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Multi-Objective Optimization using Artificial Intelligence Techniques
Details
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.
Offers a concise guide to the most important multi-objective optimization techniques Discusses in detail several experimental results The source codes for all the proposed algorithms are provided on a dedicated webpage
Weitere Informationen
- Allgemeine Informationen
- GTIN 09783030248345
- Auflage 1st edition 2020
- Sprache Englisch
- Genre Allgemeines & Lexika
- Lesemotiv Verstehen
- Größe H235mm x B155mm x T5mm
- Jahr 2019
- EAN 9783030248345
- Format Kartonierter Einband
- ISBN 3030248348
- Veröffentlichung 07.08.2019
- Titel Multi-Objective Optimization using Artificial Intelligence Techniques
- Autor Jin Song Dong , Seyedali Mirjalili
- Untertitel SpringerBriefs in Applied Sciences and Technology - SpringerBriefs in Computatio
- Gewicht 125g
- Herausgeber Springer International Publishing
- Anzahl Seiten 72