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.
