Abstract
In this paper, a compressed timetable is generated to calculate capacity consumption for under construction railway routes using an optimization approach. Since the detailed timetable for under construction routes does not exist, the timetable is not required in the applied model. The model generates a compressed timetable based on UIC 406 method. The capacity consumption problem is formulated as a multicommodity network design model on a space-discrete time network. A local branching heuristic algorithm is proposed to solve the model. The main idea underlining the local branching algorithm is the utilization of a general mixed integer programming solver to explore neighborhoods and locally search around the best-known solution by employing tree search. The parameters of the algorithm are tuned by using design of experiments. The proposed method is implemented in Iran Railways and the results are reported.
Similar content being viewed by others
References
Abril M, Barber F, Ingolotti L, Salido M, Tormos P, Lova A (2008) An assessment of railway capacity. Transp Res E-Log 44:774–806
Adenso-Díaz B, Laguna M (2006) Fine-tuning of algorithms using fractional experimental designs and local search. Oper Res 54:99–114
Berglund GP, Kwon C (2013) Robust Facility Location Problem for Hazardous Waste Transportation. Netw Spat Econ (in press)
Brännlund U, Lindberg P, Nôu A, Nilsson J (1998) Railway timetabling using Lagrangian relaxation. Transp Sci 32:358–369
Burdett RL, Kozan E (2006) Techniques for absolute capacity determination in railways. Transport Res B-Meth 40:616–632
Cacchiani V, Caprara A, Toth P (2010) Scheduling extra freight trains on railway networks. Transport Res B-Meth 44:215–231
Caimi G, Burkolter D, Herrmann T, Chudak F, Laumanns M (2009) Design of a railway scheduling model for dense services. Netw Spat Econ 9(1):25–46
Carey M (1994) A model and strategy for train pathing with choice of lines, platforms, and routes. Trans Res Part B 28(5):333–353
Carey M, Lockwood D (1995) A model, algorithms and strategy for train pathing. J Oper Res Soc 46B(8):988–1005
Coy SP, Golden BL, Runger GC, Wasil EA (2001) Using experimental design to find effective parameter settings for heuristics. J Heuristics 7:77–97
D’Ariano A, Pranzo M (2009) An advanced real-time train dispatching system for minimizing the propagation of delays in a dispatching area under severe disturbances. Netw Spat Econ 9(1):63–84
D’Ariano A, Pacciarelli D, Pranzo M (2007) A branch and bound algorithm for scheduling trains in a railway network. Eur J Oper Res 183:643–657
De Kort F, Heidergott B, Ayhan H (2003) A probabilistic (max, +) approach for determining railway infrastructure capacity. Eur J Oper Res 148:644–661
Dingler MH, Lai YC, Barkan CPL (2009) Impact of train type heterogeneity on single-track railway capacity. Transp Res Rec 2117:41–49
Do Chung B, Yao T, Xie C, Thorsen A (2011) Robust optimization model for a dynamic network design problem under demand uncertainty. Netw Spat Econ 11(2):371–389
Fığlalı N, Özkale C, Engin O, Fığlalı A (2009) Investigation of ant system parameter interactions by using design of experiments for job-shop scheduling problems. Comput Ind Eng 56:538–559
Fischetti M, Lodi A (2003) Local branching. Math Program 98:23–47
Harrod S (2009) Capacity factors of a mixed speed railway network. Transp Res E 45:830–841
Higgins A, Kozan E, Ferreira L (1996) Optimal scheduling of trains on a single line track. Transp Res B-Meth 30:147–161
International Union of Railways (UIC) (1983) UIC Leaflet 405-1. Method to be used for the Determination of the Capacity of Lines
International Union of Railways (UIC) (2004) Leaflet 406: Capacity
Islamic Republic of Iran Railways (2012) Train timetable. Office of train operation. Transportation studies and planning group
Khadem-Sameni M, Preston J, Armstrong J (2010) Railway capacity challenge: measuring and managing in Britain. Proceedings of the 2010 Joint Rail Conference. JRC2010, Urbana, IL, USA, JRC-36280
Kontaxi E, Ricci S (2011) Calculation of railway network capacity: comparing methodologies for lines and nodes. Conference on Operation Research in Railway Engineering, RAILROME, In
Krueger H (1999) Parametric modeling in rail capacity planning, proceedings of winter simulation conference. Phoenix, AZ
Lai YC, Barkan CPL (2009) Enhanced parametric railway capacity evaluation tool. Transp Res Rec 2117:33–40
Lai YC, Barkan CPL (2011) Comprehensive decision support framework for strategic railway capacity planning. J Transp Eng 137:738–749
Landex A (2008) Methods to estimate railway capacity and passenger delays. Ph.D. Thesis, In: Department of Transport., Technical university of Denmark: Kgs. Lyngby
Landex A (2009) Evaluation of railway networks with single track operation. Netw Spat Econ 9:7–23
Libardo A, Pellegrini P, Giorgio S (2011) Capacity in railway junctions and optimal route management. Conference on operation research in railway. Engineering, RAILROME
Merel A, Gandibleux X, Demassey S, Lusby R (2009) An improved upper bound for the railway infrastructure capacity problem on the pierrefitte-gonesse junction. Dixième congrès de la Société Française de Recherche Opérationnelle et d’Aide à la Décision, Nancy, France, pp 62–76
Montgomery DC (2009) Design and analysis of experiments. John Wiley and Sons
Mu S, Dessouky M (2011) Scheduling freight trains traveling on complex networks. Transp Res B-Meth 45:1103–1123
Mussone L, Calvo RW (2013) An analytical approach to calculate the capacity of a railway system. Eur J Oper Res 228:11–23
Pachl J, White T (2004) Analytical capacity management with blocking times. Transportation Research Board. 83rd Annual Meeting, Mira Digital Publishing, Washington, D.C
Ridge E, Kudenko D (2007) Tuning the performance of the MMAS heuristic, In: Stützle T, Birattari M, Hoos, HH (eds), Proc. International Workshop on Engineering Stochastic Local Search Algorithms, 46–60
Ridge E, Kudenko D (2010) Tuning an algorithm using design of experiments. In: Bartz-Beielstein T, Chiarandini M, Paquete L, Preuss M (eds) Experimental methods for the analysis of optimization algorithms. Natural Computing Series, Springer, Berlin, pp 265–286
Şahin G, Ahuja Ravindra K, Cunha Claudio B (2010) Integer programming based solution approaches for the train dispatching problem, Sabanci University
Yaghini M, Nikoo N, Ahadi H (2012) An integer programming model for analyzing impacts of different train types on railway line capacity. Transp, (in press)
Yaghini M, Momeni M, Sarmadi M (2013) An improved local branching approach for train formation planning. Appl Math Model 37:2300–2307
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Yaghini, M., Sarmadi, M., Nikoo, N. et al. Capacity Consumption Analysis Using Heuristic Solution Method for Under Construction Railway Routes. Netw Spat Econ 14, 317–333 (2014). https://doi.org/10.1007/s11067-014-9223-0
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11067-014-9223-0