基于混合差异度控制的基因表达式编程

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Abstract Gene expression programming (GEP) is an evolution algorithm which has the problem of local optimization like other evolution algorithms. The general method to this problem is to keep the diversity degree of population in the evolution. A method is proposed for measuring the diversity of the population, and it merges characters of both population space and sample space. Based on the method for mergence measuring the diversity of population, GEP evolution algorithm with diversity control is proposed. The rival theory is introduced into the initialization of population. The experimental results show that the proposed algorithm efficiently avoids falling into early local optimization.

Key words： Gene Expression Programming (GEP) Local Optimization Diversity of Population Rival Theory Fusing Diversity of Population

Received: 23 December 2010

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	XUAN Shi-Bin
	LIU Yi-Guang

Cite this article:

XUAN Shi-Bin,LIU Yi-Guang. GEP Evolution Algorithm Based on Control of Mixed Diversity Degree[J]. , 2012, 25(2): 186-194.

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http://manu46.magtech.com.cn/Jweb_prai/EN/ OR http://manu46.magtech.com.cn/Jweb_prai/EN/Y2012/V25/I2/186

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