IDEAS home Printed from https://ideas.repec.org/a/eee/transe/v82y2015icp217-237.html
   My bibliography  Save this article

Introducing a preliminary consists selection in the locomotive assignment problem

Author

Listed:
  • Piu, F.
  • Prem Kumar, V.
  • Bierlaire, M.
  • Speranza, M.G.

Abstract

The Locomotive Assignment Problem (LAP) is a class of planning and scheduling problems solved by assigning a fleet of locomotives to a network of trains. In the planning versions of the LAP, the type of consist (a group of linked locomotives) assigned to each train in a given schedule is determined. We introduce an optimization model (called consists selection) that precedes the planning LAP solution and determines the set of consist types. This selection leads to solutions that are characterized by potential savings in terms of overall fueling cost and are easier to handle in the routing phase.

Suggested Citation

  • Piu, F. & Prem Kumar, V. & Bierlaire, M. & Speranza, M.G., 2015. "Introducing a preliminary consists selection in the locomotive assignment problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 82(C), pages 217-237.
    • Handle: RePEc:eee:transe:v:82:y:2015:i:c:p:217-237
    DOI: 10.1016/j.tre.2015.07.003
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S136655451500143X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.tre.2015.07.003?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Warren B. Powell & Belgacem Bouzaiene-Ayari & Coleman Lawrence & Clark Cheng & Sourav Das & Ricardo Fiorillo, 2014. "Locomotive Planning at Norfolk Southern: An Optimizing Simulator Using Approximate Dynamic Programming," Interfaces, INFORMS, vol. 44(6), pages 567-578, December.
    2. Marar, Arun & Powell, Warren B., 2009. "Capturing incomplete information in resource allocation problems through numerical patterns," European Journal of Operational Research, Elsevier, vol. 197(1), pages 50-58, August.
    3. Ravindra K. Ahuja & Jian Liu & James B. Orlin & Dushyant Sharma & Larry A. Shughart, 2005. "Solving Real-Life Locomotive-Scheduling Problems," Transportation Science, INFORMS, vol. 39(4), pages 503-517, November.
    4. Koorush Ziarati & François Soumis & Jacques Desrosiers & Marius M. Solomon, 1999. "A Branch-First, Cut-Second Approach for Locomotive Assignment," Management Science, INFORMS, vol. 45(8), pages 1156-1168, August.
    5. Balachandran Vaidyanathan & Ravindra K. Ahuja & James B. Orlin, 2008. "The Locomotive Routing Problem," Transportation Science, INFORMS, vol. 42(4), pages 492-507, November.
    6. Warren Powell & Joel Shapiro & Hugo Simao, 2001. "A Representational Paradigm for Dynamic Resource Transformation Problems," Annals of Operations Research, Springer, vol. 104(1), pages 231-279, April.
    7. Dondo, Rodolfo & Cerda, Jaime, 2007. "A cluster-based optimization approach for the multi-depot heterogeneous fleet vehicle routing problem with time windows," European Journal of Operational Research, Elsevier, vol. 176(3), pages 1478-1507, February.
    8. Marco E. Lübbecke & Uwe T. Zimmermann, 2003. "Engine Routing and Scheduling at Industrial In-Plant Railroads," Transportation Science, INFORMS, vol. 37(2), pages 183-197, May.
    9. Ziarati, Koorush & Soumis, Francois & Desrosiers, Jacques & Gelinas, Sylvie & Saintonge, Andre, 1997. "Locomotive assignment with heterogeneous consists at CN North America," European Journal of Operational Research, Elsevier, vol. 97(2), pages 281-292, March.
    10. D H Noble & M Al-Amin & R G J Mills, 2001. "Production of locomotive rosters for a multi-class multi-locomotive problem," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 52(11), pages 1191-1200, November.
    11. Vaidyanathan, Balachandran & Ahuja, Ravindra K. & Liu, Jian & Shughart, Larry A., 2008. "Real-life locomotive planning: New formulations and computational results," Transportation Research Part B: Methodological, Elsevier, vol. 42(2), pages 147-168, February.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Scheffler, Martin & Neufeld, Janis S. & Hölscher, Michael, 2020. "An MIP-based heuristic solution approach for the locomotive assignment problem focussing on (dis-)connecting processes," Transportation Research Part B: Methodological, Elsevier, vol. 139(C), pages 64-80.
    2. Canca, David & Barrena, Eva, 2018. "The integrated rolling stock circulation and depot location problem in railway rapid transit systems," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 109(C), pages 115-138.
    3. Huang, Baobin & Tang, Lixin & Baldacci, Roberto & Wang, Gongshu & Sun, Defeng, 2023. "A metaheuristic algorithm for a locomotive routing problem arising in the steel industry," European Journal of Operational Research, Elsevier, vol. 308(1), pages 385-399.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Prashant Premkumar & P. N. Ram Kumar, 2019. "Literature Review of Locomotive Assignment Problem from Service Operations Perspective: The Case of Indian Railways," IIM Kozhikode Society & Management Review, , vol. 8(1), pages 74-86, January.
