高速铁路列车开行方案两阶段优化方法研究

Two-stage Optimization Method of High Speed Railway Train Operation Scheme

我国高速铁路客流时空分布复杂且有明显的时变特征,这就要求铁路运营企业能够根据客流出行的时空分布特征设计相吻合的列车开行方案,并根据客流需求变化来制定和调整列车开行方案以提供相应的运输产品。根据高速铁路客流出行需求,提出了列车开行方案两阶段优化方法,生成研究时段内备选开行列车集合,以最小化列车旅行时间和动车组车小时数为目标构建初始开行方案模型M1,然后以旅客总旅行时间最小为目标构建客流分配模型M2。针对模型M1的特点,设计基于遗传算法的启发式求解方法,模型M2运用商业软件ILOGCPLEX进行求解。通过京兰通道北京北—呼和浩特东段的实际案例分析,验证模型的正确有效性和算法的适用性。

The time-space distribution of passenger flow of high speed railway in China is complex and has obvious time-varying characteristics,which requires railway operators to design train operation schemes according to the time-space distribution characteristics of passenger flow,and formulate and adjust train operation schemes according to the changes in passenger flow demand to provide corresponding transport products.According to the passenger travel demand of high speed railway,a two-stage optimization method of preparing the train operation scheme was proposed.By constructing a space-time network,all trains that can be operated in the study period were depicted.The outline model M1 of the operation scheme was constructed to minimize the train travel time and the number of EMU hours,and then the passenger flow distribution model M2 was constructed to minimize the total travel time of passengers.According to the characteristics of model M1,a heuristic solution method based on a genetic algorithm was designed.Model M2 was solved by commercial software ILOG CPLEX.The correctness and validity of the model and the applicability of the algorithm were verified by the actual case study of the Beijingbei-Huhehaotedong section of the Beijing-Lanzhou corridor.