| 一种求解TSP问题的相遇蚁群算法 |
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| 引用本文： | 赵文彬,孙志毅,李虹.一种求解TSP问题的相遇蚁群算法[J].计算机工程,2004,30(12):136-137,185. |
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| 作者姓名： | 赵文彬 孙志毅 李虹 |
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| 作者单位： | 1. 太原重型机械学院数学系,太原,030024
2. 太原重型机械学院电子信息分院,太原,030024 |
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| 基金项目： | 山西省自然科学基金资助项目(20021046) |
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| 摘 要： | 蚁群算法是由意大利学者M．Dorigo等人首先提出的一种新型的仿生算法。蚁群算法与其他算法同样存在搜索速度慢，易于陷于局部最优。该文提出一种改进的相遇算法克服了以上的缺陷。通过对TSP问题的仿真结果表明，提出的相遇算法与基本蚁群算法相比搜索速度和性能都有一定的提高。
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| 关 键 词： | TSP问题 蚁群算法 组合优化 相遇算法 |
| 文章编号： | 1000-3428(2004)12-0136-02 |
A Meeting Ant Colony Optimization Algorithm of Solving TSP Problem |
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| ZHAO Wenbin,SUN Zhiyi,LI Hong.A Meeting Ant Colony Optimization Algorithm of Solving TSP Problem[J].Computer Engineering,2004,30(12):136-137,185. |
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| Authors: | ZHAO Wenbin SUN Zhiyi LI Hong |
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| Affiliation: | ZHAO Wenbin1,SUN Zhiyi2,LI Hong2 |
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| Abstract: | Ant colony optimization (ACO) algorithm is a novel metaheuristic algorithm which is proposed first by Italian scholars M. Dorigo,V. Maniezzo,A. Colorni. Its searching speed is slow and it is easy to fall in local best as other evolutionary algorithm .In this paper ,an improved meeting algorithm is presented to solve this shortcoming .The simulation for TSP problems shows that the improved meeting algorithm is efficient and searching speed outperforms the basic ACO. |
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| Keywords: | TSP problem Ant colony optimization(ACO)algorithm Combinatorial optimization Meeting algorithm |
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