A new hybrid genetic algorithm based on clan competition

Weihong Zhou, Shun-Qing Xiong, L. Ying
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Abstract

It is difficult for basic genetic algorithm and evolutionary programming algorithm to converge at global optimal solution of real-continual function in practice, although both of the algorithms have the ability for getting the global optimal solution with convergent probabilities 1 in theory. In this paper, a new hybrid genetic algorithm based on clan competition is proposed, and it is proved that the probability of the new algorithm convegent to the global optimal solution is 1, Numerical experiments results illustrate that, compared with the former two algorithms, the new algorithm is the robustest among the three algorithms, what's more, it has the highest precision with the equal parameters.
一种基于宗族竞争的混合遗传算法
基本遗传算法和进化规划算法在实践中难以收敛于实连续函数的全局最优解,尽管这两种算法在理论上都具有收敛概率为1的全局最优解能力。本文提出了一种新的基于族竞争的混合遗传算法,并证明了新算法收敛到全局最优解的概率为1,数值实验结果表明,与前两种算法相比,新算法是三种算法中最鲁棒的,并且在等参数下具有最高的精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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