- Modeling and Comparison Methods.- Hybrid Metaheuristics for Optimizing Logistics.- Metaheuristics for Vehicle Routing Problems.- Applications in Air Traffic Management.

Автор: Fasano
Название: Modeling and Optimization in Space Engineering
ISBN: 1461444683 ISBN-13(EAN): 9781461444688
Издательство: Springer
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Цена: 18167.00 р.
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Описание: This volume presents a selection of studies that address a substantial list of key challenges arising in space engineering. The contributing authors are well-recognized researchers and practitioners in space engineering and in applied optimization. Novel points of view such as computational global optimization, multidisciplinary design optimization and optimal control theory are emphasized and both mathematical modeling and algorithmic aspects are discussed. Classic space application problems, such as trajectory optimization, are presented together with systems engineering and logistics aspects, such as propulsion system design and cargo accommodation. A particular attention is paid to the scenarios expected for future interplanetary explorations.  Modeling and Optimization in Space Engineering will benefit researchers and practitioners in the field of space engineering, as well as aerospace graduate and post-graduate students willing to broaden their academic knowledge, by studying real-world applications and challenging problems that they will be likely to tackle in their future professional activities.