Research On Empty Vehicle Scheduling Theory Of Rail Network

The ideal process of transport services is to send the goods to the destination and obtain the best value using the shortest time and the least capacity, taking the least link and the minimum mileage and spending the least cost. However, in the organizations of the actual transportation, the improper planning will result in transporting capacity wasting, transporting time increasing and the total freight cost overrunning. The empty driving in return and depart are the serious form of improper transportation. Therefore, minimizing the empty driving costs and improving its efficiency is one of the most effective means to realize the ideal transport service. Currently, the rail transport system has been improved and the road transport is widly distributing, so it is suitable to use the combined transportion to carry out a social transportation system in the form of of diversion of highway and rail with short-distance transport. In this paper, after integrating the rail and road transport, a rail transport network which is suitable for the combined transportion is proposed. It has important practical value and significance to the research of the the empty scheduling theory.This paper analyses the various forms of domestic and foreign vehicle scheduling problem under the present situation and sums up the two core issues of the empty driving scheduling problems which need to be resolved. The empty driving scheduling of the rail transport network is also researched. First, the system theory of empty driving scheduling in the rail transport network is established; the reason of the empty vehicle generation and the core problem needs to be sloved is analysed. Through the neural network model and using multi-objective genetic algorithm to optimize the ways, the network empty demand forecast solution is deduced. Second, in combination the empty scheduling method in other transport systems, build the harmonious and optimal path selection and the distribution of the multi-objective empty vehicle scheduling optimization model. Then, the solving optimization to this multi-objective nonlinear mixed programming model is attempted. Empty scheduling model will be devided into two subsystems in order to find the slution by using the expert system. At the first level, the selection of the determined subsystem for the path is founded. At the second level, the capacity constraints will be used as the coupler between the assigned two subsystems. According to the idea of decoupling, the hybrid optimization model is translated equally into two sub-models, which are respectively based on the theory of multi-objective linear programming and balanced transportation problem.According to the characteristics of the model, the multi-objective genetic algorithm which has good effect in solve the multi-objective optimization problem, is used to solve the model, and to design the network and its related parameters. Through the analysis in conditions of different parameters, the solution of the model is obtained, which can provide theoretical basis for the research in empty vehicle scheduling theory of rail network.