IDEAS home Printed from https://ideas.repec.org/a/eee/apmaco/v251y2015icp132-142.html
   My bibliography  Save this article

A multi-start variable neighborhood search for solving the single path multicommodity flow problem

Author

Listed:
  • Masri, H.
  • Krichen, S.
  • Guitouni, A.

Abstract

In this paper, we propose a new global routing algorithm supporting advance reservation. A predefined number of messages are to be routed in a capacitated network including a set of nodes that can be producers and/or consumers of information. We assume that the same information can be held by different sources. We first propose the non-linear mathematical formulation for this problem by extending the single path multicommodity flow formulation. To solve such an NP-hard optimization problem, we develop a multi-start variable neighborhood search method (MVNS). The results of extensive computational experiments across a variety of networks from the literature are reported. For small and medium scale instances, the results are compared with the optimal solution generated by LINGO in terms of time and optimality. For large size instances, a comparison to a state-of-the-art ant colony system approach is performed. The obtained results show that the MVNS algorithm is computationally effective and provides high-quality solutions.

Suggested Citation

  • Masri, H. & Krichen, S. & Guitouni, A., 2015. "A multi-start variable neighborhood search for solving the single path multicommodity flow problem," Applied Mathematics and Computation, Elsevier, vol. 251(C), pages 132-142.
    • Handle: RePEc:eee:apmaco:v:251:y:2015:i:c:p:132-142
    DOI: 10.1016/j.amc.2014.10.123
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0096300314014982
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.amc.2014.10.123?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. Jeff L. Kennington, 1978. "A Survey of Linear Cost Multicommodity Network Flows," Operations Research, INFORMS, vol. 26(2), pages 209-236, April.
    2. Kaj Holmberg & Di Yuan, 2003. "A Multicommodity Network-Flow Problem with Side Constraints on Paths Solved by Column Generation," INFORMS Journal on Computing, INFORMS, vol. 15(1), pages 42-57, February.
    3. Cynthia Barnhart & Christopher A. Hane & Pamela H. Vance, 2000. "Using Branch-and-Price-and-Cut to Solve Origin-Destination Integer Multicommodity Flow Problems," Operations Research, INFORMS, vol. 48(2), pages 318-326, April.
    4. A. Ouorou & P. Mahey & J.-Ph. Vial, 2000. "A Survey of Algorithms for Convex Multicommodity Flow Problems," Management Science, INFORMS, vol. 46(1), pages 126-147, January.
    5. Hansen, Pierre & Mladenovic, Nenad, 2001. "Variable neighborhood search: Principles and applications," European Journal of Operational Research, Elsevier, vol. 130(3), pages 449-467, May.
    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. Khodakaram Salimifard & Sara Bigharaz, 2022. "The multicommodity network flow problem: state of the art classification, applications, and solution methods," Operational Research, Springer, vol. 22(1), pages 1-47, March.
    2. François Lamothe & Emmanuel Rachelson & Alain Haït & Cedric Baudoin & Jean-Baptiste Dupé, 2021. "Randomized rounding algorithms for large scale unsplittable flow problems," Journal of Heuristics, Springer, vol. 27(6), pages 1081-1110, December.

