Multi-Objective Optimization using Artificial Intelligence Techniques

Seyedali Mirjalili, Jin Song Dong (Autoren)

Buch | Softcover

XI, 58 Seiten

2019 | 1st ed. 2020
Springer International Publishing (Verlag)
978-3-030-24834-5 (ISBN)

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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.

Erscheinungsdatum	09.08.2019
Reihe/Serie	SpringerBriefs in Applied Sciences and Technology
Reihe/Serie	SpringerBriefs in Computational Intelligence
Zusatzinfo	XI, 58 p. 26 illus., 25 illus. in color.
Verlagsort	Cham
Sprache	englisch
Maße	155 x 235 mm
Gewicht	129 g
Themenwelt	Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik
	Technik
	Wirtschaft ► Betriebswirtschaft / Management ► Unternehmensführung / Management
Schlagworte	Evolutionary Optimization Algorithms • Impact of Mutation Rate • Interactive Multi-Objective Optimization • MOGWO Algorithm • MOPSO • Multi-objective Optimization Algorithms • NSGA-II • Pareto Optimality Dominance • Performance of Genetic Algorithms • Posteriori Multi-Objective Optimization • PSO algorithm • Techniques for Decision Making • Using Multiobjective Algorithms
ISBN-10	3-030-24834-8 / 3030248348
ISBN-13	978-3-030-24834-5 / 9783030248345
Zustand	Neuware