Multi-Objective Optimization using Artificial Intelligence Techniques / SpringerBriefs in Applied Sciences and Technology (PDF)
(Sprache: Englisch)
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...
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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.
Bibliographische Angaben
- Autoren: Seyedali Mirjalili , Jin Song Dong
- 2019, 1st ed. 2020, 58 Seiten, Englisch
- Verlag: Springer-Verlag GmbH
- ISBN-10: 3030248356
- ISBN-13: 9783030248352
- Erscheinungsdatum: 24.07.2019
Abhängig von Bildschirmgrösse und eingestellter Schriftgrösse kann die Seitenzahl auf Ihrem Lesegerät variieren.
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- Dateiformat: PDF
- Grösse: 4.55 MB
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Sprache:
Englisch
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