    2. Camilo Ortiz-Astorquiza & Jean-François Cordeau & Emma Frejinger, 2021. "The Locomotive Assignment Problem with Distributed Power at the Canadian National Railway Company," Transportation Science, INFORMS, vol. 55(2), pages 510-531, March.
    3. Prashant Premkumar & P. N. Ram Kumar, 2022. "Locomotive assignment problem: integrating the strategic, tactical and operational level aspects," Annals of Operations Research, Springer, vol. 315(2), pages 867-898, August.
    4. Belgacem Bouzaiene-Ayari & Clark Cheng & Sourav Das & Ricardo Fiorillo & Warren B. Powell, 2016. "From Single Commodity to Multiattribute Models for Locomotive Optimization: A Comparison of Optimal Integer Programming and Approximate Dynamic Programming," Transportation Science, INFORMS, vol. 50(2), pages 366-389, May.
    5. Xu, Xiaoming & Li, Chung-Lun & Xu, Zhou, 2018. "Integrated train timetabling and locomotive assignment," Transportation Research Part B: Methodological, Elsevier, vol. 117(PA), pages 573-593.
    6. Warren B. Powell & Belgacem Bouzaiene-Ayari & Coleman Lawrence & Clark Cheng & Sourav Das & Ricardo Fiorillo, 2014. "Locomotive Planning at Norfolk Southern: An Optimizing Simulator Using Approximate Dynamic Programming," Interfaces, INFORMS, vol. 44(6), pages 567-578, December.
    7. Petr KOZLOV & Sergey VAKULENKO & Nikolay TUSHIN & Elena TIMUKHINA, 2017. "Model To Calculate The Optimal Mode Of Train Locomotives Turnover," Transport Problems, Silesian University of Technology, Faculty of Transport, vol. 12(3), pages 125-133, September.
    8. Vaidyanathan, Balachandran & Ahuja, Ravindra K. & Liu, Jian & Shughart, Larry A., 2008. "Real-life locomotive planning: New formulations and computational results," Transportation Research Part B: Methodological, Elsevier, vol. 42(2), pages 147-168, February.
    9. Balachandran Vaidyanathan & Ravindra K. Ahuja & James B. Orlin, 2008. "The Locomotive Routing Problem," Transportation Science, INFORMS, vol. 42(4), pages 492-507, November.
    10. Frisch, Sarah & Hungerländer, Philipp & Jellen, Anna & Primas, Bernhard & Steininger, Sebastian & Weinberger, Dominic, 2021. "Solving a real-world Locomotive Scheduling Problem with Maintenance Constraints," Transportation Research Part B: Methodological, Elsevier, vol. 150(C), pages 386-409.
    11. Scheffler, Martin & Neufeld, Janis S. & Hölscher, Michael, 2020. "An MIP-based heuristic solution approach for the locomotive assignment problem focussing on (dis-)connecting processes," Transportation Research Part B: Methodological, Elsevier, vol. 139(C), pages 64-80.
    12. Nourbakhsh, Seyed Mohammad & Ouyang, Yanfeng, 2010. "Optimal fueling strategies for locomotive fleets in railroad networks," Transportation Research Part B: Methodological, Elsevier, vol. 44(8-9), pages 1104-1114, September.
    13. Philimon Nyamugure & Siphosenkosi Dube Swene & Edward T. Chiyaka & Farikayi K. Mutasa, 2014. "Train Schedule Optimization: A Case Study of the National Railways of Zimbabwe," International Journal of Management Sciences, Research Academy of Social Sciences, vol. 3(1), pages 1-20.
    14. Petr KOZLOV & Elena TIMUKHINA & Nikolay TUSHIN, 2018. "Coordination Of Locomotives Turnover And Servicing Modes," Transport Problems, Silesian University of Technology, Faculty of Transport, vol. 13(1), pages 19-26, March.
    15. Rouillon, Stéphane & Desaulniers, Guy & Soumis, François, 2006. "An extended branch-and-bound method for locomotive assignment," Transportation Research Part B: Methodological, Elsevier, vol. 40(5), pages 404-423, June.
    16. Chung, Ji-Won & Oh, Seog-Moon & Choi, In-Chan, 2009. "A hybrid genetic algorithm for train sequencing in the Korean railway," Omega, Elsevier, vol. 37(3), pages 555-565, June.
    17. Michael F. Gorman & John-Paul Clarke & Amir Hossein Gharehgozli & Michael Hewitt & René de Koster & Debjit Roy, 2014. "State of the Practice: A Review of the Application of OR/MS in Freight Transportation," Interfaces, INFORMS, vol. 44(6), pages 535-554, December.
    18. Haahr, J.T. & Wagenaar, J.C. & Veelenturf, L.P. & Kroon, L.G., 2015. "A Comparison of Two Exact Methods for Passenger Railway Rolling Stock (Re)Scheduling," ERIM Report Series Research in Management ERS-2015-007-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    19. Sato, Keisuke & Fukumura, Naoto, 2012. "Real-time freight locomotive rescheduling and uncovered train detection during disruption," European Journal of Operational Research, Elsevier, vol. 221(3), pages 636-648.
    20. Shah, Nirav & Kumar, Subodha & Bastani, Farokh & Yen, I-Ling, 2012. "Optimization models for assessing the peak capacity utilization of intelligent transportation systems," European Journal of Operational Research, Elsevier, vol. 216(1), pages 239-251.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:transe:v:82:y:2015:i:c:p:217-237. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/600244/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.