Multi-Objective Optimization using Artificial Intelligence Techniques
Seiten
2019
|
1st ed. 2020
Springer International Publishing (Verlag)
978-3-030-24834-5 (ISBN)
Springer International Publishing (Verlag)
978-3-030-24834-5 (ISBN)
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 | 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 |
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