Research On The Integrated Scheduling And Optimization Of Multiple Resources In A Container Transshipment Yard Of Railway Border Station

During the implementation of “The Belt and Road” initiative,China has become increasingly connected with countries along “The Belt and Road”,especially represented by the China Railway Express,which has greatly promoted the trade cooperation between China,Europe,and Asia.Under the background of increasing demand for international trade,the volume of imported containers in China also shows a trend of continuous rise.With the increase in freight volume,the shortage of storage capacity also limits the reloading capacity of border stations,which brings challenges to the reloading capacity of railway border stations that need reloading operations.In order to improve the container reloading capacity of border stations,it is necessary to make reasonable planning and utilization of the resources of the container transshipment yard.Based on this,this paper conducts in-depth research on the cooperative scheduling and optimization of space resources and loading and unloading equipment resources of container transshipment yards at railway border stations.The main contents and achievements of this paper are as follows:(1)This paper studies the cooperative scheduling and optimization of space resources and loading and unloading equipment resources in the container transshipment yard of the railway border station.Firstly,introduce the basic situation of the border station and determine the type of the border station studied in this paper.Secondly,the space resources and loading and unloading equipment resources of the container transshipment yard are analyzed in detail.Finally,analyze the integrated scheduling and optimization problem of space resources and loading and unloading equipment resources in container transshipment yard of railway border station,which provides the basis for the following research.(2)Construct a two-layer planning model for integrated scheduling and optimization of space resources and loading and unloading equipment resources of container transshipment yard at railway border station.The upper model is a resource scheduling optimization model for loading and unloading equipment that takes the minimum total time to complete loading and unloading operations by rail-mounted gantry cranes.The lower model is a space resource scheduling optimization model to minimize the number of stacked containers generated by the storage of incoming containers.The upper model and the lower model feedback each other through the loading and unloading operation sequence of the incoming container and the storage position so that the efficiency of the operating system in the container transshipment yard can be optimized.(3)Design a two-layer genetic algorithm to solve the model established in this paper.Through the analysis of the calculation example,the model and algorithm established in this paper are proved to be feasible,and the calculation results are compared with the results of individual scheduling optimization.The results show that integrated scheduling and optimization can effectively reduce the number of stacked containers generated by the incoming containers,and shorten the completion time of loading and unloading of rail-mounted gantry cranes.In addition,the influence of different arrival and departure times of wide and standard gauge trains on the integrated scheduling and optimization is analyzed.The results show that the simultaneous arrival of wide and standard gauge trains can effectively improve the efficiency of the transshipment operation,but the staggered arrival of wide and standard gauge trains can effectively shorten the detention time of trains in the container transshipment yard.This paper studies the operation optimization of the container transshipment yard of the railway border station,which is conducive to improving the efficiency of the container transshipment yard and providing theoretical support for the actual operation of the border station.This paper includes 40 figures,17 tables,and 64 references.