基因表达式编程初始种群的多样化策略

The Strategy for Diversifying Initial Population of Gene Expression Programming

基因表达式编程(GeneExpressionProgramming,GEP)算法是遗传家族的新成员,被广泛用于知识发现,其初始种群的质量对进化效率和进化结果至关重要.为了产生优势初始种群,提出了基因空间均匀分布策略(GeneSpaceBalanceStrategy,GSBS),证明了描述编码空间量化性质的GEP编码空间定理.实验表明,GSBS提高进化效率超过20%.GSBS算法的思想还可以应用于其它进化计算中.

Gene Expression Programming （GEP） is a new genetic algorithm for knowledge discovery. The diversification of initial population is very important to the evolution efficiency and result. In order to produce excellent initial population of GEP, Gene Space Balance Strategy （GS- BS） is proposed. The theorem of describing the space of GEP encoding is proved. The simulation experiments show that GSBS can increase the evolutionary efficiency by 20%. The idea of GSBS algorithms can be used in other evolutionary computation else.