IDEAS home Printed from https://ideas.repec.org/a/inm/orijoc/v35y2023i1p83-103.html
   My bibliography  Save this article

Robust Minimum-Cost Flow Problems Under Multiple Ripple Effect Disruptions

Author

Listed:
  • Mehdi Ansari

    (School of Industrial Engineering and Management, Oklahoma State University, Stillwater, Oklahoma 74078)

  • Juan S. Borrero

    (School of Industrial Engineering and Management, Oklahoma State University, Stillwater, Oklahoma 74078)

  • Leonardo Lozano

    (Operations, Business Analytics & Information Systems, University of Cincinnati, Cincinnati, Ohio 45221)

Abstract

We study a class of adversarial minimum-cost flow problems where the arcs are subject to multiple ripple effect disruptions that increase their usage cost. The locations of the disruptions’ epicenters are uncertain, and the decision maker seeks a flow that minimizes cost assuming the worst-case realization of the disruptions. We evaluate the damage to each arc using a linear model, where the damage is the cumulative damage of all disruptions affecting the arc; and a maximum model, where the damage is given by the most destructive disruption affecting the arc. For both models, the arcs’ costs after disruptions are represented with a mixed-integer feasible region, resulting in a robust optimization problem with a mixed-integer uncertainty set. The main challenge to solve the problem comes from a subproblem that evaluates the worst-case cost for a given flow plan. We show that for the linear model the uncertainty set can be decomposed into a series of single disruption problems, which leads to a polynomial time algorithm for the subproblem. The uncertainty set of the maximum model, however, cannot be decomposed, and we show that the subproblem under this model is NP-hard. For this case, we further present a big-M free binary reformulation of the uncertainty set based on conflict constraints that results in a significantly smaller formulation with tighter linear programming relaxations. We extend the models by considering a less conservative approach where only a subset of the disruptions can occur and show that the properties of the linear and maximum models also hold in this case. We test our proposed approaches over real road networks and synthetics instances and show that our methods achieve orders of magnitude improvements over a standard approach from the literature.

Suggested Citation

  • Mehdi Ansari & Juan S. Borrero & Leonardo Lozano, 2023. "Robust Minimum-Cost Flow Problems Under Multiple Ripple Effect Disruptions," INFORMS Journal on Computing, INFORMS, vol. 35(1), pages 83-103, January.
  • Handle: RePEc:inm:orijoc:v:35:y:2023:i:1:p:83-103
    DOI: 10.1287/ijoc.2022.1243
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/ijoc.2022.1243
    Download Restriction: no

    File URL: https://libkey.io/10.1287/ijoc.2022.1243?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
    ---><---

    References listed on IDEAS

    as
    1. Tao Yao & Supreet Mandala & Byung Chung, 2009. "Evacuation Transportation Planning Under Uncertainty: A Robust Optimization Approach," Networks and Spatial Economics, Springer, vol. 9(2), pages 171-189, June.
    2. Dimitris Bertsimas & Melvyn Sim, 2004. "The Price of Robustness," Operations Research, INFORMS, vol. 52(1), pages 35-53, February.
    3. Matteo Fischetti & Ivana Ljubić & Michele Monaci & Markus Sinnl, 2017. "A New General-Purpose Algorithm for Mixed-Integer Bilevel Linear Programs," Operations Research, INFORMS, vol. 65(6), pages 1615-1637, December.
    4. Dimitris Bertsimas & Aurélie Thiele, 2006. "A Robust Optimization Approach to Inventory Theory," Operations Research, INFORMS, vol. 54(1), pages 150-168, February.
    5. Alexander Mitsos, 2010. "Global solution of nonlinear mixed-integer bilevel programs," Journal of Global Optimization, Springer, vol. 47(4), pages 557-582, August.
    6. Dimitris Bertsimas & David B. Brown, 2009. "Constructing Uncertainty Sets for Robust Linear Optimization," Operations Research, INFORMS, vol. 57(6), pages 1483-1495, December.
    7. Karthik Natarajan & Dessislava Pachamanova & Melvyn Sim, 2009. "Constructing Risk Measures from Uncertainty Sets," Operations Research, INFORMS, vol. 57(5), pages 1129-1141, October.
    8. Aharon Ben-Tal & Boaz Golany & Arkadi Nemirovski & Jean-Philippe Vial, 2005. "Retailer-Supplier Flexible Commitments Contracts: A Robust Optimization Approach," Manufacturing & Service Operations Management, INFORMS, vol. 7(3), pages 248-271, February.
    9. Berman, Oded & Krass, Dmitry & Drezner, Zvi, 2003. "The gradual covering decay location problem on a network," European Journal of Operational Research, Elsevier, vol. 151(3), pages 474-480, December.
    10. Juan S. Borrero & Leonardo Lozano, 2021. "Modeling Defender-Attacker Problems as Robust Linear Programs with Mixed-Integer Uncertainty Sets," INFORMS Journal on Computing, INFORMS, vol. 33(4), pages 1570-1589, October.
    11. Poss, Michael, 2014. "Robust combinatorial optimization with variable cost uncertainty," European Journal of Operational Research, Elsevier, vol. 237(3), pages 836-845.
    12. Zvi Drezner & George O. Wesolowsky & Tammy Drezner, 2004. "The gradual covering problem," Naval Research Logistics (NRL), John Wiley & Sons, vol. 51(6), pages 841-855, September.
    13. Richard Church & Charles R. Velle, 1974. "The Maximal Covering Location Problem," Papers in Regional Science, Wiley Blackwell, vol. 32(1), pages 101-118, January.
    14. Gregory, Christine & Darby-Dowman, Ken & Mitra, Gautam, 2011. "Robust optimization and portfolio selection: The cost of robustness," European Journal of Operational Research, Elsevier, vol. 212(2), pages 417-428, July.
    15. A. L. Soyster, 1973. "Technical Note—Convex Programming with Set-Inclusive Constraints and Applications to Inexact Linear Programming," Operations Research, INFORMS, vol. 21(5), pages 1154-1157, October.
    16. Zhang, Jianjun & Hodgson, John & Erkut, Erhan, 2000. "Using GIS to assess the risks of hazardous materials transport in networks," European Journal of Operational Research, Elsevier, vol. 121(2), pages 316-329, March.
    17. Oded Berman & Zvi Drezner & Dmitry Krass, 2019. "The multiple gradual cover location problem," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 70(6), pages 931-940, June.
    18. Aharon Ben-Tal & Elad Hazan & Tomer Koren & Shie Mannor, 2015. "Oracle-Based Robust Optimization via Online Learning," Operations Research, INFORMS, vol. 63(3), pages 628-638, June.
    Full references (including those not matched with items on IDEAS)

