Título: Um Algoritmo Híbrido Paralelo Cooperativo Baseado em DE, PSO e AG: Uma Avaliação em Computadores Multicore
Autores: Cortes, Omar Andres Carmona; Barros, Bruno Alberth Silva; Lopes, Rafael Fernandes; Silva, Josenildo Costa da; Prado, Pedro Felipe do
Resumo: This paper presents a new parallel hybrid algorithm combining Particle Swarm Optimization (PSO), Differential Evolution (ED) and Genetic Algorithms (GA) for optimizing unconstrained numerical functions. Basically, PSO and ED evolves independently in our proposal, then they cooperate between them exchanging their best individual, which undergo GA operators locally in order to search different areas in the search space. The results are evaluated concerning the quality of the solution and speedup against six benchmarks functions. The outcomes are compared with GA, PSO and ED in the serial version and with the classical island model of PSO and DE, considering two and four threads. A comparison with a hybrid algorithm is done as well.
Palavras-chave: Optimization; particle swarm; genetic algorithms; constraints; benchmarks
Código DOI: 10.21528/CBIC2013-021
Artigo em pdf: bricsccicbic2013_submission_21.pdf
Arquivo BibTex: bricsccicbic2013_submission_21.bib