Integrated optimization of Rolling Stock and Crew Rescheduling for High Speed Railway

Abstract

The integrated rescheduling problem of rolling stock and crew for the high speed railway network is challenging, especially during the real-time disruption management process. In order to tackle this problem, an integer linear programming model is presented, based on a multi-commodity flow model, which integrates the rolling stock and crew rescheduling process. The objective of the integrated model is to minimize the difference between the adjusted and original schedule and reduce the cancellations of trips caused by the shortage of rolling stocks or crews. In case of disruptions, a customized ant colony algorithm is presented to solve the problem efficiently. We test our approach on an instance of Beijing-Shanghai high-speed railway line. The calculation results show that the optimal solution can be generated within a short computational time with little RAM consumption. By rescheduling the rolling stock and crew simultaneously, this work helps to effectively support real-time operation under strict time limitations.