Abstract
The task of periodic timetabling is to determine trip arrival and departure times in a public transport system such that travel and transfer times are minimized. This paper investigates periodic timetabling models with integrated passenger routing. We show that different routing models can have a huge influence on the quality of the entire system: Whatever metric is applied, the performance ratios of timetables w.r.t. different routing models can be arbitrarily large. Computations on a real-world instance for the city of Wuppertal substantiate the theoretical findings. These results indicate the existence of untapped optimization potentials that can be used to improve the efficiency of public transport systems by integrating passenger routing.
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Borndörfer R, Grötschel M, Pfetsch ME (2007) A column-generation approach to line planning in public transport. Transp Sci 41(1):123–132. http://opus.kobv.de/zib/volltexte/2005/852/, ZIB Report 05-18
Borndörfer R, Karbstein M (2012) A direct connection approach to integrated line planning and passenger routing. In: Delling D, Liberti L (eds) ATMOS 2012—12th workshop on algorithmic approaches for transportation modelling, optimization, and systems, vol 25, pp 47–57. doi:10.4230/OASIcs.ATMOS.2012.47
Fu Q, Liu R, Hess S (2012) A review on transit assignment modelling approaches to congested networks: a new perspective. Proc Soc Behav Sci 54:1145–1155
Kinder M (2008) Models for periodic timetabling. Diploma thesis, Technische Universtität Berlin
Liebchen C (2006) Periodic timetable optimization in public transport. Ph.D. thesis, Technische Universtität Berlin. http://www.dissertation.de
Lindner T (2000) Train schedule optimization in public rail transport. Ph.D. thesis, Technische Universtität Braunschweig
Lübbe J (2009) Passagierrouting und Taktfahrplanoptimierung. Diploma thesis, Technische Universtität Berlin
Nachtigall K (1998) Periodic network optimization and fixed interval timetables. Ph.D. thesis, Deutsches Zentrum für Luft- und Raumfahrt, Institut für Flugführung, Braunschweig
Schmidt M (2012) Integrating routing decisions in network problems. Ph.D. thesis, Universität Göttingen
Schmidt M, Schöbel A (2014) Timetabling with passenger routing. OR Spectrum, pp 1–23. doi:10.1007/s00291-014-0360-0
Schöbel A, Scholl S (2006) Line planning with minimal traveling time. In: Kroon LG, Möhring RH (eds) 5th workshop on algorithmic methods and models for optimization of railways (ATMOS’05), Schloss Dagstuhl–Leibniz-Zentrum fuer Informatik, Dagstuhl, OpenAccess Series in Informatics (OASIcs), vol 2. doi:10.4230/OASIcs.ATMOS.2005.660, http://drops.dagstuhl.de/opus/volltexte/2006/660
Sels P, Dewilde T, Cattrysse D, Vansteenwegen P (2016) Reducing the passenger travel time in practice by the automated construction of a robust railway timetable. Transp Res Part B Methodol 84:124–156. doi:10.1016/j.trb.2015.12.007
Serafini P, Ukovich W (1989) A mathematical model for periodic scheduling problems. SIAM J Discrete Math 2(4):550–581
Siebert M, Goerigk M (2013) An experimental comparison of periodic timetabling models. Comput Oper Res 40(10):2251–2259
van der Hurk E, Kroon L, Marti G, Vervest P (2013) Deduction of passengers’ route choice from smart card data. In: 2013 16th international IEEE conference on intelligent transportation systems (ITSC), pp 797–802. doi:10.1109/ITSC.2013.6728329
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We thank the editors and two anonymous referees for valuable suggestions that improved the presentation of this paper.
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This research was carried out in the framework of Matheon supported by Einstein Foundation Berlin.
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Borndörfer, R., Hoppmann, H. & Karbstein, M. Passenger routing for periodic timetable optimization. Public Transp 9, 115–135 (2017). https://doi.org/10.1007/s12469-016-0132-0
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DOI: https://doi.org/10.1007/s12469-016-0132-0