Can I read Meta-Heuristic and Evolutionary Algorithms for Engineering Optimization on EtoBox?

Meta-Heuristic and Evolutionary Algorithms for Engineering Optimization by Bozorg-Haddad, Omid; Solgi, Mohammad; Loáiciga, Hugo A. is a scholarly article available to read on EtoBox.

What is Meta-Heuristic and Evolutionary Algorithms for Engineering Optimization about?

A detailed review of a wide range of meta-heuristic and evolutionary algorithms in a systematic manner and how they relate to engineering optimization problems This book introduces the main metaheuristic algorithms and their applications in optimization. It describes 20 leading meta-heuristic and evolutionary algorithms and presents discussions and assessments of their performance in solving optimization problems from several fields of engineering. The book features clear and concise principles and presents detailed descriptions of leading methods such as the pattern search (PS) algorithm, the genetic algorithm (GA), the simulated annealing (SA) algorithm, the Tabu search (TS) algorithm, the ant colony optimization (ACO), and the particle swarm optimization (PSO) technique. Chapter 1 of Meta-heuristic and Evolutionary Algorithms for Engineering Optimization provides an overview of optimization and defines it by presenting examples of optimization problems in different engineering domains. Chapter 2 presents an introduction to meta-heuristic and evolutionary algorithms and links them to engineering problems. Chapters 3 to 22 are each devoted to a separate algorithm- and they each st

Author

Bozorg-Haddad, Omid; Solgi, Mohammad; Loáiciga, Hugo A.

Publisher

John Wiley & Sons, Incorporated

Published

2017

Language

EN

ISBN

9781119387053