用群体启发进化规划求解高维优化问题

用群体启发进化规划求解高维优化问题

窦全胜^1,2,周春光²,徐中宇³,潘冠宇²

（1.山东工商学院信息与电子工程学院，山东省烟台264005；2.吉林大学计算机科学与技术学院，长春130012；3.长春工业大学计算机科学与工程学院，长春130012）

收稿日期:2005-01-10 修回日期:1900-01-01 出版日期:2005-09-26 发布日期:2005-09-26
通讯作者: 周春光

Population Heuristic Evolutionary Programming for High-dimension Optimization

DOU Quan-sheng^1,2,ZHOU Chun-guang²,XU Zhong-yu³,PAN Guan-yu²

（1.School of Information and Electronics Engineering，Shandong Institute of Business and Technology，Yantai264005，Shandong Province，China；2.College of Computer Science and Technology，Jilin University，Changchun130012，China；3.School of Computer Science and Engineering，Changchun University of Technology，Changchun130012，China）

Received:2005-01-10 Revised:1900-01-01 Online:2005-09-26 Published:2005-09-26
Contact: ZHOU Chun-guang

摘要/Abstract

摘要： 提出一种新的进化规划方法，群体启发进化规划（PHEP），在进化过程中，通过控制群体的4个参数，把握群体中个体分布情况，并通过这些信息有效地调整个体的变异步长，克服了传统EP方法变异步长修正的盲目性.将PHEP方法应用于高维优化问题，实验结果表明，PHEP方法在高维条件下的性能明显优于其他EP方法.

关键词: 进化规划, 高维优化, 群体

Abstract: A new evolutionary programming method known as population heuristic evolutionary programming （PHEP）was proposed in this paper.The information of distribution-status of population can be known by controlling four parameters of population in the evolution process and the mutation size of individuals can be adjusted according to such information，so as to overcome the deficiency of traditional EP, which updates the mutation size blindly.PHEP was tested by using benchmark functions under high-dimension condition，the experimental results show that the performance of PHEP is better than that of other EP method obviously under high-dimension condition.

Key words: evolutionary programming, high-dimension optimization, population

中图分类号:

TP301

窦全胜,周春光,徐中宇,潘冠宇. 用群体启发进化规划求解高维优化问题[J]. J4, 2005, 43(05): 622-626.

DOU Quan-sheng,ZHOU Chun-guang,XU Zhong-yu,PAN Guan-yu. Population Heuristic Evolutionary Programming for High-dimension Optimization[J]. J4, 2005, 43(05): 622-626.

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