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Multi-Objective Optimization using Artificial Intelligence Techniques. 2020 ed.
・ISBN 978-3-030-24834-5 paper EUR 59.99
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| 著者・編者 | Mirjalili, Seyedali / Dong, Jin Song, |
|---|---|
| シリーズ | (SpringerBriefs in Applied Sciences and Technology) |
| 出版社 | (Springer Nature Switzerland AG, SZ) |
| 出版年月 | 2019 |
| ページ数 | 58 pp. |
| 言語 | ENG |
| ニュース番号 | <A01-97472> |
解説
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.