| 基于混合微粒群算法的带时间窗的车辆路径问题研究 |
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| 引用本文： | 吴勇,叶春明.基于混合微粒群算法的带时间窗的车辆路径问题研究[J].物流科技,2006,29(9):31-34. |
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| 作者姓名： | 吴勇 叶春明 |
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| 作者单位： | 上海理工大学,上海,200093 |
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| 基金项目： | 上海市重点学科建设项目 |
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| 摘 要： | 本文在基本微粒群算法（PSO）的位置更新中引入了模拟退火算法思想，并改进了模拟退火算法（SA）中的降温操作该算法结合了基本PSO的快速寻优能力和SA的慨率突跳性，避免了基本PSO易于陷入局部最优的缺点，提高了进化后1期算法的收敛精度.把该算法用于解决有时间窗的车辆路径问题（VRHTW），它可以有效地求得有时间窗车辆路径问题的优化解。
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| 关 键 词： | 微粒群算法 模拟退火 时间窗 车辆路径问题 |
| 文章编号： | 1002-3100（2006）09-0031-04 |
| 收稿时间： | 2006-02-26 |
| 修稿时间： | 2006年2月26日 |
Study on Vehicle Routing Problem with Time Windows Based on Hybrid Particle Swarm Optimization |
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| WU Yong,YE Chun-ming.Study on Vehicle Routing Problem with Time Windows Based on Hybrid Particle Swarm Optimization[J].Logistics Management,2006,29(9):31-34. |
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| Authors: | WU Yong YE Chun-ming |
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| Institution: | Unirersity of Shanghai for Seience and Technolog,Shanghai 200093,China |
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| Abstract: | This paper introduces the concept of simulated annealing algorithm(SA)in the position modifying of the particle swarm optimization algorithm(PSO)and improve the operation on dropping in temperature. The proposed algorithm combines the fast search optimum ablity of original PSO with probability jump property of SA. It can avoid trapping to local minima and improve the accuracy in the later evolution period compared with original PSO. Experimental results indates that the proposed algorithm can effectively get optimal resolution after it is practiced to solve the VRPTW. |
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| Keywords: | particle swarm optimization(PSO) simulated annealing(SA) time windows vehicle routing problem |
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