Multi-Objective Optimization using Artificial Intelligence Techniques

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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.

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

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