【摘要】 传统GEP(Gene Expression Programm ing)算法存在局部收敛方面的缺陷,为了解决这一问题,提出了可以使进化快速跳出局部最优的VPS-GEP(Various Popu lation Strategy GEP)算法,证明了在概率意义上GEP平均每代进化所耗时间与群体规模成正比,用两个标准测试函数和一个标准测试数据集测试了VPS-GEP算法的函数挖掘能力和效率。实验表明,VPS-GEP算法可以减少进化停滞代数55%以上。更多还原

【Abstract】 The traditional Gene Expression Programming(GEP) has the deficiency of local optimization.In order to solve this problem,VPS-GEP(Various Population Strategy GEP),an algorithm for evolution skipping from local optimization fast,was proposed.It was proved that the time for per-generation evolution increases with the size of population under probability sense.The ability of mining function and efficiency of VPS-GEP was tested by two standard test functions and one standard dataset.The experiments showed that VPS-GEP algorithm decreases the generation-stagnancy over 55%.更多还原