Description: Nature-Inspired Algorithms and Applied Optimization Please note: this item is printed on demand and will take extra time before it can be dispatched to you (up to 20 working days). Author(s): Xin-She Yang Format: Hardback Publisher: Springer International Publishing AG, Switzerland Imprint: Springer International Publishing AG ISBN-13: 9783319676685, 978-3319676685 Synopsis 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.
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End Time: 2024-11-23T09:13:49.000Z
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Book Title: Nature-Inspired Algorithms and Applied Optimization
Item Height: 235 mm
Item Width: 155 mm
Series: Studies in Computational Intelligence
Author: Xin-She Yang
Publication Name: Nature-Inspired Algorithms and Applied Optimization
Format: Hardcover
Language: English
Publisher: Springer International Publishing A&G
Subject: Computer Science, Mathematics
Publication Year: 2017
Type: Textbook
Item Weight: 6387 g
Number of Pages: 330 Pages