Train timetabling at rapid rail transit lines: a robust multi-objective stochastic programming approach

In the setting of public transportation system, improving the service quality as well as robustness against uncertainty through minimizing the total waiting times of passengers is a real issue. This study proposed robust multi-objective stochastic programming models for train timetabling problem in...

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Bibliographic Details
Published in:Operational research Vol. 17; no. 2; pp. 435 - 477
Main Authors: Hassannayebi, Erfan, Zegordi, Seyed Hessameddin, Amin-Naseri, Mohammad Reza, Yaghini, Masoud
Format: Journal Article
Language:English
Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.07.2017
Springer Nature B.V
Subjects:
Business and Management
Computational Intelligence
Cost function
Management Science
Operations Research
Operations Research/Decision Theory
Original Paper
Passengers
Public transportation
Rapid transit systems
Robustness
Stochastic models
Stochastic programming
Transportation systems
Travel demand
Underground railways
Urban rail
Urban rail
Uncertain demand
Robust multi-objective stochastic programming
Train timetabling
ISSN:1109-2858, 1866-1505
Online Access:Get full text
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Summary:In the setting of public transportation system, improving the service quality as well as robustness against uncertainty through minimizing the total waiting times of passengers is a real issue. This study proposed robust multi-objective stochastic programming models for train timetabling problem in urban rail transit lines. The objective is to minimize the expected value of the passenger waiting times, its variance and the penalty cost function including the capacity violation due to overcrowding. In the proposed formulations, the dynamic and uncertain travel demand is represented by the scenario-based time-varying arrival rates and alighting ratio at stops. Two versions of the robust stochastic programming models are developed and a comparative analysis is conducted to testify the tractability of the models. The effectiveness of the proposed stochastic programming model is demonstrated through the application to line 5 of Tehran underground railway. The outcomes validate the benefits of implementing robust timetables for rail industry. The computational experiments shows significant reductions in expected passenger waiting time of 21.27 %, and cost variance drop of 59.98 % for the passengers, through the proposed robust mathematical modeling approach.
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ISSN:1109-2858
1866-1505
DOI:10.1007/s12351-016-0232-2