IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v287y2020i2p410-437.html
   My bibliography  Save this article

Exact solution algorithms for the maximum flow problem with additional conflict constraints

Author

Listed:
  • Şuvak, Zeynep
  • Altınel, İ. Kuban
  • Aras, Necati

Abstract

We consider a variant of the maximum flow problem on a given directed graph where some arc pairs are incompatible or conflicting; in other words, they are not allowed to carry positive flow simultaneously. This problem, called the maximum flow problem with conflicts, is known to be strongly NP-hard. In this paper, we present mixed-integer linear programming formulations for the problem and develop exact solution methods based on Benders decomposition, branch-and-bound, and Russian Doll Search over the conflict graph which represents the conflict relations. The effectiveness of the proposed algorithms is tested on a large number of randomly generated instances. The results reveal that their performances are superior to solving the mixed-integer linear programming formulations with a commercial software.

Suggested Citation

  • Şuvak, Zeynep & Altınel, İ. Kuban & Aras, Necati, 2020. "Exact solution algorithms for the maximum flow problem with additional conflict constraints," European Journal of Operational Research, Elsevier, vol. 287(2), pages 410-437.
    • Handle: RePEc:eee:ejores:v:287:y:2020:i:2:p:410-437
    DOI: 10.1016/j.ejor.2020.04.001
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377221720303192
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ejor.2020.04.001?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. Ulrich Pferschy & Joachim Schauer, 2013. "The maximum flow problem with disjunctive constraints," Journal of Combinatorial Optimization, Springer, vol. 26(1), pages 109-119, July.
    2. T. L. Magnanti & R. T. Wong, 1981. "Accelerating Benders Decomposition: Algorithmic Enhancement and Model Selection Criteria," Operations Research, INFORMS, vol. 29(3), pages 464-484, June.
    3. Ruslan Sadykov & François Vanderbeck, 2013. "Bin Packing with Conflicts: A Generic Branch-and-Price Algorithm," INFORMS Journal on Computing, INFORMS, vol. 25(2), pages 244-255, May.
    4. Svyatoslav Trukhanov & Chitra Balasubramaniam & Balabhaskar Balasundaram & Sergiy Butenko, 2013. "Algorithms for detecting optimal hereditary structures in graphs, with application to clique relaxations," Computational Optimization and Applications, Springer, vol. 56(1), pages 113-130, September.
    5. Maciej Rysz & Mohammad Mirghorbani & Pavlo Krokhmal & Eduardo L. Pasiliao, 2014. "On risk-averse maximum weighted subgraph problems," Journal of Combinatorial Optimization, Springer, vol. 28(1), pages 167-185, July.
    6. Albert E. Fernandes Muritiba & Manuel Iori & Enrico Malaguti & Paolo Toth, 2010. "Algorithms for the Bin Packing Problem with Conflicts," INFORMS Journal on Computing, INFORMS, vol. 22(3), pages 401-415, August.
    7. Samir Elhedhli & Lingzi Li & Mariem Gzara & Joe Naoum-Sawaya, 2011. "A Branch-and-Price Algorithm for the Bin Packing Problem with Conflicts," INFORMS Journal on Computing, INFORMS, vol. 23(3), pages 404-415, August.
    8. Sun, Minghe, 2002. "The transportation problem with exclusionary side constraints and two branch-and-bound algorithms," European Journal of Operational Research, Elsevier, vol. 140(3), pages 629-647, August.
    9. Rahmaniani, Ragheb & Crainic, Teodor Gabriel & Gendreau, Michel & Rei, Walter, 2017. "The Benders decomposition algorithm: A literature review," European Journal of Operational Research, Elsevier, vol. 259(3), pages 801-817.
    10. Gianni Codato & Matteo Fischetti, 2006. "Combinatorial Benders' Cuts for Mixed-Integer Linear Programming," Operations Research, INFORMS, vol. 54(4), pages 756-766, August.
    11. Andrea Bettinelli & Valentina Cacchiani & Enrico Malaguti, 2017. "A Branch-and-Bound Algorithm for the Knapsack Problem with Conflict Graph," INFORMS Journal on Computing, INFORMS, vol. 29(3), pages 457-473, August.
    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. Bigler, T. & Kammermann, M. & Baumann, P., 2023. "A matheuristic for a customer assignment problem in direct marketing," European Journal of Operational Research, Elsevier, vol. 304(2), pages 689-708.
    2. Fan, Lin & Su, Huai & Wang, Wei & Zio, Enrico & Zhang, Li & Yang, Zhaoming & Peng, Shiliang & Yu, Weichao & Zuo, Lili & Zhang, Jinjun, 2022. "A systematic method for the optimization of gas supply reliability in natural gas pipeline network based on Bayesian networks and deep reinforcement learning," Reliability Engineering and System Safety, Elsevier, vol. 225(C).

