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| 求解旅行商问题的混合粒子群优化算法 | |
| 引用本文： | 高 尚,韩 斌,吴小俊,杨静宇.求解旅行商问题的混合粒子群优化算法[J].控制与决策,2004,19(11):1286-1289. |
| 作者姓名： | 高 尚 韩 斌 吴小俊 杨静宇 |
| 作者单位： | 1. 江苏科技大学,电子信息学院,江苏,镇江,212003;南京理工大学,计算机系,江苏,南京,210094 2. 江苏科技大学,电子信息学院,江苏,镇江,212003 3. 南京理工大学,计算机系,江苏,南京,210094 |
| 摘 要： | 结合遗传算法、蚁群算法和模拟退火算法的思想，提出用混合粒子群算法来求解著名的旅行商问题．与模拟退火算法、标准遗传算法进行比较，24种混合粒子群算法的效果都比较好，其中交叉策略D和变异策略F的混合粒子群算法的效果最好，而且简单有效．对于目前仍没有较好解法的组合优化问题，通过此算法修改很容易解决． |
| 关 键 词： | 粒子群算法 遗传算法 模拟退火算法 蚁群算法 旅行商问题 |
| 文章编号： | 1001-0920(2004)11-1286-04 |
| 修稿时间： | 2003年12月29 |
Solving traveling salesman problem by hybrid particle swarm optimization algorithm |
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| GAO Shang.Solving traveling salesman problem by hybrid particle swarm optimization algorithm[J].Control and Decision,2004,19(11):1286-1289. | |
| Authors: | GAO Shang |
| Abstract: | The particle swarm optimization algorithm combining with the ideal of the genetic algorithm,the ant colony algorithm and the simulated annealing algorithm are presented to solve the well known traveling salesman problem. Compared with the standard GA and simulated annealing algorithm,all 24 hybrid particle swarm optimization algorithms are proved effective. Especially the hybrid particle swarm optimization algorithm with across strategy and mutation strategy is simple and effective. It can easily be modified for any combinatorial problem for which there is no good specialized algorithm up to now. |
| Keywords: | particle swarm algorithm genetic algorithm simulated annealing algorithm ant colony algorithm traveling salesman problem |
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