Integrated timetable synchronization optimization with capacity constraint under time-dependent demand for a rail transit network

摘要

The synchronization of train timetables is an important part of the operation of a rail transit network. Due to the well-designed synchronization of train timetables, passengers can make a smooth transfer without waiting a long time. Most of the current timetable synchronization researches didn't consider the non-transfer passengers, time-dependent demand and train capacity simultaneously. In order to extend the literature, this paper proposes a mixed-integer programming model under time-dependent demand to minimize passenger total waiting time and the number of passengers who fail to transfer. Train capacity is also considered in the model. Besides, this paper linearizes non-linear constraints to make sure the model can be solved by CPLEX. Genetic algorithm (GA) and grey wolf optimizer (GWO) are designed to solve the large-sized instance. In order to demonstrate the performance of the proposed method and algorithm, the numerical test is solved by CPLEX, GA and GWO and the optimization results are compared. Finally, a real-world case study based on the Shenyang rail transit network is applied to validate the proposed model. Optimization results show that compared with actual timetable, the performance of the proposed model is better. Non-transfer passenger waiting time, transfer passenger waiting time at origin stations, transfer waiting time and the number of passengers who fail to transfer are decreased by 3.7%, 1.9%, 26.3% and 8.6% respectively. Moreover, the performance of the proposed model is better than both non-synchronization and narrow synchronization model.