Computer Engineering and Applications ›› 2007, Vol. 43 ›› Issue (22): 38-40.

• 学术探讨 • Previous Articles     Next Articles

Research on cultural genetic algorithm based on schema fetching

GAO Li-li,LIU Hong,LI Tong-xi   

  1. Dept. of Information & Engineering,Shandong Normal University,Ji’nan 250014,China
  • Received:1900-01-01 Revised:1900-01-01 Online:2007-08-01 Published:2007-08-01
  • Contact: GAO Li-li

基于模式学习的文化遗传算法研究

高丽丽,刘 弘,李同喜   

  1. 山东师范大学 信息科学与工程学院,济南 250014
  • 通讯作者: 高丽丽

Abstract:

The paper proposes a Cultural Genetic Algorithm based on Schema Fetching(CGASF).This algorithm embeds GA into the cultural algorithm framework and composes an algorithm with GA main population space and belief space.The worst individuals of the main population space are organized periodically to study the optimal schema that the belief space provides.It exploits the information sufficiently that the optimum individual carries and speeds up the evolutionary process.Experiments results prove that the algorithm is an efficient and effective improved genetic algorithm.

Key words: genetic algorithm, cultural algorithm, schema fetching, schema learning

摘要: 针对遗传算法的缺陷,提出了一种基于模式学习的文化遗传算法,该算法将遗传算法纳入文化算法框架,组成基于GA的主群体空间和信念空间两大空间,主群体空间在进化过程中定期组织最差个体向信念空间提供的种群最优模式学习,从而充分利用了优秀个体所包含的特征信息,在很大程度上提高了收敛速度。实验结果表明,该算法是一种提高遗传算法性能的有效算法。

关键词: 遗传算法, 文化算法, 模式抽取, 模式学习