Combined Optimization Of Train Service Network Design And Division Of Work Of Two Systems Of The Same Marshaling Yard

Integrated optimizing the train service network design problem and the division of work of two systems of the same marshaling yard problem is one of the core tasks in railway operation. The optimal problem is to obtain railcar flow shipping strategy and railcar flow classification route in marshaling yard in a given network structure, while not exceeding line and yard capacity. The objective is seeks to minimize the sum of shipping, accumulating and classification costs. Researchers usually study the above two problems separated, seldom consider their inner link, lead to optimal result has limitations and adaptability. In the actual transportation process, intense interactions and mutual cooperation exist between the above two problems. When integrate the above two problem into a single optimization model or Hierarchical optimize them, we can set different classification fee for different classification routes, distinguish between different system capabilities and remark connection link miles. It can optimize between which pair of yards provides a direct train service, and the direct train service departure from which system of the start yard and arrive at which system of the end yard? Which car flow routed on this train service? In this method, the railroad can minimize angular wagon flow in bidirectional marshaling stations, improve the marshaling yard utilization, reduce the workload of marshaling yards, and balance the capacity utilization of the two-way system in the same marshaling yards. To sum up, considering the train service network design problem and the division work of two systems of the same marshaling yard problem together has the important practical significance.Based on the traffic organization theory and modern mathematical methods, this paper make more in-depth study in integrated optimizing the train service network design problem and the division work of two systems of the same marshaling yard problem. The main research content and results are as follows:(1) Compares and analyzes the railroad transport equipment conditions, organizational status and typical optimization models of North America, European region and China, and pointed out their respective advantages and disadvantages, and the scope of application.(2) Constructs train service design model preference long distance (TFP-c2). Base on the typical model (TFP-c) of China, the model introduce the train service frequency decision variable, and consider the unit train operation cost and the artificial and equipment cost incurred by the classification work in marshaling yard. Compare the optimal result between model TFP-c and model TFP-c2, it can found that the later can extended transport distance of train services, decrease the number of traffic transfer, release the workload of marshaling station, reduce the fleet size of equipment (locomotive and vehicle), and accelerated the delivery speed of the goods.(3) Establishes train service design model with train service frequency and linear tree route constraint (LTFP). Base on the typical model of Europe region, the model introduce car flow first classification station selection decision variable, linearization tree chain constraint and train frequency decision variable, which make the model suit our country railway transportation actual. Compare the optimal result between model TFP-c2and model LTFP, it can found that the later not only reduces the solution space, but also convenient for artificial participate in optimization process.(4) Designs three kinds of intelligent optimization algorithms (parallel tabu search algorithm, genetic algorithm based on niche technique, hybrid genetic algorithm based on the neighborhood search and niche technology) for solving TFP-c, TFP-c2and LTFP models. In order to validate the validity of the model and evaluate the performance of the three algorithms, the paper designs three different scale examples. the calculation result indicates that, in the small scale, the above three kinds of optimization algorithm all can get the global optimal solution with less time consume than accurate algorithm in Commercial solving software (Lingo11); When the example scale increase, Commercial solving software cannot obtain global optimal solution, and the computing time of local optimal solution is longer than that of optimization algorithm. In the view of solution quality, the hybrid genetic algorithm is better than the parallel tabu search algorithm, and the parallel tabu search algorithm is better than genetic algorithm. Comparing the solution result of TFP-c2model with different train dispatching cost, we can find that average train running distance is growing with the increasing cost. Compare the solution effect of intelligent optimization algorithms in model LTFP to in model TFP-c2, it can be found that the former model can greatly reduce solution space.(5) Proposes a hierarchical optimization method to determine between which pair of yards provides a direct train service, and the direct train service departure from which system of the start yard and arrive at which system of the end yard? The classification routes of cars between two systems of a marshaling yard. The up model is train service design model in which classification yard represent as a single node, rail tracks represent as lines, and the lower model is to determine classification routes of cars in a marshaling yard with two systems. In the optimal process, the optimal result of the up model can be used as input data to the lower model, the solution result of the lower can be as the supplement and adjustment of the upper model.This paper designs three types of the lower model, respectively:①In the arriving yard of a train service, the service is limited to access only one system of a marshalling station with two system in advance, in this condition, constructed a model for operation division of work of two systems in a marshaling yard.②In the arriving or departing yard of a train service, trains are not limited to out or access only one system in advance, in this condition, developed a model for operation division of work of two systems in a marshaling yard.③take multiple angular path of car flow classification route in bidirectional marshalling station, developed a model for operation division of work of two systems in a marshaling yard. Finally, using the intelligent optimization algorithms to solve the upper optimization model, and using the commercial software (lingo) solve to the second lower model, verify the hierarchical optimization method is feasible and the model design feasibility.(6) Constructs three different types of integrate models for a combined train service design and division of work of two system in a marshalling yard problem aiming at minimizing train service accumulated delay cost, classification cost and shipping cost in connection path in hub yard. The first two models are based on typical model of China, the former extend standard marshalling station with two systems to two nodes, the later extend Arbitrary structure marshalling station with two systems to several nodes, then consider the division of work of two system in a marshalling yard problem into train service design problem, constructed two type integrated models. The later has more extensive application scope than the former. The last one model is based on typical model of Europe, adding linear constraint of flow tree shipping chain which make the model suit the actual situation of China Railway system, simultaneous address the division of work of two system in a marshalling yard problem and train service design problem in railroad, developed another integrated model. The last one can reduce solution scope than the other two.Finally an example was presented to validate the feasibility and the consistency of the above three models. The results show that integration model can change car flow shipping strategy and avoid inevitable angle classification car flows obtaining from hierarchical optimization method, reduce the total number of angle classification cars, release the workload of marshaling yards and saving human resources investment.