Model And Solve The Wagon-flow Allocation In Marshalling Yard

The 14 th Five-Year Plan states the transport of bulk and medium-distance goods which is changed from road to railway should be accelerated.Therefore the pressure of freightage of railway increases today,peration and organizatiional capacity of the marshalling yard has a significant impact on the transport capacity of the whole railway network.Optimizing the wagon-flow allocation problem of the marshalling yard operation has an important influence on improving the transport efficiency of the railway network and promoting the railway informatization.An integer programming model with the maximum number of wagons sent from the marshalling yard to the interval is modeled in this thesis by considering the time continuity constraints,group content constraints and full loaded constraints.For the solution of the model,Static and dynamic wagon-flow allocation problems are regarded as two-layer planning problems,and the upper and lower levels are solved jointly.the static and dynamic wagon-flow allocation problems are optimized respectively.Static wagon-flow allocation is actually a large-scale linear programming problem.For this feature,the D-W decomposition and coordination algorithm is used to solve this problem and effectively reduces the scale of variables and constraint matrices during solving.Dynamic wagon-flow allocation is mainly about adjusting the disintegration order of the arrival train.An improved genetic algorithm is used in the thesis.The initial population is selected based on the corresponding disintegration interval of each departure train.The selection operator considers the acceptance of inferior solutions when copying chromosomes as the number of iterations increases by introducing the Metropolis criterion.The crossover operator considers the fitness of the individual.Probability of individuals being selected as the parent chromosome is different with different fitness.The function of fitness of genetic algorithm is the result of D-W decomposition and coordination algorithm.Therefore,the dynamic wagon-flow allocation problem based on the improved genetic algorithm has evolved into the cooperative optimization problem of static distribution and disintegration order.In the case analysis,the population size and parameters is analyzed perturbly.Based on the perturbation results,the results before and after the improvement of genetic algorithm has been analyzed.It is found that the convergence rate is much greater after improved genetic algorithm and falling into a local optimal solution has a lower possibility.The results show that the algorithm in this thesis can effectively solve the allocation problem of marshalling yard.