基于蚁群算法的聚类优化  

Clustering Optimization Based on Ant Colony Algorithm

作　　者：张丽[1] 刘希玉[1] 李章泉[2] 

机构地区：[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

出　　处：《计算机工程》2010年第9期190-191,194,共3页Computer Engineering

基　　金：国家自然科学基金资助项目(60873058);山东省自然科学基金资助项目(Z2007G03)

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。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.

关 键 词：蚁群算法 路径优化 路网简化 聚类优化 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]