Multi-Objective Optimization using Artificial Intelligence Techniques (Paperback, 1st ed. 2020)

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.

General

Imprint:	Springer Nature Switzerland AG
Country of origin:	Switzerland
Series:	SpringerBriefs in Applied Sciences and Technology
Release date:	July 2019
First published:	2020
Authors:	Seyed Ali Mirjalili • Jin Song Dong
Dimensions:	235 x 155mm (L x W)
Format:	Paperback
Pages:	58
Edition:	1st ed. 2020
ISBN-13:	978-3-03-024834-5
Categories:	Books > Business & Economics > Business & management > Management & management techniques > Operational research Books > Computing & IT > Applications of computing > Artificial intelligence > Machine learning
LSN:	3-03-024834-8
Barcode:	9783030248345

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