基于货运服务网络的铁路局车辆排空优化模型研究

Research on Optimization Model of Empty Car Distribution among Regional Railways Based on Freight Service Network

本文研究铁路空车调配过程中的车辆局外排空问题。针对已有研究对于铁路局之间的车辆排空问题缺乏有效模型与优化算法的问题,本文构建了综合考虑车辆排空成本与排空速度的整数规划优化模型,该模型能够依据空车分布情况动态选择车辆集结地、规划车辆集结路径。本文设计了针对上述模型的混合遗传算法,利用最小费用最大流算法计算种群中个体的适应度值,从而得到具有高精确性的解。通过数值实验表明,在货运服务费用已知的前提下,本文所采用的方法平均节约空车集结成本35%以上。

This paper studies the problem of empty car distribution among regional railways. We have not seen any work on effective models and optimization algorithms for this problem. We construct an integer programming optimization model that considers the trade-off between the cost and distributing speed. The model dynamically selects assembly stations and plans car assembly paths according to the distribution of empty car. In this paper, a hybrid genetic algorithm for the above model is designed, and the minimum cost maximum flow algorithm is used to calculate the fitness value of individuals in the population, thus obtaining the high-accuracy solution. Numerical experiments show that under the premise of known freight service cost, the method adopted in this paper can save over 35% of the assembly cost on average.