| 改进蚁群算法在解决TSP问题中的应用 |
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| 引用本文： | 李雪,王雷.改进蚁群算法在解决TSP问题中的应用[J].宜春学院学报,2020(3):63-67. |
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| 作者姓名： | 李雪 王雷 |
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| 作者单位： | 安徽工程大学机械与汽车工程学院 |
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| 基金项目： | 安徽省自然科学基金(1708085ME129);安徽工程大学“中青年拔尖人才”项目。 |
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| 摘 要： | 在已知静态环境的条件下,提出一种改进蚁群算法,用以解决基本蚁群算法的收敛速度慢、效率低、易陷入局部最优解等问题。在传统蚁群算法的基础上,首先通过自适应改变挥发系数来使初始时刻的蚁群搜索能力加强、范围扩大,避免陷入局部最优解;其次将轮盘赌算子利用到状态转移规则中,有效地提高了解的质量和算法的收敛速度;最后通过精英选择操作,有效地提高了算法的全局搜索效率和收敛速度。通过对不同TSP实例仿真结果表明:改进后的蚁群算法在较少的迭代次数下得到的解非常接近问题的最优解,验证了该算法的可行性和有效性。
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| 关 键 词： | 改进蚁群算法 自适应改变 轮盘算子 精英选择 TSP |
Application of Improved Ant Colony Algorithm in Solving TSP Problem |
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| LI Xue,WANG Lei.Application of Improved Ant Colony Algorithm in Solving TSP Problem[J].Journal of Yichun University,2020(3):63-67. |
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| Authors: | LI Xue WANG Lei |
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| Institution: | (School of Mechanical and Automotive Engineering,Anhui Polytechnic University,Wuhu 241000,China) |
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| Abstract: | Under the condition of known static environment,an improved ant colony algorithm is proposed to solve the problems of slow convergence,low efficiency and easy to fall into local optimal solution existing in the basic ant colony algorithm.Based on the traditional ant colony algorithm,the ant colony search ability at the initial moment is strengthened and the range is expanded to avoid falling into the local optimal solution by adaptively changing the volatility coefficient.Secondly,the roulette operator is used in the state transition rule.Effectively improve the quality of solution and the convergence speed of the algorithm;Finally,through the elite selection,the global search efficiency and convergence speed of the algorithm are effectively improved.The simulation results of different TSP examples show that the improved ant colony algorithm is close to the known optimal solution with fewer iterations.The experimental results demonstrate the feasibility and effectiveness of the algorithm. |
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| Keywords: | improved ant colony optimization adaptively change the roulette operator the elite selection TSP |
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