Hybrid Metaheuristics, Maria J. Blesa; Christian Blum; Stefan Vo?

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: Maria J. Blesa; Christian Blum; Angelo Cangelosi;
Название: Hybrid Metaheuristics
ISBN: 3319396358 ISBN-13(EAN): 9783319396354
Издательство: Springer
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Описание: This book constitutes the refereed proceedings of the 10th International Workshop on Hybrid Metaheuristics, HM 2016, held in Plymouth, UK, in June 2016. The 15 revised full papers presented were carefully reviewed and selected from 43 submissions.

Автор: Christian Blum; Carlos Cotta; Antonio Jos? Fern?nd
Название: Hybrid Metaheuristics
ISBN: 3540884386 ISBN-13(EAN): 9783540884385
Издательство: Springer
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Описание: Constitutes the refereed proceedings of the 5th International Workshop on Hybrid Metaheuristics, HM 2008, held in Dortmund, Germany, in October 2008. This book discusses specific aspects of combinations of metaheuristics and other solving techniques for tackling particular relevant constrained optimization problems, such as fiber optic networks.

Автор: Christian Blum; Andrea Roli; Michael Sampels
Название: Hybrid Metaheuristics
ISBN: 3642096972 ISBN-13(EAN): 9783642096976
Издательство: Springer
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Описание: Optimization problems are of great importance across a broad range of fields. This book is intended both to provide an overview of hybrid metaheuristics to novices of the field, and to provide researchers from the field with a collection of some of the most interesting recent developments.

Автор: Jorge Magalh?es-Mendes; David Greiner
Название: Evolutionary Algorithms and Metaheuristics in Civil Engineering and Construction Management
ISBN: 331920405X ISBN-13(EAN): 9783319204055
Издательство: Springer
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Описание: This book focuses on civil and structural engineering and construction management applications. The contributions constitute modified, extended and improved versions of research presented at the minisymposium organized by the editors at the ECCOMAS conference on this topic in Barcelona 2014.

Автор: Patrick Siarry
Название: Metaheuristics
ISBN: 3319454013 ISBN-13(EAN): 9783319454016
Издательство: Springer
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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: Christian Blum; Luca Gaspero; Andrea Roli; Michael
Название: Hybrid Metaheuristics
ISBN: 3642049176 ISBN-13(EAN): 9783642049170
Издательство: Springer
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Автор: Christian Blum; G?nther R. Raidl
Название: Hybrid Metaheuristics
ISBN: 3319308823 ISBN-13(EAN): 9783319308821
Издательство: Springer
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Цена: 10760.00 р.
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Автор: El-Ghazali Talbi
Название: Metaheuristics for Bi-level Optimization
ISBN: 3642378374 ISBN-13(EAN): 9783642378379
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Описание: This book provides a complete background on metaheuristics to solve complex bi-level optimization problems in a diverse range of application domains. It includes numerous examples that demonstrate how metaheuristics are applied in the real-world.

Автор: Mauro Birattari
Название: Tuning Metaheuristics
ISBN: 3642101496 ISBN-13(EAN): 9783642101496
Издательство: Springer
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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: Amir Nakib; El-Ghazali Talbi
Название: Metaheuristics for Medicine and Biology
ISBN: 3662544261 ISBN-13(EAN): 9783662544266
Издательство: Springer
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Описание: This book highlights recent research on metaheuristics for biomedical engineering, addressing both theoretical and applications aspects.