| 求解TSP的遗传蚁群融合算法 |
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| 引用本文： | 江君莉,潘丰. 求解TSP的遗传蚁群融合算法[J]. 江南大学学报(自然科学版), 2012, 11(3): 253-256 |
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| 作者姓名： | 江君莉 潘丰 |
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| 作者单位： | 江南大学轻工过程先进控制教育部重点实验室,江苏无锡,214122 |
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| 摘 要： | 原有的遗传融合蚁群算法虽然克服了基本蚁群算法的不足,优化效果得到了改善,但存在克服收敛速度较慢、易出现停滞以及全局搜索能力较低的缺陷.针对存在容易陷入局部最优解等问题,在原有的遗传融合蚁群算法的基础上进行了许多改进以扩大解的搜索空间,提高了其寻优能力和速度.仿真结果表明,改进后的算法具有更好的寻优能力,效果较好.
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| 关 键 词： | 旅行商问题 蚁群算法 模拟进化算法 遗传算法 |
Hybrid of Ant Colony Algorithm and Genetic Algorithm and Its Application in TSP |
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| JIANG Jun-li , PAN Feng. Hybrid of Ant Colony Algorithm and Genetic Algorithm and Its Application in TSP[J]. Journal of Southern Yangtze University:Natural Science Edition, 2012, 11(3): 253-256 |
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| Authors: | JIANG Jun-li PAN Feng |
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| Affiliation: | (Key Laboratory of Advanced Process Control for Light Industry,Ministry of Education,Jiangnan University,Wuxi 214122,China) |
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| Abstract: | Compared to basic colony algorithm,former ant colony algorithm based on genetic gene has overcome lots of problems,such as slow convergence speed,easy to get stagnated,and low ability of full search etc.But it also have some disvantages,such as easy to fall into a local optimal solution.Therefore,made many improvements in the former ant algorithm based on genetic gene to expand search space solutions,to improve its optimization ability and speed.The experimental results indicated that the improved algorithm has better optimization ability,results are satisfactory. |
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| Keywords: | TSP ant colony algorithm simulated evolutionary algorithm genetic algorithm |
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