Self-organizing Migrating Algorithm : Theory and Application
Language: English
Published by Springer, 2016
Series: Book 146 of 538 - Studies in Computational Intelligence
- Hardcover
- New
Seller: GreatBookPrices, Columbia, MD, U.S.A.GreatBookPrices
AbeBooks seller since April 6, 2009
Condition: New
US$ 129.35
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Add to basketSeller Inventory # 25081697-n
- Title
- Self-organizing Migrating Algorithm : Theory and Application
- Author
- Davendra, Donald (EDT); Zelinka, Ivan (EDT)
- Publisher
- Springer
- Publication year
- 2016
- Condition
- New
- Binding
- Hardcover
- Language
- English
- ISBN 10
- 3319281593
- ISBN 13
- 9783319281599
- Series
- Book 146 of 538: Studies in Computational Intelligence
This book brings together the current state of-the-art research in Self Organizing Migrating Algorithm (SOMA) as a novel population-based evolutionary algorithm, modeled on the predator-prey relationship, by its leading practitioners.
As the first ever book on SOMA, this book is geared towards graduate students, academics and researchers, who are looking for a good optimization algorithm for their applications. This book presents the methodology of SOMA, covering both the real and discrete domains, and its various implementations in different research areas. The easy-to-follow and implement methodology used in the book will make it easier for a reader to implement, modify and utilize SOMA.
"Synopsis" may belong to another edition of this title.
From the Back Cover
This book brings together the current state of-the-art research in Self Organizing Migrating Algorithm (SOMA) as a novel population-based evolutionary algorithm, modeled on the predator-prey relationship, by its leading practitioners.
As the first ever book on SOMA, this book is geared towards graduate students, academics and researchers, who are looking for a good optimization algorithm for their applications. This book presents the methodology of SOMA, covering both the real and discrete domains, and its various implementations in different research areas. The easy-to-follow and implement methodology used in the book will make it easier for a reader to implement, modify and utilize SOMA.
"About the title" may belong to another edition of this title.
GreatBookPrices
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