    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. Lijun Wei & Zhixing Luo, & Roberto Baldacci & Andrew Lim, 2020. "A New Branch-and-Price-and-Cut Algorithm for One-Dimensional Bin-Packing Problems," INFORMS Journal on Computing, INFORMS, vol. 32(2), pages 428-443, April.
    2. Orlando Rivera Letelier & François Clautiaux & Ruslan Sadykov, 2022. "Bin Packing Problem with Time Lags," INFORMS Journal on Computing, INFORMS, vol. 34(4), pages 2249-2270, July.
    3. Saharnaz Mehrani & Carlos Cardonha & David Bergman, 2022. "Models and Algorithms for the Bin-Packing Problem with Minimum Color Fragmentation," INFORMS Journal on Computing, INFORMS, vol. 34(2), pages 1070-1085, March.
    4. Coniglio, Stefano & Furini, Fabio & San Segundo, Pablo, 2021. "A new combinatorial branch-and-bound algorithm for the Knapsack Problem with Conflicts," European Journal of Operational Research, Elsevier, vol. 289(2), pages 435-455.
    5. Bigler, T. & Kammermann, M. & Baumann, P., 2023. "A matheuristic for a customer assignment problem in direct marketing," European Journal of Operational Research, Elsevier, vol. 304(2), pages 689-708.
    6. Andrea Bettinelli & Valentina Cacchiani & Enrico Malaguti, 2017. "A Branch-and-Bound Algorithm for the Knapsack Problem with Conflict Graph," INFORMS Journal on Computing, INFORMS, vol. 29(3), pages 457-473, August.
    7. Maher, Stephen J., 2021. "Implementing the branch-and-cut approach for a general purpose Benders’ decomposition framework," European Journal of Operational Research, Elsevier, vol. 290(2), pages 479-498.
    8. Belieres, Simon & Hewitt, Mike & Jozefowiez, Nicolas & Semet, Frédéric & Van Woensel, Tom, 2020. "A Benders decomposition-based approach for logistics service network design," European Journal of Operational Research, Elsevier, vol. 286(2), pages 523-537.
    9. Dursun, Pınar & Taşkın, Z. Caner & Altınel, İ. Kuban, 2019. "The determination of optimal treatment plans for Volumetric Modulated Arc Therapy (VMAT)," European Journal of Operational Research, Elsevier, vol. 272(1), pages 372-388.
    10. Renatha Capua & Yuri Frota & Luiz Satoru Ochi & Thibaut Vidal, 2018. "A study on exponential-size neighborhoods for the bin packing problem with conflicts," Journal of Heuristics, Springer, vol. 24(4), pages 667-695, August.
    11. Michels, Adalberto Sato & Lopes, Thiago Cantos & Magatão, Leandro, 2020. "An exact method with decomposition techniques and combinatorial Benders’ cuts for the type-2 multi-manned assembly line balancing problem," Operations Research Perspectives, Elsevier, vol. 7(C).
    12. Rodríguez, Jesús A. & Anjos, Miguel F. & Côté, Pascal & Desaulniers, Guy, 2021. "Accelerating Benders decomposition for short-term hydropower maintenance scheduling," European Journal of Operational Research, Elsevier, vol. 289(1), pages 240-253.
    13. Hu, Qian & Zhu, Wenbin & Qin, Hu & Lim, Andrew, 2017. "A branch-and-price algorithm for the two-dimensional vector packing problem with piecewise linear cost function," European Journal of Operational Research, Elsevier, vol. 260(1), pages 70-80.
    14. Kiho Seo & Seulgi Joung & Chungmok Lee & Sungsoo Park, 2022. "A Closest Benders Cut Selection Scheme for Accelerating the Benders Decomposition Algorithm," INFORMS Journal on Computing, INFORMS, vol. 34(5), pages 2804-2827, September.
    15. Michels, Adalberto Sato & Lopes, Thiago Cantos & Sikora, Celso Gustavo Stall & Magatão, Leandro, 2019. "A Benders’ decomposition algorithm with combinatorial cuts for the multi-manned assembly line balancing problem," European Journal of Operational Research, Elsevier, vol. 278(3), pages 796-808.
    16. Ulrich Pferschy & Joachim Schauer, 2017. "Approximation of knapsack problems with conflict and forcing graphs," Journal of Combinatorial Optimization, Springer, vol. 33(4), pages 1300-1323, May.
    17. Borja Ena & Alberto Gomez & Borja Ponte & Paolo Priore & Diego Diaz, 2022. "Homogeneous grouping of non-prime steel products for online auctions: a case study," Annals of Operations Research, Springer, vol. 315(1), pages 591-621, August.
    18. Neamatian Monemi, Rahimeh & Gelareh, Shahin & Nagih, Anass & Maculan, Nelson & Danach, Kassem, 2021. "Multi-period hub location problem with serial demands: A case study of humanitarian aids distribution in Lebanon," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 149(C).
    19. Nieto-Isaza, Santiago & Fontaine, Pirmin & Minner, Stefan, 2022. "The value of stochastic crowd resources and strategic location of mini-depots for last-mile delivery: A Benders decomposition approach," Transportation Research Part B: Methodological, Elsevier, vol. 157(C), pages 62-79.
    20. Zheng, Xiaojin & Yin, Meixia & Zhang, Yanxia, 2019. "Integrated optimization of location, inventory and routing in supply chain network design," Transportation Research Part B: Methodological, Elsevier, vol. 121(C), pages 1-20.

    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:ejores:v:287:y:2020:i:2:p:410-437. 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/locate/eor .

    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.