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Modeling and mitigating the effects of supply chain disruption in a defender–attacker game

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  • Jie Xu

    (SUNY at Buffalo)

  • Jun Zhuang

    (SUNY at Buffalo)

  • Zigeng Liu

    (Northwestern University)

Abstract

The outcomes of a defender–attacker game depend on the defender’s resources delivered through military supply chains. These are subject to disruptions from various sources, such as natural disasters, social disasters, and terrorism. The attacker and defender are at war; the defender needs resources to defeat the attacker, but those resources may not be available due to a supply chain disruption that occurs exogenously to the game. In this paper, we integrate a defender–attacker game with supply chain risk management, and study the defender’s optimal preparation strategy. We provide analytical solutions, conduct numerical analysis, and compare the combined strategy with other protection strategies. Our results indicate that: (a) the defender benefits in a defender–attacker game by utilizing supply chain risk management tools; and (b) the attacker’s best response resource allocation would not be deterred by capacity backup protection and/or inventory protection. The feature of this paper is that the defender, being the downstream user of the supply chain, is involved in a strategic contest against the attacker. This model is different than game theory applied to private-sector supply chains because most game theoretic models of private sector supply chains usually explore relationships between suppliers and firms in the same supply chain or between multiple firms competing in the marketplace for customers. Therefore, supply chain risk management for such a military application imposes effects that have not been studied before.

Suggested Citation

  • Jie Xu & Jun Zhuang & Zigeng Liu, 2016. "Modeling and mitigating the effects of supply chain disruption in a defender–attacker game," Annals of Operations Research, Springer, vol. 236(1), pages 255-270, January.
    • Handle: RePEc:spr:annopr:v:236:y:2016:i:1:d:10.1007_s10479-015-1810-z
    DOI: 10.1007/s10479-015-1810-z
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    Cited by:

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    3. Simon, Jay & Omar, Ayman, 2020. "Cybersecurity investments in the supply chain: Coordination and a strategic attacker," European Journal of Operational Research, Elsevier, vol. 282(1), pages 161-171.
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    5. Daniel Seaberg & Laura Devine & Jun Zhuang, 2017. "A review of game theory applications in natural disaster management research," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 89(3), pages 1461-1483, December.
    6. Marvin L. King & David R. Galbreath & Alexandra M. Newman & Amanda S. Hering, 2020. "Combining regression and mixed-integer programming to model counterinsurgency," Annals of Operations Research, Springer, vol. 292(1), pages 287-320, September.
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    8. Sanjoy Kumar Paul & Ruhul Sarker & Daryl Essam & Paul Tae-Woo Lee, 2019. "A mathematical modelling approach for managing sudden disturbances in a three-tier manufacturing supply chain," Annals of Operations Research, Springer, vol. 280(1), pages 299-335, September.
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