The Optimization Research Of Wagon-Flow Allocation In Stage Plan For Railway Marshalling Station

Marshaling stations are the primary units of the railway network, and the key nodes of the rail hub and the main rail lines. The mainly works of marshaling stations are handling the classification and assembly of freight trains, and making sure the trains are departed on time according to the departure schedule. Those yards operations are all planed by yards dispatcher, and the making and optimization of marshalling station stage plan is also an important part of station operation plan, which main content is to decide the marshalling structure and the sources of wagon-flow on departure trains, which is also called wagon-flow allocation problem. There are many uncertainties on the process of wagon-flow allocation for the stage plan, which were rarely considered on the present studies or discussed through the rigid optimization method. And it is not highlighted to the study on the model and arithmetic of wagon-flow allocation for the stage plan under the uncertain condition.Firstly, according to research trend and features of stage plan for railway marshalling station, the current situation as well as the characteristics and difficulties of the wagon-flow allocation in stage plan are reviewed and depicted on this paper. The reviews are based on four aspects, such as yard engines utilization, yard track utilization, and the optimization of wagon-flow allocation under certain and uncertain environment.Secondly, the uncertainties on the process of wagon-flow allocation for the stage plan are analyzed and optimized with the related mathematical theory and method. It is discussed on four aspects, such as the arrival time, train traffic information, break-up and marshalling operation time.Thirdly, a mathematical programming model is constructed for the main purpose to maximize the total number of the departure trains' priorities and the secondary purpose to minimize the total price of traffic flow connection and distribution in stage, equalize the waiting time distribution of arrival train under the uncertainty, on which the constraint conditions of models are comprehensively discussed on five aspects, such as the break-up time, the marshalling operation time, the departure time, the traffic flow connection and distribution and the capacity of railway yards.Then, based on the theory of constraint programming cumulative scheduling and lexicographic multi-objective optimization, a lexicographic multi-objective cumulative scheduling model is built through the conversion from the mathematical programming model, which includes two types of constraint conditions. One is expressed through the logical constraints, which include operational logic, priority between operations, traffic flow connection and size limitations, and the other is expressed through the resource capacity limitation constraints of cumulative scheduling, which include arriving yard, departure yard, marshalling yard, hump constraint and so on. Lexicographic multi-objective functions are based on the objective functions of mathematical programming model.Finally, a hybrid algorithm of constraint programming and multi-point constructive searching is designed to the model, which is calculated by the Java program based on the traffic flow data of one stage in Wuchang south marshalling station. The numerical case is used to verify the efficiency and accuracy of the model and algorithm.