Title :
Optimization of Dynamic Dispatching Decision of Transferring Wagon-Flows in Terminal with IRTS Based on Uncertainties
Author :
Hu Zuoan ; Yan Yusong ; Wang Maokui
Author_Institution :
Coll. of Traffic & Transp., Southwest Jiaotong Univ., Chengdu, China
Abstract :
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.
Keywords :
constraint handling; decision making; dispatching; genetic algorithms; large-scale systems; neural nets; railway industry; railway rolling stock; artificial neural network; complex producing system; dynamic dispatching optimization; genetic algorithm; hybrid intelligent algorithm; nonlinear complex problem; railway terminal; stochastic chance constrained programming model; wagon flows dispatching decision; Artificial intelligence; Artificial neural networks; Concrete; Dispatching; Genetic algorithms; Intelligent networks; Nonlinear dynamical systems; Rail transportation; Stochastic processes; Uncertainty; IRTS; railway terminal; uncertainty; wagon-flows organization;
Conference_Titel :
Information Management, Innovation Management and Industrial Engineering, 2009 International Conference on
Conference_Location :
Xi´an
Print_ISBN :
978-0-7695-3876-1
DOI :
10.1109/ICIII.2009.371
