一种改进的变异算子,可提高遗传算法的性能

Yingying Song, Feifei Yan
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引用次数: 1

摘要

针对遗传算法中存在的早熟收敛和局部优化问题,提出了一种改进的组合变异算子。CM算子结合高斯突变和初始突变对种群中的个体进行局部初始化操作,在保持种群多样性的同时提高了算子的局部搜索能力。15个基准优化问题的结果表明,所提出的CM算子可以有效地提高算法的性能,并且与其他先进算法相比,改进算法(IRCGA)具有更强的搜索能力和更快的收敛速度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Improved Mutation Operator Which Can Improve the Performance of Genetic Algorithm
An improved combined mutation operator (CM) is proposed for the problems of premature convergence and local optimization which often occur in genetic algorithm (GA). The CM operator combines the Gaussian mutation and the initial mutation to perform local initialization operations on individuals in the population, and maintain the population diversity while improving the local search ability of the operator. The results of 15 benchmark optimization problems show that the proposed CM operator can effectively improve the performance of the algorithm, and compared with other advanced algorithms, the improved algorithm (IRCGA) has stronger search capabilities and faster convergence speed.
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