计算机科学 ›› 2010, Vol. 37 ›› Issue (2): 196-199.

• 人工智能 • 上一篇    下一篇

基于EDA的并行基因表达式程序设计方法

杜欣,丁立新,谢承旺,陈莉   

  1. (武汉大学软件工程国家重点试验室 武汉430074);(空军雷达学院 武汉430019);(石家庄经济学院 石家庄050031)
  • 出版日期:2018-12-01 发布日期:2018-12-01
  • 基金资助:
    本文受高等学校博士点基金(No.20070486081),湖北省杰出青年基金(No. 2005ABB017)资助。

Parallel Gene Expression Programming Based on FDA

DU Xin,DING Li-xin,XIE Cheng-wang,CHEN Li   

  • Online:2018-12-01 Published:2018-12-01

摘要: 将分布评估算法(EDA)引入基因表达式程序设计方法中,以提高其收敛速度。为减少计算时间,提高解质量,在加入EDA的基因表达式程序设计方法的基础上设计了同步和异步分布式并行算法,同时比较了同步和异步并行算法。实验结果表明,并行算法提高了运行速度和解质量。最后通过实验分析了迁移代频对并行算法的影响。

关键词: 基因表达式程序设计方法,分布评估算法,并行算法,MPI

Abstract: In order to reduce the computation time and improve the quality of solutions of Gene Expression Programming (GEP),synchronous and asynchronous distributed parallel GEP algorithm based on Estimation of Distribution Algorithm (EDA)was proposed. The idea of introducing EDA into GEP is to accelerate the convergence speed. Moreover,the improved GEP was implemented by synchronous and asynchronous distributed parallel method based on the island parallel model. Some experiments were done on distributed network connected by twenty computers. The best results of sequential and parallel algorithms were compared, speedup and performance influence of some important parallel control parameters to this parallel algorithm were discussed. hhe experimental results show that parallel algorithms may approach linear speedup and have better ability to find optimal solution and higher stability than sequential algorithm.

Key words: UEP, EDA,Parallel algorithm, MPI

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