Heuristic search strategy of evolutionary programming

Authors:
Zhi-Ming Han;Xian-Ping Liu;Miao Tang
Affiliations:
Institute of Information and Spreading Engineering, Changchun University of Technology, Changchun, China;School of Mechatronic Engineering, Changchun University of Technology, Changchun, China;College of Software, Changchun University of Technology, Changchun, China
Venue:
CAR'10 Proceedings of the 2nd international Asia conference on Informatics in control, automation and robotics - Volume 1
Year:
2010

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Abstract

Evolutionary programming (EP) has been successfully applied to many optimization problems in recent years. However, most experimental results of EP have been obtained under low-dimension condition and weren't perfect under high-dimension condition. A new evolutionary programming method which named Heuristic Search Strategy (HSS) was proposed for solving high-dimension optimization problem. It can grasp the information of distribution-status of population by control four parameters of population in the evolution process and adjust the mutation size of individual according to such information. HSS was test by using benchmark functions, the experimental results show that performance of HSS is better than other EP method obviously under high-dimension condition.