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。 Railway current “cargo system ” freight organization principle, requests to the customer to open the car to accept the application, as soon as possible, promptly approved. In this paper, aiming at the volatility of empty customer application, a two-stage optimization model of empty allocation of railway vehicles is established and corresponding strategies of “pre-optimized empty allocation” and “secondary optimization allocation” are formulated. The pre-optimized empty car deployment is to optimize the empty car adjustment for the fixed demand. The second dynamic allocation refers to the strategy optimization that is restarted for the newly generated car loading needs during the pre-optimization deployment. The decision-making cycle of the empty truck is divided into periods, and the cost minimization is taken as the objective function. The model is made by taking the micro-evolutionary algorithm of integer coding as an example, taking into account the arrival capability of the station, the demand and supply capacity of the empty vehicles at each time, Solve. The examples show that the model and the algorithm can better solve the problem of dynamic changes of the empty demand, and provide the decision basis for the empty vehicle to adjust and approve the empty customer application.