Optimization of Dynamic Dispatching Decision of Transferring Wagon-Flows in Terminal with IRTS Based on Uncertainties

The dispatching decision of wagon-flows in railway terminal is a complex producing system that consists of a number of subsystems. The dispatching of wagon-flows in the system is a non-linear complex problem, involving many uncertainties. According to the sources of uncertainties, combined with the ideas and principles of the wagon flows dispatching decision in railway terminal, the problem that the uncertainties outside terminal system have impact on the dispatching decision of transferring wagon-flows is studied. A stochastic chance-constrained programming model is built. For the timeliness requirements for dynamic dispatching and the characteristics of the model, a hybrid intelligent algorithm is presented combined the improved genetic algorithm and artificial neural networks. The concrete steps to solve the problem are present.