| 动态自适应蚁群算法求解TSP问题 |
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| 引用本文： | 付宇,肖健梅.动态自适应蚁群算法求解TSP问题[J].计算机辅助工程,2006,15(4):10-13,18. |
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| 作者姓名： | 付宇 肖健梅 |
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| 作者单位： | 上海海事大学,物流工程学院,上海,200135 |
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| 基金项目： | 上海市教委资助项目;上海海事大学校科研和教改项目 |
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| 摘 要： | 针对基本蚁群算法容易出现早熟和停滞现象的缺点，提出一种动态自适应蚁群算法，通过引入信息素的自适应调整策略，限制信息素范围以及动态增加信息素的局部更新方式，有效抑制收敛过程中的停滞现象，提高算法的搜索能力．该算法的性能在中国旅行商问题（China Traveling Salesman Problem，CTSP）和EilSO问题上得到验证．
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| 关 键 词： | 蚁群算法 组合优化 旅行商问题 |
| 文章编号： | 1006-0871（2006）04-0010-04 |
| 收稿时间： | 2006-02-20 |
| 修稿时间： | 2006-02-202006-08-18 |
Dynamic and adaptive ant colony algorithm for solving TSP problems |
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| FU Yu,XIAO Jianmei.Dynamic and adaptive ant colony algorithm for solving TSP problems[J].Computer Aided Engineering,2006,15(4):10-13,18. |
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| Authors: | FU Yu XIAO Jianmei |
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| Affiliation: | Logistics Eng. College, Shanghai Maritime Univ., Shanghai 200135, China |
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| Abstract: | A dynamic and adaptive ant colony algorithm is presented in accordance with the defect of early variety and stagnation. The contribution of the algorithm includes an adaptive strategy of pheromone, the limited range of pheromone, and a local updating for pheromone dynamically. This method is able to restrain stagnation during the iteration process effectively, and enhance the capability of search. The experimental results for solving China Traveling Salesman Problem(CTSP) and Eil50 are proved to be effective. |
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| Keywords: | ant colony algorithm combinatorial optimization traveling salesman problem(TSP) |
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