标题：MREP: Multi-Reference Expression Programming
作者：Zhang, Qingke; Meng, Xiangxu; Yang, Bo; Liu, Weiguo
作者机构：[Zhang, Qingke; Meng, Xiangxu; Liu, Weiguo] Shandong Univ, Minist Educ, Engn Res Ctr Digital Media Technol, Sch Comp Sci & Technol, Jinan 250101, Peop 更多
会议名称：12th International Conference on Intelligent Computing (ICIC)
会议日期：AUG 02-05, 2016
来源：INTELLIGENT COMPUTING THEORIES AND APPLICATION, ICIC 2016, PT II
关键词：Multi-expression programming; Cross-layer-reference; Two dimensional; operators; Genetic programming; Symbol regression
摘要：MEP is a variant of genetic program applied to solve the symbol regression and classification problems. It can encode multiple solutions of a problem in a single chromosome. However, when the ratio of genes reuse is low, it may not get a high accuracy result within limited iterations and may fall into the trap of local optimum. Therefore, we proposed a novel genetic evolutionary algorithm named MREP (multi-reference expression programming). The MREP chromosome is encoded in a two-dimensional structure and each gene in one chromosome can refer other sub-layer's gene randomly. The main contribution can be described as follows: Firstly, a novel chromosome encoding scheme is proposed based on a two-dimensional structure. Secondly, two different cross-layer reference strategies are designed to enhance the code reuse of genes located at different layers in one chromosome. Two groups experiments were conducted on eight symbol regression functions. The statistical results reveal that the MREP performs better than the compared algorithms and can solve the symbol regression functions problem efficiently.