Multi-Objective Optimization using Artificial Intelligence Techniques
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Beschreibung
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
Autor*in
Seyedali Mirjalili
Themen in »Multi-Objective Optimization using Artificial Intelligence Techniques«
MOGWO Algorithm NSGA-II MOPSO Using Multiobjective Algorithms Multi-Objective Optimization Algorithms Interactive Multi-Objective Optimization Techniques for Decision Making Pareto Optimality Dominance Posteriori Multi-Objective Optimization Impact of Mutation Rate Performance of Genetic Algorithms PSO Algorithm Evolutionary Optimization Algorithms