Multi-Objective Optimization using Artificial Intelligence Techniques / Seyedali Mirjalili, Jin Song Dong.
"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...
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| Main Authors: | , |
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| Format: | Ebook |
| Language: | English |
| Published: |
Cham :
Springer,
[2020]
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| Series: | SpringerBriefs in applied sciences and technology. Computational intelligence.
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| Subjects: | |
| Online Access: | Springer eBooks |
| Summary: | "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 Grey Wolf 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."--Publisher's website. |
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| Physical Description: | 1 online resource (xi, 58 pages) : illustrations (some colour). |
| Bibliography: | Includes bibliographical references. |
| ISBN: | 3030248348 9783030248345 3030248356 9783030248352 |
| ISSN: | 2625-3704 |