| 基于列车车次的动车组运用优化模型与算法 |
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| 引用本文： | 钟庆伟,张永祥,王典,殷勇,闫旭,彭其渊.基于列车车次的动车组运用优化模型与算法[J].西南交通大学学报,2021,56(2):385-394. |
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| 作者姓名： | 钟庆伟 张永祥 王典 殷勇 闫旭 彭其渊 |
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| 基金项目： | 国家重点研发计划（2017YFB1200701）；国家自然科学基金（U1834209） |
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| 摘 要： | 动车组运用计划的编制通常需要综合考虑运输安全、效率及成本等多方面因素，其编制质量及编制效率对高速铁路运营有重要影响. 为了快速获得高质量动车组运用计划，以降低综合运营成本和总空驶里程等为优化目标，建立了基于列车车次的可改编动车组运用优化混合整数线性规划模型，并设计了一个迭代逼近算法框架. 该算法框架将整个问题分解为主问题和子问题，其中主问题的最优解为整个问题提供有效下界，而主问题可行解集合中能够通过子问题检验的解为整个问题提供有效上界，从而算法框架可以不断地更新上、下界之间的最优间隙，迫使生成更接近于下界的新可行解. 多个实例分析表明:所提出的方法与人工方法相比，能够快速生成动车组运用计划，且使得动车组综合运营成本平均下降10.5%，总空驶里程平均减少23%.
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| 关 键 词： | 高铁网络 动车组运用优化 改编 维修约束 迭代逼近算法 |
| 收稿时间： | 2019-12-11 |
Optimization Model and Algorithm for Train-Set Scheduling Based on Trip Sequence |
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| ZHONG Qingwei,ZHANG Yongxiang,WANG Dian,YIN Yong,YAN Xu,PENG Qiyuan.Optimization Model and Algorithm for Train-Set Scheduling Based on Trip Sequence[J].Journal of Southwest Jiaotong University,2021,56(2):385-394. |
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| Authors: | ZHONG Qingwei ZHANG Yongxiang WANG Dian YIN Yong YAN Xu PENG Qiyuan |
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| Abstract: | Usually, the train-set schedule involves several practical aspects, such as operational safety, efficiency, and cost. The quality and efficiency of the schedule have a significant impact on the operation of high-speed railways. In order to quickly obtain a high-quality train-set schedule, a mixed-integer linear programming (MILP) model that takes composition changes on the basis of the trip sequences was established with the optimization goals of reducing operating costs and total deadhead mileages. Furthermore, an iterative gap reducing algorithm is developed to solve the MILP model, which divides the whole problem into the master problem and sub-problem. The master problem provides an effective lower bound for the whole problem, and its solutions that can pass the sub-problem provide an effective upper bound for the whole problem. As a result, the algorithm can continuously reduce the gap between bounds and generate a new feasible solution towards the lower bound. The real cases show that compared with the manual method, the proposed method can generate a high quality one-day train-set schedule in a short time, which reduces the total operating costs by 10.5% and the total deadhead mileage by 23%. |
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