摘要
蚁群算法是一种新型高效的启发式优化算法,在解决优化组合问题特别是TSP求解问题上具有很高效率。本文在分析了蚁群算法的基本原理和工作机制的基础上,从信息素的更新改进实现对节点重复率的控制,并通过仿真实验实现相关参数的最优选择。实验证明,改进算法可以有效地减少蚂蚁行走的盲目性,提高了蚁群算法在迭代过程中更新TSP最优解的能力。
The ant colony algorithm is a new kind of algorithm which is effecitive and heuristic in solving optimized combination problems,such as TSP.We analysis the basic principle and working mechanism of ant colony algorithm and put forward an improved method.Our scheme can control the repetition rate of nodes by updating the pheromone in time.Then the related parameters are set optimally by simulations.The experiment proves that the improved algorithm effectively reduces the aimlessness of ants and enhances the capacity for acquiring the optimum solution of TSP problem in the iterative process.
出处
《科技通报》
北大核心
2012年第12期72-75,共4页
Bulletin of Science and Technology
基金
校级重点教学研究课题(201103)
关键词
蚁群算法
TSP
信息素
因子
ant colony algorithm
TSP
pheromone
factor
