Multi-Objective Optimization using Artificial Intelligence Techniques / / by Seyedali Mirjalili, Jin Song Dong
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| Autore: |
Mirjalili Seyedali
|
| Titolo: |
Multi-Objective Optimization using Artificial Intelligence Techniques / / by Seyedali Mirjalili, Jin Song Dong
|
| Pubblicazione: | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 |
| Edizione: | 1st ed. 2020. |
| Descrizione fisica: | 1 online resource (xi, 58 pages) |
| Disciplina: | 006.3 |
| Soggetto topico: | Computational intelligence |
| Machine learning | |
| Operations research | |
| Computational Intelligence | |
| Machine Learning | |
| Operations Research and Decision Theory | |
| Persona (resp. second.): | DongJin Song |
| Sommario/riassunto: | 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. |
| Titolo autorizzato: | Multi-Objective Optimization using Artificial Intelligence Techniques |
| ISBN: | 3-030-24835-6 |
| Formato: | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione: | Inglese |
| Record Nr.: | 9910484985003321 |
| Lo trovi qui: | Univ. Federico II |
| Opac: | Controlla la disponibilità qui |
Serie:
SpringerBriefs in Computational Intelligence, . 2625-3712