The Optimization Research Of Unloading Organization In Heavy Haul Transport

"Loading"、"Transport" and "unloading" are three links of railway heavy transport which have mutual influence and independence. The relationship between each link and system is similar to the buckets effect. Only three subsystems match each other, can the system achieve optimal capability. Distribution system has been in a weak position for a long time, which resulting in its ability lag the other two subsystem, limiting the overall system. Distribution system is based on unloading organization. Improving the capacity of distribution system by doing the research of unloading organization optimization can match the other two subsystem, which has positive significance. It takes unloading operating system of heavy haul railway as the research objective and combines Job-shop scheduling problem and the theory of combinatorial optimization problems. In Summary, it optimizes the unloading scheduling and achieves good results.Firstly, it introduces the content and features of collection and distribution system of heavy haul railway and analyzes its development process. And it points out the weakness of the system. Then it introduces the equipment of unloading and analyzes the layout of the unloading station and compares the similarities and differences with ordinary unloading station.Secondly, based on the description of process of unloading and the analysis of the feature and effective factors, it point out the problems of unloading scheduling system. When the train arrive uneven, resulting in focused arrive, if the allocation is not good, train will have a lot of time waiting to be unloaded. Reasonable allocation will greatly reduce the waiting time. This problem is similar to the Parallel machine model. Based on the feature of problem, it establishes an optimal model. The objective function of the model is to make the total time of the trains at the station min. The model is a multi-constrained, nonlinear, single goal, integer programming.Finally, based on the features of the model, it designs a genetic algorithm model. With a population initialization method based on time preference, it improves the convergence rate. To avoid falling into local optimal and precocity, it narrows the fitness function with Scaling exponent. It use roulette and elitist method as select operator and evolutionary strategy based on hybrid crossover operator. The algorithm not only improves the search speed, and avoids the premature phenomenon. Besides, it write the corresponding matlab program. Taking the 4 hours stage plan of unloading scheduling of liucunnan station for example, it verifies the effectiveness of the algorithm.The model can make the unloading more reasonable, model algorithm can get the solution quickly and meet the characteristics of time-sensitive for transportation. The work can provide a reference for unloading intelligent scheduling system.