用混合选择方法改进CIMDE

Chen Dan, Xia Da-hai, Xiong Cai-quan, Gu Wei
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引用次数: 0

摘要

差分进化(DE)是一种流行的进化算法。如何选择个体作为变异算子是一个非常关键的问题。许多研究者提出了改进的突变算子,通过选择更多的优秀个体来产生突变载体。基于集体信息动力突变算子的差异进化(CIMDE)提出了一种改进的集体信息动力突变算子,该算子利用多个优秀个体作为启发式信息来释放选择压力。但我们观察到,突变算子很容易陷入停滞。为此,提出了一种改进的混合突变算子“当前或从当前到当前的最佳/1”,以帮助个体脱离停滞。实验表明,该算子可以提高算法在CEC2013基准函数上的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Improving CIMDE with An Mixed Selection Method
Differential evolution(DE) is a popular evolution algorithm. How to select individuals for mutation operators is a very critical problem. Many researchers proposed improved mutation operators by selecting more outstanding individuals to produce mutated vectors. Collective information-powered mutation operator based differential evolution(CIMDE) proposed an improved collective information-powered mutation operator that uses multiple outstanding individuals as the heuristic information to release the selection pressure. But we observed that the mutation operator will be easily trapped into stagnation. So an improved mixed mutation operator named “current or rand-to-ci_ m best/1” is proposed to help individuals to departure from stagnation. Experiments show that this operator can improve the performance of the algorithm on CEC2013 bentmark functions.
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