| 不确定条件下速度时变VRPTW问题 |
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| 引用本文： | 李兵飞,熊智勇,张建业,毛声,赵晓林.不确定条件下速度时变VRPTW问题[J].控制与决策,2017,32(5):804-810. |
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| 作者姓名： | 李兵飞 熊智勇 张建业 毛声 赵晓林 |
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| 作者单位： | 航空电子系统综合技术重点实验室,上海200233;空军工程大学航空航天工程学院,西安710051,航空电子系统综合技术重点实验室,上海200233,空军工程大学航空航天工程学院,西安710051,空军工程大学航空航天工程学院,西安710051,空军工程大学航空航天工程学院,西安710051 |
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| 基金项目： | 航空科学基金项目(20145596024). |
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| 摘 要： | 构建了不确定条件下速度时变的VRPTW问题模型(UTDVRPTW),设计了一种改进的双重进化人工蜂群算法求解该模型.在需要两点进行操作的搜索过程中,采用一点随机选取,另一点通过遍历可行解,以其中最优解确定位置的半随机式搜索策略改进插入点算子和逆转序列算子,分别在两对以及三对城市间距离之和的解空间维度上交叉搜索,并应用到局部搜索中构成双重进化过程.实验结果验证了所提出算法的有效性以及解决UTDVRPTW的可行性.
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| 关 键 词： | 不确定性 时间窗 双重进化人工蜂群算法 |
Uncertain time-dependent vehicle routing problem with time window |
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| LI Bing-fei,XIONG Zhi-yong,ZHANG Jian-ye,MAO Sheng and ZHAO Xiao-lin.Uncertain time-dependent vehicle routing problem with time window[J].Control and Decision,2017,32(5):804-810. |
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| Authors: | LI Bing-fei XIONG Zhi-yong ZHANG Jian-ye MAO Sheng and ZHAO Xiao-lin |
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| Affiliation: | Laboratory of Science and Technology on Avionics Integration Technologies,Shanghai 200233,China;School of Aeronautics and Astronautics Engineering,Air Force Engineering University,Xián710051,China,Laboratory of Science and Technology on Avionics Integration Technologies,Shanghai 200233,China,School of Aeronautics and Astronautics Engineering,Air Force Engineering University,Xián710051,China,School of Aeronautics and Astronautics Engineering,Air Force Engineering University,Xián710051,China and School of Aeronautics and Astronautics Engineering,Air Force Engineering University,Xián710051,China |
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| Abstract: | The uncertain time dependent vehicle routing problems with time windows(UTDVRPTW) is proposed by introducing the uncertain theory and obtaining the minimal expected total cost as the goal. A variation of artificial bee colony algorithm is proposed to solve the problem. In the search process of requiring two points operating, the half stochastic optimal searching strategy is used to improve the traditional insertion operator and inversion operator, in which one point is randomly selected, and another point is selected by traversing the feasible solution space. Cross search is done respectively in the sum of the distance between different cities in the solution space and applied to the dual evolution form of local search. Experimental results show the effectiveness and feasibility of the proposed algorithm for solving the UTDVRPTW. |
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