SpringerBriefs in Applied Sciences and Technology

Mirjalili, Seyedali; Dong, Jin Song

This book focuses on the most well-regarded and recent nature-inspired algorithms capable of solving optimization problems with multiple objectives. Firstly, it provides preliminaries and essential definitions in multi-objective problems and different paradigms to solve them. It then presents an in-depth explanations of the theory, literature review, and applications of several widely-used algorithms, such as Multi-objective Particle Swarm Optimizer, Multi-Objective Genetic Algorithm and Multi-objective GreyWolf Optimizer Due to the simplicity of the techniques and flexibility, readers from any field of study can employ them for solving multi-objective optimization problem. The book provides the source codes for all the proposed algorithms on a dedicated webpage.

Details

Published by: Springer

Publication Date: 2019-08-07

Format: Paperback

ISBN-13: 9783030248345

DOI: 10.1007/978-3-030-24835-2

Dimensions: 235cm x155cm

Pages: 58