| 遗传算法和蚁群算法在求解TSP问题上的对比分析 |
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| 引用本文： | 蔡光跃,董恩清. 遗传算法和蚁群算法在求解TSP问题上的对比分析[J]. 计算机工程与应用, 2007, 43(10): 96-98 |
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| 作者姓名： | 蔡光跃 董恩清 |
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| 作者单位： | 苏州大学,电子信息学院,江苏,苏州,215021;苏州大学,电子信息学院,江苏,苏州,215021 |
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| 摘 要： | 遗传算法(Generation Algorithm, GA)和蚁群算法(Ant Colony Optimization, ACO)都是解决组合优化问题的强有力算法。特别是近几年的研究表明，蚁群算法具有极强的鲁棒性和求最优解的能力。本文在分析这两种算法的特点基础上，通过实例验证它们在解决TSP问题上各自的优缺点，并给出做进一步研究的建议。
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| 关 键 词： | 遗传算法 蚁群算法 TSP |
| 文章编号： | 1002-8331（2007）10-0096-03 |
| 收稿时间： | 2006-04-14 |
| 修稿时间： | 2006-07-01 |
Comparison and analysis of generation algorithm and ant colony optimization on TSP |
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| CAI Guang-yue,DONG En-qing. Comparison and analysis of generation algorithm and ant colony optimization on TSP[J]. Computer Engineering and Applications, 2007, 43(10): 96-98 |
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| Authors: | CAI Guang-yue DONG En-qing |
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| Affiliation: | School of Electronic and Information Engineering,Soochow University,Soochow,Jiangsu 215021,China |
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| Abstract: | GA(Generation Algorithm) and ACO(Ant Colony Optimization) are two powerful and effective algorithms for solving the combination optimization problems.Recent researches indicate that ACO has high robustness and better ability for searching optimal results.On the base of analysis regarding the two algorithms,their advantages and disadvantages are given by means of large numbers of experiments respectively.Some future research suggestions are provided. |
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| Keywords: | Generation Algorithm Ant Colony Optimization TSP |
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