SC-System of convergence theory and foundations

 

Đã lưu trong:
Chi tiết về thư mục
Tác giả: De-Los-Cobos-Silva, Sergio G.
Định dạng: artículo original
Trạng thái:Versión publicada
Ngày xuất bản:2015
Miêu tả: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.
Quốc gia:Portal de Revistas UCR
Tổ chức giáo dục:Universidad de Costa Rica
Repositorio:Portal de Revistas UCR
Ngôn ngữ:Inglés
OAI Identifier:oai:portal.ucr.ac.cr:article/20845
Truy cập trực tuyến:https://revistas.ucr.ac.cr/index.php/matematica/article/view/20845
Từ khóa: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