    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. Juan S. Borrero & Leonardo Lozano, 2021. "Modeling Defender-Attacker Problems as Robust Linear Programs with Mixed-Integer Uncertainty Sets," INFORMS Journal on Computing, INFORMS, vol. 33(4), pages 1570-1589, October.
    2. Claire Nicolas & Stéphane Tchung-Ming & Emmanuel Hache, 2016. "Energy transition in transportation under cost uncertainty, an assessment based on robust optimization," Working Papers hal-02475943, HAL.
    3. Gabrel, Virginie & Murat, Cécile & Thiele, Aurélie, 2014. "Recent advances in robust optimization: An overview," European Journal of Operational Research, Elsevier, vol. 235(3), pages 471-483.
    4. Mengshi Lu & Zuo‐Jun Max Shen, 2021. "A Review of Robust Operations Management under Model Uncertainty," Production and Operations Management, Production and Operations Management Society, vol. 30(6), pages 1927-1943, June.
    5. Alireza Ghahtarani & Ahmed Saif & Alireza Ghasemi, 2021. "Robust Portfolio Selection Problems: A Comprehensive Review," Papers 2103.13806, arXiv.org, revised Jan 2022.
    6. Wenqing Chen & Melvyn Sim & Jie Sun & Chung-Piaw Teo, 2010. "From CVaR to Uncertainty Set: Implications in Joint Chance-Constrained Optimization," Operations Research, INFORMS, vol. 58(2), pages 470-485, April.
    7. Metzker Soares, Paula & Thevenin, Simon & Adulyasak, Yossiri & Dolgui, Alexandre, 2024. "Adaptive robust optimization for lot-sizing under yield uncertainty," European Journal of Operational Research, Elsevier, vol. 313(2), pages 513-526.
    8. Oğuz Solyalı & Jean-François Cordeau & Gilbert Laporte, 2016. "The Impact of Modeling on Robust Inventory Management Under Demand Uncertainty," Management Science, INFORMS, vol. 62(4), pages 1188-1201, April.
    9. Jiankun Sun & Jan A. Van Mieghem, 2019. "Robust Dual Sourcing Inventory Management: Optimality of Capped Dual Index Policies and Smoothing," Manufacturing & Service Operations Management, INFORMS, vol. 21(4), pages 912-931, October.
    10. Andrew J. Keith & Darryl K. Ahner, 2021. "A survey of decision making and optimization under uncertainty," Annals of Operations Research, Springer, vol. 300(2), pages 319-353, May.
    11. Sandra Cruz Caçador & Pedro Manuel Cortesão Godinho & Joana Maria Pina Cabral Matos Dias, 2022. "A minimax regret portfolio model based on the investor’s utility loss," Operational Research, Springer, vol. 22(1), pages 449-484, March.
    12. Andreas Thorsen & Tao Yao, 2017. "Robust inventory control under demand and lead time uncertainty," Annals of Operations Research, Springer, vol. 257(1), pages 207-236, October.
    13. Selim Mankai & Khaled Guesmi, 2014. "Robust Portfolio Protection: A Scenarios-Based Approach," Working Papers hal-04141326, HAL.
    14. Daphné Lorne & Stéphane Tchung-Ming, 2012. "The French biofuels mandates under cost uncertainty - an assesment based on robust optimization," Working Papers hal-03206367, HAL.
    15. Güray Kara & Ayşe Özmen & Gerhard-Wilhelm Weber, 2019. "Stability advances in robust portfolio optimization under parallelepiped uncertainty," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 27(1), pages 241-261, March.
    16. Jang Ho Kim & Woo Chang Kim & Frank J. Fabozzi, 2014. "Recent Developments in Robust Portfolios with a Worst-Case Approach," Journal of Optimization Theory and Applications, Springer, vol. 161(1), pages 103-121, April.
    17. Karatas, Mumtaz & Eriskin, Levent, 2021. "The minimal covering location and sizing problem in the presence of gradual cooperative coverage," European Journal of Operational Research, Elsevier, vol. 295(3), pages 838-856.
    18. Oğuz Solyalı & Jean-François Cordeau & Gilbert Laporte, 2012. "Robust Inventory Routing Under Demand Uncertainty," Transportation Science, INFORMS, vol. 46(3), pages 327-340, August.
    19. Alireza Ghahtarani & Ahmed Saif & Alireza Ghasemi, 2022. "Robust portfolio selection problems: a comprehensive review," Operational Research, Springer, vol. 22(4), pages 3203-3264, September.
    20. Caunhye, Aakil M. & Cardin, Michel-Alexandre, 2018. "Towards more resilient integrated power grid capacity expansion: A robust optimization approach with operational flexibility," Energy Economics, Elsevier, vol. 72(C), pages 20-34.

    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:inm:orijoc:v:35:y:2023:i:1:p:83-103. 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: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    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.