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计算机工程 ›› 2010, Vol. 36 ›› Issue (9): 190-191,. doi: 10.3969/j.issn.1000-3428.2010.09.066

• 人工智能及识别技术 • 上一篇    下一篇

基于蚁群算法的聚类优化

张 丽1,刘希玉1,李章泉2   

  1. (1. 山东师范大学管理与经济学院,济南 250014;2. 德州学院,德州 253023)
  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2010-05-05 发布日期:2010-05-05

Clustering Optimization Based on Ant Colony Algorithm

ZHANG Li1, LIU Xi-yu1, LI Zhang-quan2   

  1. (1. School of Management and Economics, Shandong Normal University, Jinan 250014; 2. Dezhou College, Dezhou 253023)
  • Received:1900-01-01 Revised:1900-01-01 Online:2010-05-05 Published:2010-05-05

摘要: 为解决大型网络中的最短路径问题,基于蚁群算法进行聚类优化研究。结合蚁群算法和聚类算法,将网络分割成若干个小网络后进行处理并合成,同时在过程中直接简化网络,透明化无意义的点。实验结果表明,优化后的算法能准确获得所要求的最优解,具有较快的收敛速度。

关键词: 蚁群算法, 路径优化, 路网简化, 聚类优化

Abstract: In order to solute the shortest path problem in the large networks, a clustering algorithm based on ant colony optimization is analysed. According to ant colony algorithm and clustering algorithm combining the idea, using the large-scale network is separated into several small networks to deal with later after the synthesis as well as directly in the process to simplify network approach. Transparency of the optimization algorithm meaningless points, thus simplify the calculation, improve computational efficiency. Experimental results show that the optimization algorithm can accurately obtain the required optimal solution, and has a faster convergence speed.

Key words: ant colony algorithm, path optimization, road network simplification, clustering optimization

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