Abstract
Economic and attractive operation of suburban railways can only be realised by flexibilisation of headways, adaptation of the network and capacity of the different lines. Under those circumstances, the computation of optimal operation programmes is very complex. This contribution presents a two-level approach (computation of transport offer, timetable design) and shows the results obtained from fully-automatic offer planning and timetabling for a suburban railway.
Similar content being viewed by others
References
Albrecht T (2004) Ein Beitrag zur Nutzbarmachung Genetischer Algorithmen für die optimale Steuerung und Planung eines flexiblen Stadtschnellbahnbetriebs. PhD thesis, Dresden University of Technology
Assis WO, Milani BEA (2004) Generation of optimal schedules for metro lines using model predictive control. Automatica 40:1397–1404
Ceder A (2001) Efficient timetabling and vehicle scheduling for public transport. In: Voß S, Daduna J (eds) Computer-aided scheduling of public transport. Springer, Brelin, pp 37–52
Cury J, Gomide F, Mendes M (1980) A methodology for generation of optimal schedules for an underground railway system. IEEE Trans Automat Contr 25(2):217–222
Daduna J, Schneidereit G, Voß S (2006) Passenger information systems in public mass transit: Where we are and where we go. In: Proceedings of the 10th international conference on computer-aided scheduling of public transport (CASPT)
Glück H (1973) Die Optimierung von Triebfahrzeugumlaufplänen bei großen Zugzahlen mit Hilfe elektronischer Datenverarbeitungsanlagen. Eisenbahntech Rundsch 9:354–363
Goldberg DE (1989) Genetic algorithms in search, optimisation and machine learning. Reading, Addison-Wesley
Grega W (1993) Decomposition approach to the public transport scheduling problem. Automatica 29(3):745–750
Hansen IA, Pachl J (eds) (2008) Railway timetable and traffic. Eurailpress, Hamburg
Kwan R, Mistry P (eds) (2003) A co-evolutionary algorithm for train timetabling. In: IEEE congress on evolutionary computation, pp 2142–2148
Lehner F (1950) Menge, Arbeit, Leistung und Wirkungsgrad im Verkehr. Verkehr Tech 1(2):42–45
Minciardi R, Paolucci M, Pesenti R (1995) Generating optimal schedules for an underground railway line. In: 34th IEEE conference on decision and control, pp 4082–4085
Osuna EE, Newell GF (1972) Control strategies for an idealized public transportation system. Transp Sci 6:52–72
Scholz S, Albrecht T (2006) ALFa—a software tool for optimal scheduling of demand oriented train services. In: Allan J, Brebbia CA, Rumsey AF, Sciutto G, Sone S, Goodman CJ (eds) Computers in railways, X. WIT, Southampton, pp 541–550
Scholz S, Strobel H, Oettich S (2003) Demand-driven automated urban rapid rail transit: A new approach to the assessment of the operational efficiency. In: APM’03, Proceedings of the 9th international conference on automated people movers, Singapore
Skolicki Z, De Jong K (2004) Improving evolutionary algorithms with multi-representation island models. In: Yao X, Burke E, Lozano JA, Smith J, Merelo-Guervos JJ, Bullinaria JA, Rowe J, Tino P, Kaban A, Schwefel H-P (eds) Parallel problem solving from nature VIII. Springer, Berlin, pp 420–429
Strobel H (2001) Die Potenziale automatischer und flexibler Stadtschnellbahnen. In: Jahrbuch des Bahnwesens. Hestra, Darmstadt, pp 106–118
Strobel H, Schütte J (2004) Optimum application of automated systems. In: 2nd UITP metropolitan railways conference “Converting conventional metro lines into automated operation”
Wegele S, Schnieder E (2004) Dispatching of train operations using genetic algorithms. In: 9th international conference of computer-aided scheduling of public transport, San Diego
Whitley D (1994) A genetic algorithm tutorial. Stat Comput 4:65–85
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Albrecht, T. Automated timetable design for demand-oriented service on suburban railways. Public Transp 1, 5–20 (2009). https://doi.org/10.1007/s12469-008-0003-4
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12469-008-0003-4