The multimodal and multiperiod urban transportation integrated timetable construction problem with demand uncertainty

Abstract

The urban transport planning process has four main activities: Network design, Timetable construction, Vehicle scheduling and Crew scheduling; each activity has subactivities. In this paper the authors work with the subactivities of timetable construction: minimal frequency calculation and departure time scheduling. The authors propose to solve both subactivities in an integrated way. The developed mathematical model allows multi-period planning and it can also be used for multimodal urban transportation systems. The authors consider demand uncertainty and the authors employ fuzzy programming to solve the problem. The authors formulate the urban transportation timetabling construction problem as a bi-objective problem: to minimize the total operational cost and to maximize the number of multi-period synchronizations. Finally, the authors implemented the SAUGMECON method to solve the problem.

Bus scheduling considering trip‐varying travel times, vehicle availability and capacity

“…A distinct line of works has proposed the simultaneous optimisation of bus frequencies and timetables [19–22]. Other works, such as [23, 24], tried to determine simultaneously the route network design, the bus frequencies, and the timetable assignment by integrating the strategic and tactical planning phases.…”

Robust timetable optimization for bus lines subject to resource and regulatory constraints

“…A distinct line of works has proposed the simultaneous optimization of the route network design, the frequency setting, and the timetabling problems (Yan et al, 2006;Zhao and Zeng, 2008). Other works, such as Furth and Wilson (1981); Gallo and Miele (2001); Peeters and Kroon (2001) and Ávila-Torres et al (2017), proposed the simultaneous optimization of bus frequencies and timetables. Contrary to the above, most works on timetable optimization, such as Sun et al (2015); Wang et al (2017) and Yu et al (2017), decouple the frequency settings problem from the timetabling problem and solve them in sequential order.…”

Reliable bus dispatching times by coupling Monte Carlo evaluations with a Genetic Algorithm

“…Several works have jointly addressed the bus frequency settings problem and the bus timetabling problem [11], [12], [13], [14], [15]. Nevertheless, in most cases the optimization of the timetable of a bus line is perceived as a standalone problem and is generally decoupled from the from the frequency settings problem [16], [17], [18].…”