铁路编组站配流协同优化模型与算法

编组站配流问题是研究车站作业计划优化编制的主线, 是站调阶段计划的核心. 为了实现配流的协同优化, 综合考虑解体调机、编组调机、到发线运用、取送车作业、配流等约束, 对总车流量、出发列车满轴列数、车辆在站停留时间等目标函数进行层次划分, 建立了编组站配流优化模型, 并以ECGACO算法为基础, 设计了针对配流问题的遗传-蚁群协同求解算法. 以郑州北站的实际数据进行测试证明了算法的有效性, 为编组站阶段计划的优化编制及配流智能化的实现提供了较好的解决途径.

Collaborative optimization model and algorithm for wagon-flow allocation in railway marshalling station

Wagon-flow allocation problem, as the core of stage plan for station dispatcher, it is the key to study operation plan compilation of a station. To realize collaborative optimization for wagon-flow allocation, an optimization model for marshalling station was established, in which the objective functions include number of total wagon-flows and departure trains in full load, and residence time of wagons at station. In addition, the constraints were considered which include shunting locomotive for train sorting and classifying, utilization of arrival and departure track, placing-in and taking-out operation, and wagon-flow allocation. A kind of genetic and ant colony collaborative optimization algorithm based on ECGACO was designed, which takes the characteristic of wagon-flow allocation problem into consideration. Numerical examples of Zhengzhoubei station verify the effectiveness of the algorithm. A better solution is provided for optimization compilation of stage plan and intelligent wagon-flow allocation in a marshalling station.