突发事件下高铁列车运行与维修天窗一体化调整优化OA
Integrated optimization of high-speed railway train timetable and maintenance window rescheduling under emergencies
在高速铁路实际运营过程中,当遇到突发事件引发的列车延误和维修天窗时间延长等情况时,铁路部门需及时生成相应的延误处置策略.为解决突发事件下高铁列车运行与维修天窗的一体化调整优化问题,综合考虑列车运行调整和维修天窗约束,以列车和维修天窗总延误时间最小为目标,建立列车运行与维修天窗一体化调整优化模型.利用对偶分解方法将模型按车站分解为主问题与若干子问题,构建Dantzig-Wolfe分解模型.设计一种行列生成算法,按照线路中车站的排列顺序递次向主问题中添加区间运行约束(行),求解当前主问题并传递对偶信息供对应车站的定价子问题求解生成改进列车时刻表(列)与维修天窗开始和结束时刻,重复迭代直至生成线路上所有车站的最优列车运行和维修天窗一体化调整方案,其组合即为列车运行与维修天窗一体化调整优化问题的最优可行解.最后,为验证模型和算法的有效性,选取京沪高速铁路作为研究对象,设计不同延误场景和不同列车数量的测试案例,通过与Gurobi求解器对比分析,验证行列生成算法的质量和效率.结果表明,设计的行列生成算法在求解速度与精度上优于Gurobi,求得的列车和维修天窗总延误时间减少25.1%,求解时间在28.4 s以内.研究结果可为铁路运营管理部门在突发事件下进行高铁列车运行与维修天窗一体化调整提供科学依据.
During actual high-speed railway operations,when encountering incidents such as train delays and extended maintenance windows caused by emergencies,it is imperative for railway authorities to promptly formulate corresponding delay response strategies.To address the integrated optimization of high-speed train timetable and maintenance window rescheduling under emergencies,this study comprehensively considered train timetable rescheduling constraints and maintenance window constraints.An integrated optimization model for train timetable and maintenance window rescheduling was established,aiming to minimize the total delay time of trains and maintenance windows.Using the dual decomposition method,the model was decomposed into a master problem and several subproblems based on stations,forming a Dantzig-Wolfe decomposition model.Design a column-and-row generation algorithm that iteratively added segment operation constraints(row)to the master problem in the order of stations along the line.Solve the current master problem and pass dual information to the corresponding station's pricing subproblem to generate improved train timetable(column)along with maintenance window start and end times.Repeat the iterations until the optimal integrated rescheduling scheme for train timetable and maintenance window was obtained for all stations on the line.The resulting combination constituted the optimal feasible solution to the integrated optimization problem of train timetable and maintenance window rescheduling.Finally,to verify the effectiveness of the model and algorithm,this study selected the Beijing-Shanghai High-speed Railway as the research subject.Different delay scenarios and varying numbers of trains were designed as test cases.Through comparative analysis with the Gurobi solver,quality and efficiency of the column-and-row generation algorithm were validated.Results indicate that the designed algorithm comprehensively outperforms Gurobi in both solution speed and accuracy,it can reduce the total delay time of trains and maintenance windows by approximately 25.1%and the solution time is within 28.4 seconds.The research results can provide a scientific basis for railway operation management departments to conduct integrated rescheduling of high-speed railway train timetable and maintenance window under emergencies.
邓智文;刘斌;董傲冉;田志强;柴崇峻
兰州交通大学 交通运输学院,甘肃 兰州 730070兰州交通大学 交通运输学院,甘肃 兰州 730070兰州交通大学 交通运输学院,甘肃 兰州 730070兰州交通大学 交通运输学院,甘肃 兰州 730070兰州交通大学 交通运输学院,甘肃 兰州 730070
交通工程
高速铁路列车运行调整维修天窗混合整数规划Dantzig-Wolfe分解行列生成算法Gurobi
high-speed railwaytrain timetable reschedulingmaintenance windowmixed integer programmingDantzig-Wolfe decompositioncolumn-and-row generation algorithmGurobi
《铁道科学与工程学报》 2026 (5)
2020-2033,14
国家自然科学基金资助项目(71761023,72161023)西部铁路智能运维与管控关键技术研究(24ZYQA044)
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