SC-System of convergence theory and foundations
Guardado en:
| 作者: | |
|---|---|
| 格式: | artículo original |
| 状态: | Versión publicada |
| Fecha de Publicación: | 2015 |
| 实物特征: | In this paper a novel system of convergence (SC) is presented as well as its fundamentals and computing experience. An implementation using a novel mono-objetive particle swarm optimization (PSO) algorithm with three phases (PSO-3P): stabilization, generation with broad-ranging exploration and generation with in-depth exploration, is presented and tested in a diverse benchmark problems. Evidence shows that the three-phase PSO algoritm along with the SC criterion (SC-PSO-3P)can converge to the global optimum in several difficult test functions for multiobjective optimization problems, constrained optimization problems and unconstrained optimization problems with 2 until 120,000 variables. |
| País: | Portal de Revistas UCR |
| 机构: | Universidad de Costa Rica |
| Repositorio: | Portal de Revistas UCR |
| 语言: | Inglés |
| OAI Identifier: | oai:portal.ucr.ac.cr:article/20845 |
| 在线阅读: | https://revistas.ucr.ac.cr/index.php/matematica/article/view/20845 |
| Palabra clave: | particle swarm optimization unconstrained optimization constrained optimization multiobjective optimization fuzzy numbers optimización por enjambres de partículas optimización sin res- tricciones optimización con restricciones optimización multiobjetivo |