SC: a novel fuzzy criterion for solving engineering and constrained optimization problems
In this paper a novel fuzzy convergence system (SC) and its fundamentals are presented. The model was implemented on a monoobjetive PSO algorithm with three phases: 1) Stabilization, 2) generation and breadth-first search, and 3) generation and depth-first. The system SC-PSO-3P was tested with sever...
| Autores: | , , , , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2017 |
| País: | Costa Rica |
| Institución: | Universidad de Costa Rica |
| Repositorio: | Portal de Revistas UCR |
| Idioma: | inglés |
| OAI Identifier: | oai:portal.ucr.ac.cr:article/22353 |
| Acceso en línea: | https://revistas.ucr.ac.cr/index.php/matematica/article/view/22353 |
| Access Level: | acceso abierto |
| Palabra clave: | particle swarm optimization (PSO) optimization optimización por enjambres de partículas optimización |
| Sumario: | In this paper a novel fuzzy convergence system (SC) and its fundamentals are presented. The model was implemented on a monoobjetive PSO algorithm with three phases: 1) Stabilization, 2) generation and breadth-first search, and 3) generation and depth-first. The system SC-PSO-3P was tested with several benchmark engineering problems and with several CEC2006 problems. The computing experience and comparison with previously reported results is presented. In some cases the results reported in the literature are improved. |
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