“实货制”下铁路空车动态调配两阶段优化模型与算法研究

Study on Two-phase Optimization Models and Algorithms for Empty Railcar Dynamic Distribution Based on "Real Freight System"

铁路现行的"实货制"货运组织原则,要求对客户提出的要车申请敞开受理、随到随办、及时批复。本文针对客户空车申请具有波动性的特点,构建铁路空车动态调配两阶段优化模型,制定相应的"预优化空车调配"和"二次优化调配"两阶段求解策略。预优化空车调配是对固定需求的空车调整进行优化,二次动态调配指执行预优化调配过程中,对于新产生的装车需求而重新进行的策略优化。将空车调配的决策周期进行时段划分,以费用最小化为目标函数,综合考虑车站的到发能力、各时段空车供需能力、线路通过能力建立模型,采用整数编码的微进化算法对模型进行求解。算例表明模型与算法能够较好解决空车需求动态变化的调配问题,为空车调整及批复客户空车申请提供决策依据。

The ＂Real Freight System＂ principle of current railway freight transport organization requires that customers＂ demand for railcars be accepted openly, be handled at any time and be approved timely. In view of the fluctuation of customer applications for empty railcars, a two-stage optimization model of Empty Railcar Dynamic Distribution was constructed to develop corresponding two-phase solutions of ＂Pre-optimization Distribution for empty railcars＂ and ＂Second Dynamic Distribution＂. The former aimed to optimize the railcars＇ distribution when the demands were steady and the latter aimed to make further strategic optimization based on newly generated loading demands during the implementation of ＂Pre-optimization Distribution＂ process. By di- viding the decision-making cycle for empty railcar distribution into certain periods of time, with cost minimization as objective function, the model was built considering the impact of receiving and departing capacity of stations, supply and demand capacity for empty railcars in each period of time,and transport capacity of rail-lines. The Microevolution Algorithm that used integer coding was proposed to solve the problem. The example showed that the model and algorithm can better solve the distribution issue involving the dynamic changes in the demands for empty railcars, providing the decision basis for the distribution of empty railcars and approval for customer＇s application for empty railcars.