| 求解TSP问题的一种改进蚁群算法 |
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| 引用本文： | 王峰峰,王仁明,伍佳.求解TSP问题的一种改进蚁群算法[J].自动化技术与应用,2010,29(7):1-3. |
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| 作者姓名： | 王峰峰 王仁明 伍佳 |
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| 作者单位： | 三峡大学,电气与新能源学院,湖北,宜昌,433002 |
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| 摘 要： | TSP问题是典型的NP—hard组合优化问题，用蚁群算法求解此问题存在搜索时间长，容易陷入局部最优解的不足。本文提出了一种改进的蚁群算法。该算法在蚁群算法中植入遗传算法，利用遗传算法生成信息素的分布，克服了蚁群算法中搜索时间长的缺陷。此外，在蚁群算法寻优中，采用交叉和变异的策略，改善了TSP解的质量。仿真结果显示，改进的蚁群算法是有效的。
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| 关 键 词： | 蚁群算法 遗传算法 TSP问题 |
An Improved Ant Colony Algorithm for Solving TSP |
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| WANG Feng-feng,WANG Ren-ming,WU Jia.An Improved Ant Colony Algorithm for Solving TSP[J].Techniques of Automation and Applications,2010,29(7):1-3. |
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| Authors: | WANG Feng-feng WANG Ren-ming WU Jia |
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| Affiliation: | WANG Feng-feng,WANG Ren-ming,WU Jia(College of Electrical and New Energy,Three Gorges University,Yichang 433002 China) |
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| Abstract: | TSP is a classical NP-hard combinatorial optimization.There are some drawbacks such as long time searching and fall into local optimal solution.This paper presents an optimized algorithm for solving TSP.The proposed algorithm combines the ant colony algorithm and genetic algorithm.It uses GA to generate the distribution of pheromone.In addition,in the ant colony algorithm,the crossover and mutation strategies is used to improve the quality of TSP solution.The simulation result shows that the improved algori... |
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| Keywords: | ant colony algorithm genetic algorithm TSP optimization |
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