SC-System of convergence theory and foundations
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| Автор: | |
|---|---|
| Формат: | artículo original |
| Статус: | Versión publicada |
| Дата публикации: | 2015 |
| Описание: | 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. |
| Страна: | Portal de Revistas UCR |
| Институт: | Universidad de Costa Rica |
| Repositorio: | Portal de Revistas UCR |
| Язык: | Inglés |
| OAI Identifier: | oai:portal.ucr.ac.cr:article/20845 |
| Online-ссылка: | https://revistas.ucr.ac.cr/index.php/matematica/article/view/20845 |
| Ключевое слово: | 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 |