HPSOM: A HYBRID PARTICLE SWARM OPTIMIZATION ALGORITHM WITH GENETIC MUTATION

Ahmed A. A. Esmin; Stan Matwin

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HPSOM: A HYBRID PARTICLE SWARM OPTIMIZATION ALGORITHM WITH GENETIC MUTATION

机译：HPSOM：带有遗传突变的混合粒子群优化算法

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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.

机译：本文提出了一种混合的粒子群优化算法（HPSOM），该算法利用变异过程来改进标准的粒子群优化（PSO）算法。 HPSOM的主要思想是将PSO与遗传算法变异方法集成在一起。结果，所提出的算法具有全局和局部搜索能力之间的自动平衡能力。已针对各种基准问题测试了HPSOM算法的有效性。实验结果表明，该方法在收敛速度，求解质量，寻找全局最优值的能力以及求解稳定性方面均明显优于标准PSO方法。

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《International Journal of Innovative Computing Information and Control》 |2013年第5期|1919-1934|共16页
作者
Ahmed A. A. Esmin; Stan Matwin;
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作者单位

Department of Computer Science Federal University of Lavras Lavras, MG 37200-000, Brazil,School of Electrical Engineering and Computer Science University of Ottawa Ottawa, ON, Canada;

School of Electrical Engineering and Computer Science University of Ottawa Ottawa, ON, Canada,Institute of Computer Science Polish Academy of Sciences Warsaw, Poland;

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正文语种 eng
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关键词
PSO; Evolutionary algorithm; Hybrid PSO;

机译：PSO;进化算法;混合PSO;

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HPSOM: A HYBRID PARTICLE SWARM OPTIMIZATION ALGORITHM WITH GENETIC MUTATION

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