Nature-Inspired Metaheuristic Algorithms for Engineering Optimization Applications (Hardcover, 1st ed. 2021)

This book engages in an ongoing topic, such as the implementation of nature-inspired metaheuristic algorithms, with a main concentration on optimization problems in different fields of engineering optimization applications. The chapters of the book provide concise overviews of various nature-inspired metaheuristic algorithms, defining their profits in obtaining the optimal solutions of tiresome engineering design problems that cannot be efficiently resolved via conventional mathematical-based techniques. Thus, the chapters report on advanced studies on the applications of not only the traditional, but also the contemporary certain nature-inspired metaheuristic algorithms to specific engineering optimization problems with single and multi-objectives. Harmony search, artificial bee colony, teaching learning-based optimization, electrostatic discharge, grasshopper, backtracking search, and interactive search are just some of the methods exhibited and consulted step by step in application contexts. The book is a perfect guide for graduate students, researchers, academicians, and professionals willing to use metaheuristic algorithms in engineering optimization applications.

General

Imprint:	Springer Verlag, Singapore
Country of origin:	Singapore
Series:	Springer Tracts in Nature-Inspired Computing
Release date:	April 2021
First published:	2021
Editors:	Serdar Carbas • Abdurrahim Toktas • Deniz Ustun
Dimensions:	235 x 155mm (L x W)
Format:	Hardcover
Pages:	404
Edition:	1st ed. 2021
ISBN-13:	978-981-3367-72-2
Categories:	Books > Science & Mathematics > Mathematics > Numerical analysis Books > Computing & IT > General theory of computing > Mathematical theory of computation Books > Science & Mathematics > Mathematics > Optimization > General Books > Computing & IT > Applications of computing > Artificial intelligence > General
LSN:	981-3367-72-5
Barcode:	9789813367722

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