Multi-Objective Optimization using Artificial Intelligence Techniques

✍ Scribed by Seyedali Mirjalili, Jin Song Dong

Publisher: Springer
Year: 2020
Tongue: English
Leaves: 66
Category: Library

No coin nor oath required. For personal study only.

✦ Synopsis

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.

✦ Table of Contents

Front Matter ....Pages i-xi
Introduction to Multi-objective Optimization (Seyedali Mirjalili, Jin Song Dong)....Pages 1-9
What is Really Multi-objective Optimization? (Seyedali Mirjalili, Jin Song Dong)....Pages 11-20
Multi-objective Particle Swarm Optimization (Seyedali Mirjalili, Jin Song Dong)....Pages 21-36
Non-dominated Sorting Genetic Algorithm (Seyedali Mirjalili, Jin Song Dong)....Pages 37-45
Multi-objective Grey Wolf Optimizer (Seyedali Mirjalili, Jin Song Dong)....Pages 47-58

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