    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. Khodakaram Salimifard & Sara Bigharaz, 2022. "The multicommodity network flow problem: state of the art classification, applications, and solution methods," Operational Research, Springer, vol. 22(1), pages 1-47, March.
    2. Hela Masri & Saoussen Krichen, 2018. "Exact and approximate approaches for the Pareto front generation of the single path multicommodity flow problem," Annals of Operations Research, Springer, vol. 267(1), pages 353-377, August.
    3. Bita Tadayon & J. Cole Smith, 2014. "Algorithms for an Integer Multicommodity Network Flow Problem with Node Reliability Considerations," Journal of Optimization Theory and Applications, Springer, vol. 161(2), pages 506-532, May.
    4. Garg, Manish & Smith, J. Cole, 2008. "Models and algorithms for the design of survivable multicommodity flow networks with general failure scenarios," Omega, Elsevier, vol. 36(6), pages 1057-1071, December.
    5. Naga V. C. Gudapati & Enrico Malaguti & Michele Monaci, 2022. "Network Design with Service Requirements: Scaling-up the Size of Solvable Problems," INFORMS Journal on Computing, INFORMS, vol. 34(5), pages 2571-2582, September.
    6. Gamvros, Ioannis & Raghavan, S., 2012. "Multi-period traffic routing in satellite networks," European Journal of Operational Research, Elsevier, vol. 219(3), pages 738-750.
    7. Pillac, Victor & Van Hentenryck, Pascal & Even, Caroline, 2016. "A conflict-based path-generation heuristic for evacuation planning," Transportation Research Part B: Methodological, Elsevier, vol. 83(C), pages 136-150.
    8. Yu Zhou & Leishan Zhou & Yun Wang & Xiaomeng Li & Zhuo Yang, 2017. "A practical model for the train-set utilization: The case of Beijing-Tianjin passenger dedicated line in China," PLOS ONE, Public Library of Science, vol. 12(5), pages 1-24, May.
    9. Amy Cohn & Sarah Root & Alex Wang & Douglas Mohr, 2007. "Integration of the Load-Matching and Routing Problem with Equipment Balancing for Small Package Carriers," Transportation Science, INFORMS, vol. 41(2), pages 238-252, May.
    10. Trivella, Alessio & Corman, Francesco & Koza, David F. & Pisinger, David, 2021. "The multi-commodity network flow problem with soft transit time constraints: Application to liner shipping," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 150(C).
    11. Peeters, M. & Kroon, L.G., 2003. "Circulation of Railway Rolling Stock: A Branch-and-Price Approach," ERIM Report Series Research in Management ERS-2003-055-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.
    12. Esteban Inga & Roberto Hincapié & Sandra Céspedes, 2019. "Capacitated Multicommodity Flow Problem for Heterogeneous Smart Electricity Metering Communications Using Column Generation," Energies, MDPI, vol. 13(1), pages 1-21, December.
    13. Maenhout, Broos & Vanhoucke, Mario, 2010. "A hybrid scatter search heuristic for personalized crew rostering in the airline industry," European Journal of Operational Research, Elsevier, vol. 206(1), pages 155-167, October.
    14. Manlio Gaudioso & Giovanni Giallombardo & Giovanna Miglionico, 2018. "Minimizing Piecewise-Concave Functions Over Polyhedra," Mathematics of Operations Research, INFORMS, vol. 43(2), pages 580-597, May.
    15. Meng, Qiang & Lee, Chung-Yee, 2016. "Liner container assignment model with transit-time-sensitive container shipment demand and its applicationsAuthor-Name: Wang, Shuaian," Transportation Research Part B: Methodological, Elsevier, vol. 90(C), pages 135-155.
    16. Fernandez del Pozo, J. A. & Bielza, C. & Gomez, M., 2005. "A list-based compact representation for large decision tables management," European Journal of Operational Research, Elsevier, vol. 160(3), pages 638-662, February.
    17. Amina Lamghari & Roussos Dimitrakopoulos & Jacques Ferland, 2015. "A hybrid method based on linear programming and variable neighborhood descent for scheduling production in open-pit mines," Journal of Global Optimization, Springer, vol. 63(3), pages 555-582, November.
    18. J. Redondo & J. Fernández & I. García & P. Ortigosa, 2009. "A robust and efficient algorithm for planar competitive location problems," Annals of Operations Research, Springer, vol. 167(1), pages 87-105, March.
    19. Patricia Domínguez-Marín & Stefan Nickel & Pierre Hansen & Nenad Mladenović, 2005. "Heuristic Procedures for Solving the Discrete Ordered Median Problem," Annals of Operations Research, Springer, vol. 136(1), pages 145-173, April.
    20. Ali Shahabi & Sadigh Raissi & Kaveh Khalili-Damghani & Meysam Rafei, 2021. "Designing a resilient skip-stop schedule in rapid rail transit using a simulation-based optimization methodology," Operational Research, Springer, vol. 21(3), pages 1691-1721, September.

    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:apmaco:v:251:y:2015:i:c:p:132-142. 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: https://www.journals.elsevier.com/applied-mathematics-and-computation .

    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.