Optimizing the Utilization Plan of CRH-Emu with Particle Swarm Algorithm

Abstract

China Railway High-speed is expanding dramatically recently. The utilization plan of China Railway High-speed Electric Multiple Unit (CRH-Emu) train plays the basic role in the routine transportation organization of high-speed railway. Because the plan is interacted with CRH-Emu's off-line repair plan and influenced by many other factors, it is a rather complicated task for CRH-Emu Depot to schedule it manually. In order to obtain optimal long-term solution to instead manual operation, this paper established an integer model, with balancing CRH-Emu’s future repair workload as the objective function, and with the transportation demand, off-line repair regulation, and depot's repair capacity as the constraints. By separating the mutual influencing factors between on-line utilization and off-line repair plans, the original problem became easier to resolve. The particle swarm optimization algorithm was applied to solve the model. Furthermore, a testing example was given to testify the model and algorithm, and the result showed that the proposed method could obtain desirable solutions and assist CRH-Emu Depot to manipulate Emu’s daily organization.