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Multi-Objective Optimization using Artificial Intelligence Techniques

Inhalt

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.

Bibliografische Angaben

August 2019, 58 Seiten, SpringerBriefs in Computational Intelligence, SpringerBriefs in Applied Sciences and Technology, Englisch
Springer Nature EN
978-3-030-24834-5

Schlagworte

Weitere Titel der Reihe: SpringerBriefs in Computational Intelligence

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