Authors:
Offers a comprehensive and state-of-the-art introduction to nature-inspired metaheuristics
Includes detailed, implementable algorithmic flowcharts for the most popular algorithms
Discusses over 100 different types of nature-inspired search and optimization methods
Will allow students to discover the newest trends in metaheuristics and optimization
Includes supplementary material: sn.pub/extras
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Table of contents (23 chapters)
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Front Matter
About this book
An introductory chapter covers the necessary biological and mathematical backgrounds for understanding the main material. Subsequent chapters then explore almost all of the major metaheuristics for search and optimization created based on natural phenomena, including simulated annealing, recurrent neural networks, genetic algorithms and genetic programming, differential evolution, memetic algorithms, particle swarm optimization, artificial immune systems, ant colony optimization, tabu search and scatter search, bee and bacteria foraging algorithms, harmony search, biomolecular computing, quantum computing, and many others. General topics on dynamic, multimodal, constrained, and multiobjective optimizations are also described. Each chapter includes detailed flowcharts that illustrate specific algorithms and exercises that reinforce important topics. Introduced in the appendix are some benchmarks for the evaluation of metaheuristics.
Search and Optimization by Metaheuristics is intended primarily as a textbook for graduate and advanced undergraduate students specializing in engineering and computer science. It will also serve as a valuable resource for scientists and researchers working in these areas, as well as those who are interested in search and optimization methods.
Reviews
Authors and Affiliations
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Xonlink Inc, Ningbo, Zhejiang, China, and Department of Electrical and Computer Engineering, Concordia University, Montreal, Canada
Ke-Lin Du
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Department of Electrical and Computer Engineering, Concordia University, Montreal, Canada
M. N. S. Swamy
About the authors
M.N.S. Swamy, PhD, is Research Professor and Tier I Concordia Research Chair in the Department of Electrical and Computer Engineering at Concordia University, Montreal, Quebec, Canada.
Bibliographic Information
Book Title: Search and Optimization by Metaheuristics
Book Subtitle: Techniques and Algorithms Inspired by Nature
Authors: Ke-Lin Du, M. N. S. Swamy
DOI: https://doi.org/10.1007/978-3-319-41192-7
Publisher: Birkhäuser Cham
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer International Publishing Switzerland 2016
Hardcover ISBN: 978-3-319-41191-0Published: 02 August 2016
Softcover ISBN: 978-3-319-82290-7Published: 31 May 2018
eBook ISBN: 978-3-319-41192-7Published: 20 July 2016
Edition Number: 1
Number of Pages: XXI, 434
Number of Illustrations: 28 b/w illustrations, 40 illustrations in colour
Topics: Computational Science and Engineering, Algorithms, Optimization, Simulation and Modeling, Computational Intelligence