关键词: 铁路运输, 编组站, 阶段计划, 随机相关机会规划, 混合智能算法鲁棒性

Abstract: Under the current operation mode of railway, the contradiction between the robustness of stage plan and the arrival time of inbound trains becomes increasingly intense. To improve the robustness of the stage plan, this paper addresses the problem of optimizing the marshalling station stage plan with the random arrival time of the inbound trains (compared to the arrival time of inbound trains of schedule) by stochastic programming methods. A dependent-chance programming model is developed with the object function to maximize the probability of keeping the stage plan feasible under the fluctuation of inbound train’s arrival time. Then, a hybrid intelligent algorithm based on stochastic simulation and tabu search is presented in the paper. The numerical experiments show that the algorithm can converge within a short time and the dependent-chance programming can produce a more robust stage plan and improves the decisino basis of the computer-aided dispatching plan.

Key words: railway transportation, marshalling station, stage plan, stochastic dependent-chance programming, hybrid intelligent algorithm, robustness