Computer Engineering and Applications ›› 2010, Vol. 46 ›› Issue (36): 7-10.DOI: 10.3778/j.issn.1002-8331.2010.36.002

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Novel hybrid GA based on bare bones PSO and its application

LEI Yang,LI Shu-rong,ZHANG Qiang,ZHANG Xiao-dong   

  1. College of Information and Control Engineering,China University of Petroleum,Dongying,Shandong 257061,China
  • Received:2010-10-18 Revised:2010-12-05 Online:2010-12-21 Published:2010-12-21
  • Contact: LEI Yang


雷 阳,李树荣,张 强,张晓东   

  1. 中国石油大学(华东) 信息与控制工程学院,山东 东营 257061
  • 通讯作者: 雷 阳

Abstract: A novel Genetic Algorithm(GA) is proposed,in which the position displacement idea of bare bones Particle Swarm Optimization(PSO) is applied to change the mutation operator.The validity of the algorithm is tested by using three benchmark functions.From the comparison of the results obtained by using Hybrid Genetic Algorithm(HGA) and Standard Genetic Algorithm(SGA) respectively,the accuracy of HGA is much better than that of SGA.In the end,the HGA is applied to solve the optimal control problem of polymer flooding.

Key words: Hybrid Genetic Algorithm(HGA), bare bones Particle Swarm Optimization(PSO), optimal control, polymer flooding

摘要: 采用骨干粒子群的位置更新操作改进遗传算法的变异算子,提出一种新的混合遗传算法。利用三个benchmark函数测试了新的混合遗传算法的性能,并将测试结果与标准遗传算法进行比较。利用该方法,对聚合物驱最优控制问题的进行了仿真求解,结果表明该方法优于标准遗传算法。

关键词: 混合遗传算法, 骨干粒子群, 最优控制, 聚合物驱

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