【摘要】 受生物基因片段重叠表达现象的启发,文中提出了一种新的基于重叠表达进化算法——MEOE(Multi-gene Evolutionary algorithm based on Overlapped Expression).文章具体描述了MEOE的基因表达结构及相应的算法.不同于已有的工作,在MEOE中作为遗传物质的基因具有重复表达的概率,同时算法融合了免疫算法关于浓度的计算技术.文章对MEOE算法作了较为全面的分析,讨论了算法在表达空间、可表达性、性状遗传上的特点,并与传统算法作了相应比较.详尽的实验证明,MEOE算法在速度上是GEP的2.5~9.4倍.在高次函数发现问题上MEOE算法的成功率比GEP提高至少一个数量级.另外,通过实验证明了基于密度的概率选择函数在高次函数发现问题上具有一定优势.更多还原

【Abstract】 Inspired by the overlapped gene expression in the phenomena of biology,this paper proposes a novel evolutionary algorithm,MEOE(Multi-gene Evolutionary algorithm based on Overlapped Expression),and describes the genetic expression structures and relevant algorithm of it.Different from existing works,MEOE suggests a new expression structure of genes with probabilities of overlapped expression for some segments and borrows some idea from artificial immunity algorithm.This paper systematically analyzes MEOE,discusses the features of expression space,capability of expression,and compares MEOE with traditional algorithms.The detailed experiments show that MEOE algorithm is 2.5～9.4 times faster than usual GEP method,and in higher-degree polynomial function finding problem,the success rate of MEOE is 10 times than usual GEP.The experiments results also show that the probability selection function based on density works well in higher-degree polynomial function finding problem.更多还原