Nature-Inspired Algorithms and Applied Optimization: 744 (Studies in Computational Intelligence, 744) - Softcover

Softcover

ISBN 10: 3319884654 ISBN 13: 9783319884653

Publisher: Springer, 2018

Synopsis

Reviews the state-of-the-art developments in nature-inspired algorithms and optimization

Presents a number of theories (no-free-lunch theorems and convergence analysis) and insights into nature-inspired algorithms

Introduces algorithms with an emphasis on applied optimization in real-world applications

About 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.

Edition details

• Publisher: Springer
• Publication date: 2018
• Language: English
• ISBN 10: 3319884654
• ISBN 13: 9783319884653
• Binding: Paperback
• Number of pages: 341
• Editor: Yang Xin-She