计算机应用 ›› 2005, Vol. 25 ›› Issue (02): 374-376.DOI: 10.3724/SP.J.1087.2005.0374

• 软件技术 • 上一篇    下一篇

一种基于学习机制的并行遗传算法

张桂娟,武兆慧,刘希玉   

  1. 山东师范大学信息管理学院
  • 发布日期:2005-02-01 出版日期:2005-02-01
  • 基金资助:

    国家自然科学基金资助项目 ( 6037405 );;山东省自然科学基金重大项目 (Z2004G02 );;山东省中青年科学家奖励基金资助项目(03BS003)

Parallel genetic algorithm based on learning mechanism

ZHANG Gui-juan, WU Zhao-hui,LIU Xi-yu   

  1. ollege of Information Management, Shandong Normal University
  • Online:2005-02-01 Published:2005-02-01

摘要: 基于生物学群落的概念,提出了一个群落—种群—个体的三层模型,并在该模型上发展了一种基于学习机制的并行遗传算法(PGABL)。算法引入黑板模型作为控制和交互的数据结构,采用群内、群间、群落三个学习算子,将遗传进化和遗传学习相结合,有效地改善了遗传算法的性能。实验结果表明,该算法具有良好的适应性和稳定性。

关键词: 遗传学习, 早熟收敛, 并行遗传算法

Abstract: Based on the concept of biotic community in Biology, a 3-layer model named community-population-individual was proposed. Meanwhile, a parallel genetic algorithm based on learning mechanism (PGABL) was developed on this model. As the data structure for collaborations between subpopulations, the Blackboard model was introduced. And three learning operators are designed, through which PGABL combines the advantages of genetic evolution and genetic learning that improves the performance of traditional genetic algorithm effectively. Experimental results show that PGABL is of good adaptability and stability.

Key words: genetic learning, premature convergence, parallel genetic algorithm

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