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The budget constrained r-interdiction median problem with capacity expansion

Author

Listed:
  • Deniz Aksen
  • Nuray Piyade
  • Necati Aras

Abstract

In this article, we elaborate on a budget constrained extension of the r-interdiction median problem with fortification (RIMF). The objective in the RIMF is to find the optimal allocation of protection resources to a given service system consisting of p facilities so that the disruptive effects of r possible attacks to the system are minimized. The defender of the system needs to fortify q facilities of the present system to offset the worst-case loss of r non-fortified facilities due to an interdiction in which the attacker’s objective is to cause the maximum possible disruption in the service level of the system. The defender-attacker relationship fits a bilevel integer programming (BIP) formulation where the defender and attacker take on the respective roles of the leader and the follower. We adopt this BIP formulation and augment it with a budget constraint instead of a predetermined number of facilities to be fortified. In addition, we also assume that each facility has a flexible service capacity, which can be expanded at a unit cost to accommodate the demand of customers who were serviced by some other interdicted facility before the attack. First, we provide a discrete optimization model for this new facility protection planning scenario with a novel set of closest assignment constraints. Then, to tackle this BIP problem we use an implicit enumeration algorithm performed on a binary tree. For each node representing a different fortification scheme, the attacker’s problem is solved to optimality using Cplex 11. We report computational results obtained on a test bed of 96 randomly generated instances. The article concludes with suggestions for future research. Copyright Springer-Verlag 2010

Suggested Citation

  • Deniz Aksen & Nuray Piyade & Necati Aras, 2010. "The budget constrained r-interdiction median problem with capacity expansion," 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. 18(3), pages 269-291, September.
  • Handle: RePEc:spr:cejnor:v:18:y:2010:i:3:p:269-291
    DOI: 10.1007/s10100-009-0110-6
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    References listed on IDEAS

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    1. Richard Church, 2003. "COBRA: A New Formulation of the Classic p-Median Location Problem," Annals of Operations Research, Springer, vol. 122(1), pages 103-120, September.
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    Cited by:

    1. Kaike Zhang & Xueping Li & Mingzhou Jin, 2022. "Efficient Solution Methods for a General r -Interdiction Median Problem with Fortification," INFORMS Journal on Computing, INFORMS, vol. 34(2), pages 1272-1290, March.
    2. Tanınmış, Kübra & Aras, Necati & Altınel, İ. Kuban, 2022. "Improved x-space algorithm for min-max bilevel problems with an application to misinformation spread in social networks," European Journal of Operational Research, Elsevier, vol. 297(1), pages 40-52.
    3. Sarhadi, Hassan & Tulett, David M. & Verma, Manish, 2017. "An analytical approach to the protection planning of a rail intermodal terminal network," European Journal of Operational Research, Elsevier, vol. 257(2), pages 511-525.
    4. Yiyong Xiao & Pei Yang & Siyue Zhang & Shenghan Zhou & Wenbing Chang & Yue Zhang, 2020. "Dynamic Gaming Case of the R-Interdiction Median Problem with Fortification and an MILP-Based Solution Approach," Sustainability, MDPI, vol. 12(2), pages 1-17, January.
    5. Bhuiyan, Tanveer Hossain & Medal, Hugh R. & Harun, Sarah, 2020. "A stochastic programming model with endogenous and exogenous uncertainty for reliable network design under random disruption," European Journal of Operational Research, Elsevier, vol. 285(2), pages 670-694.
    6. Nader Azad & Elkafi Hassini, 2019. "A Benders Decomposition Method for Designing Reliable Supply Chain Networks Accounting for Multimitigation Strategies and Demand Losses," Transportation Science, INFORMS, vol. 53(5), pages 1287-1312, September.
    7. Parajuli, Anubhuti & Kuzgunkaya, Onur & Vidyarthi, Navneet, 2017. "Responsive contingency planning of capacitated supply networks under disruption risks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 102(C), pages 13-37.
    8. Michael Stiglmayr & José Figueira & Kathrin Klamroth, 2014. "On the multicriteria allocation problem," Annals of Operations Research, Springer, vol. 222(1), pages 535-549, November.
    9. Ghaffarinasab, Nader & Motallebzadeh, Alireza, 2018. "Hub interdiction problem variants: Models and metaheuristic solution algorithms," European Journal of Operational Research, Elsevier, vol. 267(2), pages 496-512.
    10. Li, Qing & Li, Mingchu & Zhang, Runfa & Gan, Jianyuan, 2021. "A stochastic bilevel model for facility location-protection problem with the most likely interdiction strategy," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    11. Nicolas Fröhlich & Stefan Ruzika, 2022. "Interdicting facilities in tree networks," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 30(1), pages 95-118, April.
    12. Luohao Tang & Cheng Zhu & Zaili Lin & Jianmai Shi & Weiming Zhang, 2016. "Reliable Facility Location Problem with Facility Protection," PLOS ONE, Public Library of Science, vol. 11(9), pages 1-24, September.
    13. Parajuli, Anubhuti & Kuzgunkaya, Onur & Vidyarthi, Navneet, 2021. "The impact of congestion on protection decisions in supply networks under disruptions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 145(C).
    14. Ramamoorthy, Prasanna & Jayaswal, Sachin & Sinha, Ankur & Vidyarthi, Navneet, 2018. "Multiple allocation hub interdiction and protection problems: Model formulations and solution approaches," European Journal of Operational Research, Elsevier, vol. 270(1), pages 230-245.
    15. Girish Ch. Dey & Mamata Jenamani, 2019. "Optimizing fortification plan of capacitated facilities with maximum distance limits," OPSEARCH, Springer;Operational Research Society of India, vol. 56(1), pages 151-173, March.
    16. Sachuer Bao & Chi Zhang & Min Ouyang & Lixin Miao, 2019. "An integrated tri-level model for enhancing the resilience of facilities against intentional attacks," Annals of Operations Research, Springer, vol. 283(1), pages 87-117, December.
    17. Losada, Chaya & Scaparra, M. Paola & O’Hanley, Jesse R., 2012. "Optimizing system resilience: A facility protection model with recovery time," European Journal of Operational Research, Elsevier, vol. 217(3), pages 519-530.
    18. Ramamoorthy, Prasanna & Jayaswal, Sachin & Sinha, Ankur & Vidyarthi, Navneet, 2016. "Hub Interdiction & Hub Protection problems: Model formulations & Exact Solution methods. (Revised)," IIMA Working Papers WP2016-10-01, Indian Institute of Management Ahmedabad, Research and Publication Department.
    19. Chaya Losada & M. Scaparra & Richard Church & Mark Daskin, 2012. "The stochastic interdiction median problem with disruption intensity levels," Annals of Operations Research, Springer, vol. 201(1), pages 345-365, December.
    20. Kübra Tanınmış & Markus Sinnl, 2022. "A Branch-and-Cut Algorithm for Submodular Interdiction Games," INFORMS Journal on Computing, INFORMS, vol. 34(5), pages 2634-2657, September.
    21. Ghaffarinasab, Nader & Atayi, Reza, 2018. "An implicit enumeration algorithm for the hub interdiction median problem with fortification," European Journal of Operational Research, Elsevier, vol. 267(1), pages 23-39.
    22. Lazar Mrkela & Zorica Stanimirović, 2022. "A variable neighborhood search for the budget-constrained maximal covering location problem with customer preference ordering," Operational Research, Springer, vol. 22(5), pages 5913-5951, November.

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