Metaheuristic Computation: A Performance Perspective
Language: English
Published by Springer International Publishing, 2020
Series: Book 162 of 188 - Intelligent Systems Reference Library
- Hardcover
- New
Seller: moluna, Greven, Germanymoluna
AbeBooks seller since July 9, 2020
Condition: New
£ 81.50
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Add to basketItem description from seller
Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Presents the performance comparison of various metaheuristic techniques when they face complex optimization problemsParticularly focuses on recently developed algorithmsThis book is designed so that each chapter can be read independently.
Seller Inventory # 448685116
- Title
- Metaheuristic Computation: A Performance Perspective
- Author
- Erik Cuevas|Primitivo Diaz|Octavio Camarena
- Publisher
- Springer International Publishing
- Publication year
- 2020
- Condition
- New
- Binding
- Hardcover
- Language
- English
- ISBN 10
- 3030580997
- ISBN 13
- 9783030580995
- Series
- Book 162 of 188: Intelligent Systems Reference Library
- Seller catalogs
- Mathematik/Naturwissenschaften/Technik/Medizin
This book is primarily intended for undergraduate and postgraduate students of Science, Electrical Engineering, or Computational Mathematics. Metaheuristic search methods are so numerous and varied in terms of design and potential applications; however, for such an abundant family of optimization techniques, there seems to be a question which needs to be answered: Which part of the design in a metaheuristic algorithm contributes more to its better performance? Several works that compare the performance among metaheuristic approaches have been reported in the literature. Nevertheless, they suffer from one of the following limitations: (A)Their conclusions are based on the performance of popular evolutionary approaches over a set of synthetic functions with exact solutions and well-known behaviors, without considering the application context or including recent developments. (B) Their conclusions consider only the comparison of their final results which cannot evaluate the nature of a good or bad balance between exploration and exploitation. The objective of this book is to compare the performance of various metaheuristic techniques when they are faced with complex optimization problems extracted from different engineering domains. The material has been compiled from a teaching perspective.
"Synopsis" may belong to another edition of this title.
From the Back Cover
This book is primarily intended for undergraduate and postgraduate students of Science, Electrical Engineering, or Computational Mathematics. Metaheuristic search methods are so numerous and varied in terms of design and potential applications; however, for such an abundant family of optimization techniques, there seems to be a question which needs to be answered: Which part of the design in a metaheuristic algorithm contributes more to its better performance? Several works that compare the performance among metaheuristic approaches have been reported in the literature. Nevertheless, they suffer from one of the following limitations: (A)Their conclusions are based on the performance of popular evolutionary approaches over a set of synthetic functions with exact solutions and well-known behaviors, without considering the application context or including recent developments. (B) Their conclusions consider only the comparison of their final results which cannot evaluate the nature of a good or bad balance between exploration and exploitation. The objective of this book is to compare the performance of various metaheuristic techniques when they are faced with complex optimization problems extracted from different engineering domains. The material has been compiled from a teaching perspective.
"About the title" may belong to another edition of this title.
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