Abstract
Train timetables are usually established far in advance of operations and are based on forecasted demands. However, due to changes in actual freight traffic, railways need to determine the actual operation of trains arising in daily operations through train path selection, i.e., selecting a portion of the timetable for these trains to execute. To improve current freight train scheduling in daily operations, this paper suggests taking into account the car flow transfer between consecutive trains and shipment delivery time requirements. A train path selection optimization model is developed to minimize the total travel time of freight trains while seeking minimum penalties for shipment delivery delays. A tabu search algorithm is designed to solve this problem. The effectiveness of the proposed model and algorithm is demonstrated by numerical experiments on instances built on real data from the Menghua railway, a rail freight corridor. The results show that, compared to current practice, this optimization method can achieve a reduction in total train travel time and ensure the punctual delivery of shipments.
Highlights
During the last two decades, the high-speed railway has been ushering in rapid development with massive construction of passenger-dedicated lines
To further evaluate the performance of the proposed algorithm, we generated a larger instance and tested it when there is car flow transfer between trains. This instance is based on the full-capacity timetable and contains 530 train paths, 152 trains, and 365 car flows, where 29 car flows need to transfer between trains
It can be concluded that the proposed algorithm can be used for freight train scheduling in large-scale practical applications even when there is car flow transfer between trains
Summary
During the last two decades, the high-speed railway has been ushering in rapid development with massive construction of passenger-dedicated lines. Considerable track capacities have been released in existing lines, providing favorable conditions for developing freight transportation. This motivates this paper to seek optimization methods for freight train scheduling, which is a crucial operating decision. An improved train schedule can decrease operation costs and enhance customer service. As different national freight rail transportation systems have their own characteristics regarding management structure and operation conditions, the planning and executing process of freight train timetables varies from one country to another. We primarily address the train scheduling problem of Chinese freight railway
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