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【背景】在运行图和预测需求已知条件下，动车组交路、灵活编组与乘务交路强耦合，分阶段编制易造成车辆接续、编组转换和乘务覆盖不协调。【目标】面向运行图和预测需求已知的计划编制场景，研究动车组交路、编组状态和乘务覆盖的联合优化问题。模型同时考虑短编、重联和长编状态转换，以及换编能力、库存容量和乘务覆盖约束。【方法】构建含短编、重联和长编状态的车次时空状态网络，建立耦合编组选择、车辆状态弧流、换编能力、时变库存和乘务候选列选择的双目标0-1混合整数规划模型，并采用Gurobi ε-约束法与FS-NSGA-Ⅱ-MEA算法求解。【结果】中等规模算例中，Gurobi构造基准非支配前沿；重复运行表明，FS-NSGA-Ⅱ-MEA较普通NSGA-Ⅱ可行解获取更稳定。大规模算例中，算法获得满足关键约束的可行近似解集。【结论】在确定性需求条件下，所建模型能够同时描述动车组交路、编组状态转换和乘务覆盖之间的关联关系，所设计算法可用于较大规模算例的可行方案搜索。
Abstract：【Background】With a given timetable and forecast demand， EMU circulation， flexible formation and crew routing are strongly coupled， and staged planning may lead to inconsistent vehicle connections， formation changes and crew coverage.【Objective】The joint optimization problem of EMU circulation， formation states and crew coverage is studied for a planning scenario with a given timetable and forecast demand. The model considers state transitions among short， coupled and long formations， as well as formation-change capacity， inventory capacity and crew coverage constraints.【Method】A train-task time-space-state network with short， coupled and long formation states is constructed. A bi-objective 0-1 mixed-integer programming model is formulated by coupling formation selection， vehicle state arc flow， formation-change capacity， time-varying inventory and crew-column selection， and is solved by the Gurobi epsilon-constraint method and the FS-NSGA-Ⅱ-MEA algorithm.【Result】For the medium-scale instance， Gurobi constructs a benchmark nondominated frontier. Repeated runs show that FS-NSGA-Ⅱ-MEA obtains feasible solutions more stably than plain NSGA-Ⅱ. For the large-scale instance， the algorithm obtains a feasible approximate solution set satisfying key constraints.【Conclusion】The results show that， under deterministic demand， the proposed model can describe the relationships among EMU circulation， formation-state transitions and crew coverage， and the designed algorithm can be used to search feasible solutions for larger-scale instances.
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基本信息:
DOI：10.19961/j.cnki.1672-4747.2026.05.036
中图分类号:U292
引用信息:
[1]刘宗贤,何世伟,迟居尚,等.动车组交路、灵活编组与乘务交路联合优化方法[J].交通运输工程与信息学报().DOI:10.19961/j.cnki.1672-4747.2026.05.036.
基金信息:
中国国家铁路集团有限公司科技研究开发计划课题项目（K2025X011）; 中央高校基本科研业务费专项资金资助（科技领军人才团队项目）（2022JBQY006）
2026-07-07
2026-07-07
2026-07-07