摘要
蚁群算法是近年来出现的一种新的仿生优化算法。针对基本蚁群算法在求解过程中容易出现收敛时间过长以及易陷入局部最优解的不足,对算法中的状态转移、搜索方式以及信息素更新进行改进,提出了一种新的改进蚁群算法。一类典型旅行商问题的仿真实验表明改进的蚁群算法具有收敛速度快、全局搜索能力强和计算时间短的特点,证明了方法的可行性和有效性。
The ant colony algorithm is a new bionic simulated evolutionary algorithm developed in recent years.An improved ant colony algorithm(IACA) is presented to solve the limitations of the standard ant colony algorithm such as converging at local optimum.The experiments results of the typical TSP application example show that IACA has good features such as strong global search capability,rapid convergence and short computation time,which confirm the validity and feasibility of this approach.
出处
《成都信息工程学院学报》
2007年第z1期79-82,共4页
Journal of Chengdu University of Information Technology
关键词
蚁群算法
信息素
旅行商问题
ant colony algorithm
pheromone
traveling salesman problem
