An exact method for real-time rescheduling after disturbances in metro lines

Research output: Contribution to conferencePaper

6 Downloads (Pure)

Abstract

This study proposes an exact model for timetable recovery after disturbances. Our model is applicable to high frequency services that operate under frequencies of at least 5 trips per hour. The objective of our model is the minimization of the deviation between the actual headways and their planned (target) values - a typical objective in high frequency services that indicates the service regularity. In the formulation of the timetable recovery model, we focus on metro lines with stable dwell times at stations that are not sensitive to changes in passenger demand. The resulting model is nonlinear and non-smooth; thus, it cannot be solved to optimality. To rectify this, we propose a model reformulation using slack variables. The reformulated program is equivalent to the original one and can be solved to global optimality in real time with exact optimization methods for quadratic programming. With our model, we investigate how many upstream trips should be rescheduled to respond to a service disturbance using real data from the red metro line inWashington D.C. Our experiments demonstrate an improvement potential of the service regularity by up to 30% if we reschedule the five upstream trips of a disrupted train.
Original languageEnglish
Number of pages21
Publication statusPublished - Jan 2020
EventTransportation Research Board (TRB) 99th Annual Meeting - Walter E. Washington Convention Center, Washinton, United States
Duration: 12 Jan 202016 Jan 2020
Conference number: 99
http://www.trb.org/AnnualMeeting/AnnualMeeting.aspx

Conference

ConferenceTransportation Research Board (TRB) 99th Annual Meeting
Abbreviated titleTRB 2020
CountryUnited States
CityWashinton
Period12/01/2016/01/20
Internet address

Fingerprint

Recovery
Quadratic programming
Experiments

Cite this

Gkiotsalitis, K., Eikenbroek, O. A. L., & Cats, O. (2020). An exact method for real-time rescheduling after disturbances in metro lines. Paper presented at Transportation Research Board (TRB) 99th Annual Meeting, Washinton, United States.
Gkiotsalitis, Konstantinos ; Eikenbroek, Oskar Adriaan Louis ; Cats, Oded. / An exact method for real-time rescheduling after disturbances in metro lines. Paper presented at Transportation Research Board (TRB) 99th Annual Meeting, Washinton, United States.21 p.
@conference{a16c5aff0d7541e38dd4a11cd6ce2cde,
title = "An exact method for real-time rescheduling after disturbances in metro lines",
abstract = "This study proposes an exact model for timetable recovery after disturbances. Our model is applicable to high frequency services that operate under frequencies of at least 5 trips per hour. The objective of our model is the minimization of the deviation between the actual headways and their planned (target) values - a typical objective in high frequency services that indicates the service regularity. In the formulation of the timetable recovery model, we focus on metro lines with stable dwell times at stations that are not sensitive to changes in passenger demand. The resulting model is nonlinear and non-smooth; thus, it cannot be solved to optimality. To rectify this, we propose a model reformulation using slack variables. The reformulated program is equivalent to the original one and can be solved to global optimality in real time with exact optimization methods for quadratic programming. With our model, we investigate how many upstream trips should be rescheduled to respond to a service disturbance using real data from the red metro line inWashington D.C. Our experiments demonstrate an improvement potential of the service regularity by up to 30{\%} if we reschedule the five upstream trips of a disrupted train.",
author = "Konstantinos Gkiotsalitis and Eikenbroek, {Oskar Adriaan Louis} and Oded Cats",
year = "2020",
month = "1",
language = "English",
note = "Transportation Research Board (TRB) 99th Annual Meeting, TRB 2020 ; Conference date: 12-01-2020 Through 16-01-2020",
url = "http://www.trb.org/AnnualMeeting/AnnualMeeting.aspx",

}

Gkiotsalitis, K, Eikenbroek, OAL & Cats, O 2020, 'An exact method for real-time rescheduling after disturbances in metro lines' Paper presented at Transportation Research Board (TRB) 99th Annual Meeting, Washinton, United States, 12/01/20 - 16/01/20, .

An exact method for real-time rescheduling after disturbances in metro lines. / Gkiotsalitis, Konstantinos ; Eikenbroek, Oskar Adriaan Louis; Cats, Oded.

2020. Paper presented at Transportation Research Board (TRB) 99th Annual Meeting, Washinton, United States.

Research output: Contribution to conferencePaper

TY - CONF

T1 - An exact method for real-time rescheduling after disturbances in metro lines

AU - Gkiotsalitis, Konstantinos

AU - Eikenbroek, Oskar Adriaan Louis

AU - Cats, Oded

PY - 2020/1

Y1 - 2020/1

N2 - This study proposes an exact model for timetable recovery after disturbances. Our model is applicable to high frequency services that operate under frequencies of at least 5 trips per hour. The objective of our model is the minimization of the deviation between the actual headways and their planned (target) values - a typical objective in high frequency services that indicates the service regularity. In the formulation of the timetable recovery model, we focus on metro lines with stable dwell times at stations that are not sensitive to changes in passenger demand. The resulting model is nonlinear and non-smooth; thus, it cannot be solved to optimality. To rectify this, we propose a model reformulation using slack variables. The reformulated program is equivalent to the original one and can be solved to global optimality in real time with exact optimization methods for quadratic programming. With our model, we investigate how many upstream trips should be rescheduled to respond to a service disturbance using real data from the red metro line inWashington D.C. Our experiments demonstrate an improvement potential of the service regularity by up to 30% if we reschedule the five upstream trips of a disrupted train.

AB - This study proposes an exact model for timetable recovery after disturbances. Our model is applicable to high frequency services that operate under frequencies of at least 5 trips per hour. The objective of our model is the minimization of the deviation between the actual headways and their planned (target) values - a typical objective in high frequency services that indicates the service regularity. In the formulation of the timetable recovery model, we focus on metro lines with stable dwell times at stations that are not sensitive to changes in passenger demand. The resulting model is nonlinear and non-smooth; thus, it cannot be solved to optimality. To rectify this, we propose a model reformulation using slack variables. The reformulated program is equivalent to the original one and can be solved to global optimality in real time with exact optimization methods for quadratic programming. With our model, we investigate how many upstream trips should be rescheduled to respond to a service disturbance using real data from the red metro line inWashington D.C. Our experiments demonstrate an improvement potential of the service regularity by up to 30% if we reschedule the five upstream trips of a disrupted train.

M3 - Paper

ER -

Gkiotsalitis K, Eikenbroek OAL, Cats O. An exact method for real-time rescheduling after disturbances in metro lines. 2020. Paper presented at Transportation Research Board (TRB) 99th Annual Meeting, Washinton, United States.