Description: Nature-inspired Optimization Algorithms, Paperback by Yang, Xin-She, ISBN 0128219866, ISBN-13 9780128219867, Brand New, Free shipping in the US Nature-Inspired Optimization Algorithms, Second Edition provides an introduction to all major nature-inspired algorithms for optimization. Th's unified approach, balancing algorithm introduction, theoretical background and practical implementation, complements extensive literature with case studies to illustrate how these algorithms work. Topics include particle swarm optimization, ant and bee algorithms, simulated annealing, cuckoo search, firefly algorithm, bat algorithm, flower algorithm, harmony search, algorithm analysis, constraint handling, hybrid methods, parameter tuning and control, and multi-objective optimization. This book can serve as an introductory book for graduates, for lecturers in computer science, engineering and natural sciences, and as a source of inspiration for new applications. Discusses and summarizes the latest developments in nature-inspired algorithms with comprehensive, timely literature Provides a theoretical understanding and practical implementation hints Presents a step-by-step introduction to each algorithm Includes four new chapters covering mathematical foundations, techniques for solving discrete and combination optimization problems, data mining techniques and their links to optimization algorithms, and the latest deep learning techniques, background and various applications
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Book Title: Nature-inspired Optimization Algorithms
Number of Pages: 332 Pages
Language: English
Publication Name: Nature-Inspired Optimization Algorithms
Publisher: Elsevier Science & Technology
Publication Year: 2020
Subject: Biotechnology, General, Biomedical
Type: Textbook
Subject Area: Mathematics, Technology & Engineering, Science
Item Length: 9.2 in
Author: Xin-She Yang
Item Width: 7.5 in
Format: Trade Paperback
