An improved gene expression programming algorithm based on hybrid strategy

Chao-xue Wang, Jing-jing Zhang, Shu-ling Wu, Chunsen Ma
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引用次数: 4

Abstract

Gene expression programming (GEP) is a new evolutionary algorithm, which has the very good applications in the field of function finding. In view of the insufficiency of traditional GEP, this paper puts forward an improved gene expression programming algorithm based on hybrid strategy (HSI-GEP). This paper has two improvements: (1) using mirror and reset mechanism to replace the inferior individuals of population, to improve the quality and the diversity of population; (2) introducing the clonal selection before tournament selection in order to improve the mining ability of algorithm about the superior individuals. The experiments compared with the improved GEP from authoritative literatures about function finding problems have been carried on, and the results show that HSI-GEP is of high quality, has fast convergence rate and obvious competitiveness.
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一种改进的基于混合策略的基因表达式编程算法
基因表达编程(Gene expression programming, GEP)是一种新的进化算法,在功能查找领域有很好的应用。针对传统GEP算法的不足,提出了一种改进的基于混合策略的基因表达编程算法(HSI-GEP)。本文的改进之处有两点:(1)利用镜像和重置机制替代种群中的劣势个体,提高种群的质量和多样性;(2)在竞赛选择之前引入克隆选择,以提高算法对优秀个体的挖掘能力。与权威文献中关于函数查找问题的改进GEP进行了实验比较,结果表明HSI-GEP质量高,收敛速度快,具有明显的竞争力。
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