| 求解TSP问题的改进最大最小蚁群算法 |
| |
| 引用本文： | 杨延庆,李鹏飞,何博.求解TSP问题的改进最大最小蚁群算法[J].西北纺织工学院学报,2010(6):818-821. |
| |
| 作者姓名： | 杨延庆 李鹏飞 何博 |
| |
| 作者单位： | [1]西安工程大学计算机科学学院,陕西西安710048 [2]中国兵器工业第213研究所,陕西西安710061 |
| |
| 摘 要： | 针对基本蚁群算法搜索时间长,易产生停滞现象等缺点,提出一种求解旅行商问题的改进最大最小蚁群算法.通过对有优质解的蚂蚁个体所走路径的信息素τ的最大最小值进行固定及信息素的更新方式的改变,可以避免在算法运行过程中信息素轨迹的差异过大.仿真结果表明,该改进算法有更高的执行效率和更好的计算稳定性.
|
| 关 键 词： | 蚁群算法 旅行商问题 优质解 最大最小化 |
Improved algorithm of maximized and minimized ants on solving TSP |
| |
| YANG Yan-qing,LI Peng-fei,HE Bo.Improved algorithm of maximized and minimized ants on solving TSP[J].Journal of Northwest Institute of Textile Science and Technology,2010(6):818-821. |
| |
| Authors: | YANG Yan-qing LI Peng-fei HE Bo |
| |
| Affiliation: | 1.School of Computer Science,Xi′an Polytechnic University,Xi′an 710048,China;2.China North Industries Group Corporation Institute 213,Xi′an 710061,China) |
| |
| Abstract: | Basic ant colony algorithm to search for a long time,easy to produce stagnation and other shortcomings.We presents a modified algorithm for solving traveling salesman（TSP） problem by use of max-min ant colony algorithm.Solution through a high-quality individuals are taking the path of ants pheromone the maximum and minimum for fixed and update the pheromone change in the way,can easily be avoided during the operation in the algorithm the pheromone path difference is too large.Simulation results show that the improved algorithm has higher efficiency and better stability of the calculation. |
| |
| Keywords: | ant colony algorithm traveling salesman problem（TSP） quality solutions max-min |
| 本文献已被 维普 等数据库收录！ |
|
