Nature-Inspired Algorithms and Applied Optimization / Studies in Computational Intelligence Bd.744 (PDF)
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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.
- 2017, 1st ed. 2018, 330 Seiten, Englisch
- Herausgegeben: Xin-She Yang
- Verlag: Springer-Verlag GmbH
- ISBN-10: 3319676695
- ISBN-13: 9783319676692
- Erscheinungsdatum: 08.10.2017
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- Grösse: 6.38 MB
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“The book is rich with relevant illustrations and real-life/practical problems, where the various topics are or can be applied. The book is a comprehensive and in-depth study, and the style of presentation is remarkable. These aspects make reading this book an absolute delight.” (Sudev Naduvath, Computing Reviews, August, 2018)
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