Double system coevolutionary gene expression programming
and its application in function finding problems

WANG Chaoxue,WU Shuling,ZHANG Jingjing

（School of Information and Control Engineering,Xi’an University of Architecture and

Technology,Xi’an 710055,China）

Received:2015-09-16 Revised:2015-11-04 Online:2016-11-25 Published:2016-11-25

Abstract:

Inspired by the evolution process of human,we propose a double system coevolutionary gene

expression programming (DSCEGEP).The DSCEGEP consists of a natural evolution system and

an artificial intervention system.The latter includes individual intervention operation and

population intervention operation.The individual intervention operation is based on a gene

pool which aims to improve the quality of individuals.It has a repairing operator that

removes the morbid genes in individuals and a strengthening operator that spreads eminent

genes to the individuals.The population intervention operation improves the diversity of

population and the global searching ability of the algorithm by introducing a certain

number of feasible random individuals and feasible mirror individuals.Experimental results

show that the performance of the DSCEGEP is better than that of other GEP algorithms

proposed in related literatures regarding function finding problems in terms of convergence

speed and solution quality,and that it promises competitive performance.

Key words:

WANG Chaoxue,WU Shuling,ZHANG Jingjing.

Double system coevolutionary gene expression programming

and its application in function finding problems

[J]. Computer Engineering & Science.

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