Nature-Inspired Algorithms and Applied Optimization Hardback - 2017
by Xin-She Yang (Editor)
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From the publisher
From the rear 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.
Details
- Title Nature-Inspired Algorithms and Applied Optimization
- Author Xin-She Yang (Editor)
- Binding Hardback
- Pages 330
- Volumes 1
- Language ENG
- Publisher Springer
- Publication date 2017-10-18
- Illustrated Yes
- Features Illustrated
- ISBN 9783319676685 / 3319676687
- Weight 1.45 lbs (0.66 kg)
- Dimensions 9.21 x 6.14 x 0.81 in (23.39 x 15.60 x 2.06 cm)
- Category Computers - General Information
- Dewey Decimal Code 006.3
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