Abstract
Electric Multiple Unit (EMU) high-level maintenance planning is a typical discrete system. EMU high-level maintenance (HM) planning determines when to undergo HM or execute transportation task for train-sets, based on practical requirements such as passenger transport demand, workshop maintenance capacity, and maintenance regulations. This research constructs a time-state network that can display the transformation processes between different states. On this basis, a path based model and its improvement are developed to minimize the HM costs with consideration of all necessary regulations and practical constraints. To handle the solution space, a path set generation method is presented. A real-world instance from Shanghai Railway, which is the largest affiliate in China Railway Corporation, was conducted to demonstrate the efficiency and effectiveness of the proposed approach, which indicates that the model can be solved to optimum within short computational times by the state-of-the-art solver Gurobi. Moreover, a sensitivity analysis was also performed to evaluate the effects of the variation in average daily operating mileage, HM capacity at the depot and the assumed minimum value of cumulative mileage.
Highlights
According to the statistical bulletin of National Railway Administration of the People’s Republic of China, the railway passenger traffic volume reached 357 million during the Spring Festival TravelRush in 2017, among which people travelling by high-speed rail accounts for 51.4%
The high-level maintenance plan (HMP) must be considered in advance by the management because it requires a long time for the maintenance procedures, and the workshop has limited capacity, and it is scheduled once a year
It is an important objective pursued by a railway operator to supply enough available electric multiple unit (EMU) train-sets for passenger transport demand and to reduce the major maintenance costs
Summary
According to the statistical bulletin of National Railway Administration of the People’s Republic of China, the railway passenger traffic volume reached 357 million during the Spring Festival Travel. 0-1 integer programming model and its improvements were proposed to reduce the costs of HM with consideration of all necessary regulations and practical constraints, especially for the passenger transport peak demand; (2) Taking into account the practice constraints, we constructed a time-state network for optimizing HMP; (3) the generation method of the path set was presented to solve the mathematical model effectively and efficiently by controlling the solution space.
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