eprintid: 22657 rev_number: 14 eprint_status: archive userid: 1903 dir: disk0/00/02/26/57 datestamp: 2014-11-03 18:54:40 lastmod: 2014-11-03 18:54:40 status_changed: 2014-11-03 18:54:40 type: article metadata_visibility: show item_issues_count: 0 creators_name: Cadarso Morga, Luis creators_name: Marín Gracia, Angel creators_name: Torres, Luis title: Robust rolling stock under uncertain demand in rapid transit networks rights: by-nc-nd ispublished: pub subjects: matematicas full_text_status: public keywords: Suburban railways, stochastic, rolling stock abstract: This paper focuses on the railway rolling stock circulation problem in rapid transit networks where the known demand and train schedule must be met by a given fleet. In rapid transit networks the frequencies are high and distances are relatively short. Although the distances are not very large, service times are high due to the large number of intermediate stops required to allow proper passenger flow. The previous circumstances and the reduced capacity of the depot stations and that the rolling stock is shared between the different lines, force the introduction of empty trains and a careful control on shunting operation. In practice the future demand is generally unknown and the decisions must be based on uncertain forecast. We have developed a stochastic rolling stock formulation of the problem. The computational experiments were developed using a commercial line of the Madrid suburban rail network operated by RENFE (The main Spanish operator of suburban trains of passengers). Comparing the results obtained by deterministic scenarios and stochastic approach some useful conclusions may be obtained. date_type: published date: 2012-09 publication: Relatórios de pesquisa em engenharia de produção volume: 12 number: 3 pagerange: 29-40 institution: Aeronauticos department: Matematica_Aplicada9 refereed: TRUE issn: 1678-2399 referencetext: Alfieri, A., Groot, R., Kroon, L.G. and Schrijver, A., (2006), A. Efficient circulation of railway rolling stock. Transportation Science, 40, 378-391. Ben-Khedher, N., Kintanar, J., Queille, C. and Stripling, W. (1998), Schedule Optimization at SNCF: From Conception to Day of Departure. Interfaces, 28, 6-23. Birge, J.R. and Louveaux, F., (1997) Introduction to Stochastic programming, Springer Series in operations Research. Cadarso, L., Marín, A., (2011). Robust Rolling Stock in Rapid Transit Networks. Computers and Operations Research, 32, 1131-1142. Fioole, P.G., Kroon, L.G., Maróti, G. and Schrijver, A., (2006), A rolling stock circulation model for combining and splitting of passenger trains. European Journal of Operational Research, 174(2):1281-1297. Kall, P. and Mayer, J., (2005). Stochastic linear programming: Models, Theory and Computation, Kluwer Academic Publishers, New York. Maróti, G., (2006), Operations Research Models for Railway Rolling Stock Planning, PhD thesis, Eindhoven, Technische Universiteit Eindhoven. Mellouli, T. and Suhl, L. (20007). Rotation planni ng of locomotive and carriage groups with shared capacities. In F. Geraets, L.G. Kroon, A. Schbel, D. Wagner, and C. Zaroliagis, editors, Algorithmic Methods for Railway Optimization. Springer, Berlin, Germany. Prékopa, A., (1995), Stochastic Programming, Kluwer Academic Publishers, Dordrecht. Rockafeller, R.T. and Wets, R.J.B., (1991), Scenarios and policy in optimization under uncertainty, Mathematics of Operations Research,16, 119-147. Ruszczynski, A. and Shapiro, A., (2003), Stochastic Programming. Handbook in Operations Research and Management Science, volume 10. Elsevier. citation: Cadarso Morga, Luis and Marín Gracia, Angel and Torres, Luis (2012). Robust rolling stock under uncertain demand in rapid transit networks. "Relatórios de pesquisa em engenharia de produção", v. 12 (n. 3); pp. 29-40. ISSN 1678-2399. document_url: https://oa.upm.es/22657/1/INVE_MEM_2012_153276.pdf