摘要
针对基本蚁群算法存在容易陷入局部最优解出现早熟停滞状态的缺点,提出了基于混合蛙跳思想的蚁群算法,并应用于城市交通路径寻优研究。通过引入混合蛙跳算法的全局信息共享和局部深度搜索机制,提高了蚁群算法跳出局部最优解的能力与全局收敛性。以重庆市渝中半岛的路网为实例计算以行程时间为目标的最优路径,实验结果表明该算法有效改善了基本蚁群算法的全局搜索能力,同时为解决城市交通路径寻优问题获得了较好的效果。
Due to the disadvantage of local optimum of basic ant colony algorithm, an improved ant colony algorithm based on shuffled frog leaping algorithm is proposed and applied on study about optimal route of urban road network. The global information sharing mechanism and local depth search ability of shuffled frog leaping algorithm are introduced to increase the convergence rate and the capability to avoid precocity and stagnation of basic ant colony algorithm. The road network of Chongqing Yuzhong Peninsula is taken as an example to calculate the optimal route based on the least travel time. The experimental results show that the proposed algorithm has much higher capacity of global optimization than basic ant colony algorithm and it is feasible and effective for optimal route choice.
出处
《自动化技术与应用》
2016年第4期6-9,14,共5页
Techniques of Automation and Applications
关键词
智能交通系统
蚁群算法
混合蛙跳算法
最优路径
intelligent transportation system
ant colony algorithm
shuffled frog leaping algorithm
optimal route
