摘要
在传统蚁群算法的基础上,结合混沌的遍历性、随机性和规律性,提出一种混沌蚁群算法,阐述该算法在智能交通系统中应用的可行性,解决了智能交通中常见的最优路径问题,并通过实验数据说明本算法的有效性.
Based on the properties of ergodicity, randomicity, and regularity of chaos, a chaos ant colony optimization（CACO）algorithm is proposed to solve searching shortest path of the intelligent transportation system. The practicability of the application of the CACO in the ITS is also discussed in this paper. Compared with the standard ACA and other simulated annealing algorithms, simulation results show that the chaos ant colony optimization is an effective algorithm.
出处
《成都大学学报（自然科学版）》
2007年第4期309-312,共4页
Journal of Chengdu University（Natural Science Edition）
基金
山东省自然科学基金(Q2006G03)资助项目
关键词
蚁群算法
混沌
混沌蚁群算法
智能交通
ant colony algorithm
chaos
chaos ant colony optimization algorithm
intelligent transportation system
