Nature-inspired Algorithms and Applied Optimization
Language: English
Published by Springer, 2017
Series: Book 248 of 538 - Studies in Computational Intelligence
- Hardcover
- New

Seller: GreatBookPrices, Columbia, MD, U.S.A.GreatBookPrices
AbeBooks seller since April 6, 2009
Condition: New
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- Title
- Nature-inspired Algorithms and Applied Optimization
- Author
- Yang, Xin-she (EDT)
- Publisher
- Springer
- Publication year
- 2017
- Condition
- New
- Binding
- Hardcover
- Language
- English
- ISBN 10
- 3319676687
- ISBN 13
- 9783319676685
- Series
- Book 248 of 538: Studies in Computational Intelligence
This book reviews the state-of-the-art developments in nature-inspired algorithms and their applications in various disciplines, ranging from feature selection and engineering design optimization to scheduling and vehicle routing. It introduces each algorithm and its implementation with case studies as well as extensive literature reviews, and also includes self-contained chapters featuring theoretical analyses, such as convergence analysis and no-free-lunch theorems so as to provide insights into the current nature-inspired optimization algorithms. Topics include ant colony optimization, the bat algorithm, B-spline curve fitting, cuckoo search, feature selection, economic load dispatch, the firefly algorithm, the flower pollination algorithm, knapsack problem, octonian and quaternion representations, particle swarm optimization, scheduling, wireless networks, vehicle routing with time windows, and maximally different alternatives. This timely book serves as a practical guide and reference resource for students, researchers and professionals.
"Synopsis" may belong to another edition of this title.
From the Back Cover
This book reviews the state-of-the-art developments in nature-inspired algorithms and their applications in various disciplines, ranging from feature selection and engineering design optimization to scheduling and vehicle routing. It introduces each algorithm and its implementation with case studies as well as extensive literature reviews, and also includes self-contained chapters featuring theoretical analyses, such as convergence analysis and no-free-lunch theorems so as to provide insights into the current nature-inspired optimization algorithms. Topics include ant colony optimization, the bat algorithm, B-spline curve fitting, cuckoo search, feature selection, economic load dispatch, the firefly algorithm, the flower pollination algorithm, knapsack problem, octonian and quaternion representations, particle swarm optimization, scheduling, wireless networks, vehicle routing with time windows, and maximally different alternatives. This timely book serves as a practical guide and reference resource for students, researchers and professionals.
"About the title" may belong to another edition of this title.
GreatBookPrices
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