Abstract
This study proposes a biobjective optimization method for timetable rescheduling during the end-of-service period of a subway network, taking all stakeholders’ interests into consideration. We seek to minimize the total transfer waiting time for all transfer passengers, meanwhile minimizing the deviation to the scheduled timetable. The ε-constraint method and linearization techniques are utilized to obtain the approximate Pareto optimal solutions within limited seconds, allowing for figuring out the trade-off between the two objectives. The method is validated by numerical experiments for different delay scenarios based on a real-world case: the Beijing subway network.
Highlights
There are several contributions to the last-train timetabling problem of a subway system, which focused only on the last train of each line in the network and expected to generate a more efficiently scheduled timetable for all last trains [1,2,3,4]
If the missed connecting train is the last train of the connecting line, the transfer waiting time of these transfer passengers equals the penalty time; see the following formula: tVw,Vait = tp, if V = Vl & xV,V = 0 (3)
The single-objective model obtained in Section 4.1 is converted into a single-objective integer linear programming (ILP) model with objective function (12) and linear constraints ((5)-(11)), ((14)-(16)), and ((18)-(21)), which can be solved by Cplex within limited seconds
Summary
There are several contributions to the last-train timetabling problem of a subway system, which focused only on the last train of each line in the network and expected to generate a more efficiently scheduled timetable for all last trains [1,2,3,4]. This study is devoted to the timetable rescheduling problem during a specific period: the end-of-service period. In order to deal with the disturbances occurring during the end-of-service period, the first contribution of this study is that a timetable rescheduling model is proposed from a stakeholder-oriented perspective with the consideration of benefits of both passengers and operating agencies.
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