Metaheuristics for Bi-level Optimization, El-Ghazali Talbi

Автор: Gendreau
Название: Handbook of Metaheuristics
ISBN: 1441916636 ISBN-13(EAN): 9781441916631
Издательство: Springer
Рейтинг:
Цена: 33401.00 р.
Наличие на складе: Поставка под заказ.

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: 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
Рейтинг:
Цена: 15672.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

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
Рейтинг:
Цена: 19564.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

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: Mauro Birattari
Название: Tuning Metaheuristics
ISBN: 3642101496 ISBN-13(EAN): 9783642101496
Издательство: Springer
Рейтинг:
Цена: 20962.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

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.