| Título: | Particle Swarm Optimization with Flexible Swarm for Unconstrained Optimization |
| Autores: |
Kahramanlı, Humar; Selcuk University Allahverdi, Novruz; Selcuk University |
| Fecha: | 2013-03-11 |
| Publicador: | International Journal of Intelligent Systems and Applications in Engineering |
| Fuente: |
 |
| Tipo: |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
| Tema: | Particle Swarm Optimization Algorithm;Particle Swarm Optimization Algorithm with Flexible Swarm; Unconstrained Optimization |
| Descripción: | Particle Swarm Optimization (PSO) algorithm inspired from behavior of bird flocking and fish schooling. It is well-known algorithm which has been used in many areas successfully. However it sometimes suffers from premature convergence. In resent year’s researches have been introduced a various approaches to avoid of this problem. This paper presents the particle swarm optimization algorithm with flexible swarm (PSO-FS). The new algorithm was evaluated on 14 functions often used to benchmark the performance of optimization algorithms. PSO-FS algorithm was compared to some other modifications of PSO. The results show that PSO-FS always performed one of the better results. |
| Idioma: | Inglés |
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