Integrated Optimization of Stop Planning and Timetabling for Demand-Responsive Transport in High-Speed Railways

Abstract

The high-speed railways have made rapid developments in recent years. Fulfilling passenger demand and providing precise train services are the core problems to be solved in railway operation. This paper proposes an optimization strategy for demand-responsive transport to integrate train-stop planning and timetabling in high-speed railways. Passenger travel information, including their origins, destinations and expected departure times is taken as input. A mixed integer linear programming model is established to obtain an effective service plan, which consists of train stop pattern, passenger ride plan and train arrival/departure times at all stations. The optimization objective is to minimize the remaining passenger demand and train travel time. Finally, the proposed method is applied to a real-world case, and a series of several experiments are conducted to prove the efficiency and validity of the proposed model. The results suggest that the proposed approach could generate efficient service plans which are responsive to passenger demand.

A Two-Level Fuzzy Multi-Objective Design of ATO Driving Commands for Energy-Efficient Operation of Metropolitan Railway Lines

“…Other methods involve using the ε-constraint method and applying multi-objective optimization with distance-based methods [27]. Several mixed-integer programming models have been proposed to solve the scheduling problem for single-track railways [28], to integrate train-stop planning and timetabling in high-speed railways [29], to solve the timetable and train-set circulation plans in transition times for high-speed lines [30], to solve the problem of multiperiodic train timetabling and routing high-speed trains at stations [31], to integrate the line planning, timetable and rolling stock allocation problem [32], to integrate the timetable problem with passengers' train booking decisions [33], and to solve the schedules of trains on a railway network to determine the best stop locations for both technical and religious services [34]. Passenger waiting time has also been included in optimization [35] by treating passenger behaviour as deterministic.…”