Advances in Metaheuristics for Hard Optimization (Natural Computing Series)

Zbigniew Michalewicz

ISBN 10: 3540729593 / ISBN 13: 9783540729594

Published by Springer, 2007

About this Item

479 pp., illustrations, bibliography, index. Many advances have been made recently in metaheuristic methods, from theory to applications. 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 various metaheuristics. The book gathers contributions related to the following topics: theoretical developments in metaheuristics; adaptation of discrete metaheuristics to continuous optimization; performance comparisons of metaheuristics; cooperative methods combining different approaches; parallel and distributed metaheuristics for multiobjective optimization; software implementations; and real-world applications. This book is suitable for practitioners, researchers and graduate students in disciplines such as optimization, heuristics, operations research, and natural computing.

Seller Inventory # 3540729593EVANS031516

Bibliographic Details

• Title: Advances in Metaheuristics for Hard Optimization (Natural Computing Series)
• Publisher: Springer
• Publication Date: 2007
• Language: English
• ISBN 10: 3540729593
• ISBN 13: 9783540729594
• Binding: Hardcover
• Condition: Fine

About this title

Synopsis

Many advances have been made recently in metaheuristic methods, from theory to applications. 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 various metaheuristics.

The book gathers contributions related to the following topics: theoretical developments in metaheuristics; adaptation of discrete metaheuristics to continuous optimization; performance comparisons of metaheuristics; cooperative methods combining different approaches; parallel and distributed metaheuristics for multiobjective optimization; software implementations; and real-world applications.

This book is suitable for practitioners, researchers and graduate students in disciplines such as optimization, heuristics, operations research, and natural computing.