计算机工程与应用 ›› 2007, Vol. 43 ›› Issue (15): 37-40.

• 学术探讨 • 上一篇    下一篇

基于粒子群位移转移的混合遗传算法及其应用

苗 荣,闫 伟,李树荣   

  1. 中国石油大学 信息与控制工程学院,山东 东营 257061
  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2007-05-21 发布日期:2007-05-21
  • 通讯作者: 苗 荣

Novel hybrid GA based on position displacement idea of PSO and its application

MIAO Rong,YAN Wei,LI Shu-rong   

  1. College of Information and Control Engineering,China University of Petroleum,Dongying,Shandong 257061,China
  • Received:1900-01-01 Revised:1900-01-01 Online:2007-05-21 Published:2007-05-21
  • Contact: MIAO Rong

摘要: 基于粒子群位移转移的思想,改变遗传算法的变异规则,提出了一种新的混合遗传算法。利用3个benchmark函数测试了新的混合算法的性能,并将测试结果与标准遗传算法进行了比较。提出了一种多阶段半方差投资选择模型,并将混合算法应用在多阶段半方差投资选择问题的求解上。

关键词: 混合遗传算法, 粒子群算法, 投资选择问题, 多阶段半方差

Abstract: A novel genetic algorithm is proposed,in which the position displacement idea of the PSO(Particle Swarm Optimization) is applied to change the mutation operation rule.The validity of the algorithm is tested by using three benchmark functions.From the comparison of the results obtained by using HGA and standard GA respectively,the accuracy of HGA is much better than that of SGA.In the end,a multi-period semi-variance portfolio selection problem is presented and the HGA is applied to solve a multi-period semi-variance portfolio selection problem.

Key words: hybrid GA, PSO algorithm, portfolio selection problem, multi-period semi-variance