基于信息融合的多维自适应蚁群优化算法研究  

Research on optimization algorithm for multidimensional adaptive ant colony based on information fusion

作　　者：董甲东[1] 郑春香[2] 

机构地区：[1]安庆师范学院物理与电气工程学院,安徽安庆246011 [2]安庆师范学院计算机与信息学院,安徽安庆246011

出　　处：《信息技术》2015年第10期53-56,共4页Information Technology

基　　金：安徽省教育厅自然科学研究重点项目(KJ2011A199)

摘　　要：文中设计了多维系统各子蚁群时间同步方案以及信息融合时间窗口开启策略;针对影响蚁群算法的主要参数,提出动态认知的参数自适应调整改进算法,实现算法初期路径选择的多样性、成熟后可提高算法的寻优效率。以解决TSP问题为例,对启发式因子、信息素挥发因子等主要参数对蚁群最优路径影响进行仿真分析。Time synchronization scheme and time window strategy of sub ant colony in multidimensional system are designed. In view of the influence of the main parameters of ant colony algorithm,the algorithm with the parameters of improved adaptive dynamic cognition is proposed. At the early stage of the algorithm,path selection can achieve diversity. The algorithm reaches maturity,the searching efficiency can be improved. In order to solve the TSP problem as an example,the simulation analysis of the main parameters that influence the heuristic factor,pheromone volatilization factor on ant colony optimal path is presented.

关 键 词：蚁群算法 时间同步 自适应 参数优化 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]