Multi-Objective Optimization using Artificial Intelligence Techniques - Seyedali Mirjalili,Jin Song Dong
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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 ... Pilns apraksts
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Aprašymas
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.
Vairāk informācijas
| Autors | Seyedali Mirjalili, Jin Song Dong |
|---|---|
| Izdevējs | Springer Nature Switzerland |
| Izlaides gads | 2019 |
| Vāka tips | Mīkstais vāks |
| EAN | 9783030248345 |