双系统协同进化的基因表达式编程及其在函数发现中的应用

计算机工程与科学

双系统协同进化的基因表达式编程及其在函数发现中的应用

王超学,吴书玲,张婧菁

（西安建筑科技大学信息与控制工程学院，陕西西安 710055）

收稿日期:2015-09-16 修回日期:2015-11-04 出版日期:2016-11-25 发布日期:2016-11-25
基金资助:
国家自然科学基金（31170393）；陕西省自然科学基金（2012JM8023）

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

摘要/Abstract

摘要：

受人类进化过程的启发，提出了一种双系统协同进化的基因表达式编程算法DSCEGEP。DSCEGEP由自

然进化系统和人工干预系统组成。人工干预系统包括个体干预和种群干预。个体干预是依据基因库对种

群中的个体进行去劣和增优操作，旨在改善种群中个体的质量；种群干预通过引入随机和镜像个体来提

高种群的多样性和全局寻优能力。与权威文献中改进的GEP关于函数发现问题的大量对比实验表明，本文

算法在收敛速度、求解质量方面优于对比算法，具有明显的竞争力。

关键词: 双系统协同进化基因表达式编程, 基因库, 人工干预系统, 函数发现问题

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:

double system coevolutionary gene expression programming;gene pool;artificial , intervention system;function finding problems

王超学,吴书玲,张婧菁. 双系统协同进化的基因表达式编程及其在函数发现中的应用[J]. 计算机工程与科学.

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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