铁路枢纽双编组站静态配流协同优化研究

Collaborative Optimization of Static Flow Allocation in Double Marshalling Stations of Railway Hub

枢纽内跨编组站进行协同配流有助于优化枢纽内的车流接续,提高全局配流质量。引入跨编组站协同配流思想,构建铁路枢纽双编组站静态配流协同优化模型,以最小化双编组站的配流总代价、最大化双编组站的总满轴列车数为优化目标,考虑车流量约束、列车到解编发作业与枢纽小运转列车走行的接续时间约束、出发列车满轴与不违编约束、调机资源使用约束。以列车等级、编组去向数及出发时刻排序作为配流代价。设计理想点算法将多目标转化为单目标进行求解,最后运用算例对模型及算法的有效性进行验证。结果表明,双编组站联合配流相较于两编组站单独配流,可使满轴列车总数增加1列、站存车总数减少13辆、配流总代价降低5.4%,从而达到更佳的配流效果。

Collaborative flow allocation across marshalling stations in the hub helps optimize the wagon flow connection and improve the overall quality of flow allocation.The idea of collaborative flow allocation across marshalling stations was introduced.This paper built a collaborative programming model for static wagon-flow combined allocation of double marshalling stations in the hub,aiming to minimize the total cost of the double marshalling stations and maximize the total number of full-axle trains in the double marshalling stations.This model considered the constraints of wagon flow volume,time of trains’arrival,breaking-up,marshalling,departure,and the junction terminal transfer trains’running time.The constraints of the loading limit of departure trains and the use of shunting locomotives were also involved in the model.The paper took train rank,number of directions,and departure time ranking as the cost of wagon flow allocation.The ideal point algorithm was designed to solve the problem,which transformed multiple objects into a single object.Finally,the validity of the model and algorithm was verified by an example.The results show that the wagon-flow combined allocation of double marshalling stations can increase the total number of full-axle trains by 1,reduce the total number of cars stored in the station by 13,and reduce the total cost of allocation by 5.4%compared with the separate allocation of two marshalling stations,achieving a better allocation effect.