Multi-Objective Optimization using Artificial Intelligence Techniques.
Mirjalili, Seyedali
Multi-Objective Optimization using Artificial Intelligence Techniques. - Switzerland Springer Nature 2020 - xi, 58 pages; Figures; - Computational Intelligence .
1. Introduction to Multi-objective Optimization
-2. What is Really Multi-objective Optimization?
-3. Multi-objective Particle Swarm Optimization
-4. Non-dominated Sorting Genetic Algorithm
-5. Multi-objective Grey Wolf Optimizer
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.
9783030248345
Computational Intelligence
Optimization
Artificial Intelligence
006.3 / M675
Multi-Objective Optimization using Artificial Intelligence Techniques. - Switzerland Springer Nature 2020 - xi, 58 pages; Figures; - Computational Intelligence .
1. Introduction to Multi-objective Optimization
-2. What is Really Multi-objective Optimization?
-3. Multi-objective Particle Swarm Optimization
-4. Non-dominated Sorting Genetic Algorithm
-5. Multi-objective Grey Wolf Optimizer
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.
9783030248345
Computational Intelligence
Optimization
Artificial Intelligence
006.3 / M675