Abstract
Purpose This paper aims to reschedule the freight train timetable in case of disturbance to restore the train services as soon as possible. Design/methodology/approach Hence, an integer linear programming model for the real-time freight heavy-haul railway traffic management is developed in case of large primary delays caused by the delayed cargos loading. The proposed model based on the alternative graph at the microscopic level depicts the freight train movements in detail. Multiple dispatching measures such as re-timing and re-ordering are taken into account. Moreover, two objective functions, namely, the total final delays and the consecutive delays, are minimized in the freight trains dispatching problem. Findings Finally, a real-world computational experiment based on the Haolebaoji-Ji’an freight heavy-haul railway is implemented. The results of all disrupted cases are obtained within 10 s. The results give insight into that the consecutive delays are more than the total final delays when the same disrupted situation and the consecutive or total final delays increase as the primary delays increase. Originality/value An integer linear programming model based on the alternative graph for the real-time freight heavy-haul railway traffic management is developed in case of large primary delays caused by the delayed cargos loading. The method can be developed as the computer-aided tool for freight train dispatchers.
Highlights
This paper forms part of special section “Intelligent Technology and Application of Freight Railway”, guest edited by Jiansheng Zhu, Ruimin Wang and Peng Xie
The freight railway industry has been essential to society and economy, as it transports the strategic goods such as grain, coal and ore
The results give insight into that the consecutive delays are more than the total final delays when the same disrupted situation, and the consecutive or total final delays increase as the primary delays increase
Summary
© Yaqin Zhang, Mingming Wang, Ruimin Wang, Zhipeng Li and Nan Zhang. The full terms of this licence maybe seen at http://creativecommons.org/licences/by/4.0/legalcode. This paper forms part of special section “Intelligent Technology and Application of Freight Railway”, guest edited by Jiansheng Zhu, Ruimin Wang and Peng Xie
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