Multi-Objective Optimization using Artificial Intelligence Techniques

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.

Riassunto

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.

Dettagli sul prodotto

• Autori: Jin Song Dong, Seyedal Mirjalili, Seyedali Mirjalili
• Editore: Springer, Berlin
• Lingue: Inglese
• Formato: Tascabile
• Pubblicazione: 01.01.2019
• EAN: 9783030248345
• ISBN: 978-3-0-3024834-5
• Pagine: 58
• Dimensioni: 154 mm x 5 mm x 177 mm
• Peso: 138 g
• Illustrazioni: XI, 58 p. 26 illus., 25 illus. in color.
• Serie: SpringerBriefs in Applied Sciences and Technology; SpringerBriefs in Computational Intelligence
• Categorie: Scienze naturali, medicina, informatica, tecnica > Tecnica > Tematiche generali, enciclopedie; Operations Research, C, Unternehmensforschung, machine learning, Maschinelles Lernen, Management: Entscheidungstheorie, engineering, Operations Research/Decision Theory, Operations Research and Decision Theory, Management decision making, Operational research, Decision Making, Computational Intelligence, Performance of Genetic Algorithms, Evolutionary Optimization Algorithms, PSO Algorithm