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.
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