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Evolutionary Algorithms and Metaheuristics in Civil Engineering and Construction Management, Jorge Magalh?es-Mendes; David Greiner


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Автор: Jorge Magalh?es-Mendes; David Greiner
Название:  Evolutionary Algorithms and Metaheuristics in Civil Engineering and Construction Management
ISBN: 9783319373218
Издательство: Springer
Классификация:




ISBN-10: 3319373218
Обложка/Формат: Paperback
Страницы: 127
Вес: 0.20 кг.
Дата издания: 17.10.2016
Серия: Computational Methods in Applied Sciences
Язык: English
Размер: 234 x 156 x 8
Основная тема: Engineering
Ссылка на Издательство: Link
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Поставляется из: Германии
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.


Handbook of Metaheuristics

Автор: Gendreau
Название: Handbook of Metaheuristics
ISBN: 1441916636 ISBN-13(EAN): 9781441916631
Издательство: Springer
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Цена: 33401.00 р.
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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.

Tuning 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.

Evolutionary Algorithms and Metaheuristics in Civil Engineering and Construction Management

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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Цена: 15672.00 р.
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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.

Evolutionary Hierarchical Multi-Criteria Metaheuristics for Scheduling in Large-Scale Grid Systems

Автор: Joanna Ko?odziej
Название: Evolutionary Hierarchical Multi-Criteria Metaheuristics for Scheduling in Large-Scale Grid Systems
ISBN: 3642436617 ISBN-13(EAN): 9783642436611
Издательство: Springer
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Цена: 15672.00 р.
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Описание: This book explores hot topics in the design, administration and management of dynamic grid environments. The emphasis is on preferences and autonomous decisions of system users, secure access to processed data and services and the use of green technologies.

Artificial Intelligence, Evolutionary Computing and Metaheuristics

Автор: Xin-She Yang
Название: Artificial Intelligence, Evolutionary Computing and Metaheuristics
ISBN: 3642437036 ISBN-13(EAN): 9783642437038
Издательство: Springer
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Цена: 36197.00 р.
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Описание: Joining in the centenary celebration of the life and work of Alan Turing, this book reviews the latest developments in artificial intelligence, evolutionary computation and metaheuristics, all of which can be traced back to Turing`s pioneer work.

Applications of Metaheuristics in Process Engineering

Автор: Jayaraman Valadi; Patrick Siarry
Название: Applications of Metaheuristics in Process Engineering
ISBN: 3319357042 ISBN-13(EAN): 9783319357041
Издательство: Springer
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Цена: 13275.00 р.
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Описание: Metaheuristics exhibit desirable properties like simplicity, easy parallelizability and ready applicability to different types of optimization problems such as real parameter optimization, combinatorial optimization and mixed integer optimization.

Metaheuristics for Bi-level Optimization

Автор: El-Ghazali Talbi
Название: Metaheuristics for Bi-level Optimization
ISBN: 3642378374 ISBN-13(EAN): 9783642378379
Издательство: Springer
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Цена: 23508.00 р.
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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.

Metaheuristics

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.


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