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Please use this identifier to cite or link to this item: http://repositorio.ufla.br/jspui/handle/1/11498

Title: HPSOM: A hybrid particle swarm optimization algorithm with genetic mutation
???metadata.dc.creator???: Esmin, Ahmed Ali Abdalla
Matwin, Stan
Keywords: Computer algorithms
Evolutionary computation
Brownouts
Particle swarm optimization (PSO)
Hybrid particle swarm optimization (HPSOM)
Genetic algorithms (Computation)
Algoritmos computacionais
Computação evolucionária
Energia elétrica – Racionamento
Otimização por nuvem de partículas híbridas
Algorítmo genético (Computação)
Publisher: ICIC International
Issue Date: Jun-2012
Citation: ESMIN A. A. A.; MATWIN, S. HPSOM: A hybrid particle swarm optimization algorithm with genetic mutation. International Journal of Innovative Computing, Information and Control, [S. l.], v. 9, n. 5, p. 1919-1934, May 2013.
Abstract: In this paper, a hybrid particle swarm optimization algorithm (HPSOM) that uses the mutation process to improve the standard particle swarm optimization (PSO) algorithm is presented. The main idea of the HPSOM is to integrate the PSO with genetic algorithm mutation method. As a result, the proposed algorithm has the automatic balance ability between global and local searching abilities. The validity of the HPSOM algorithm is tested for a variety of benchmark problems. Experimental results show empirically that the proposed method outperforms significantly the standard PSO methods in terms of convergence speed, solution quality, ability to find the global optimum, and solution stability.
URI: http://www.ijicic.org/ijicic-12-02085.pdf
http://repositorio.ufla.br/jspui/handle/1/11498
???metadata.dc.language???: en_US
Appears in Collections:DCC - Artigos publicados em periódicos

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