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CCP game: A game theoretical model for improving the scheduling of chemical cluster patrolling

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  • Zhang, Laobing
  • Reniers, Genserik
  • Chen, Bin
  • Qiu, Xiaogang

Abstract

Chemical clusters can be attractive targets for terrorism, due to the extreme importance of them as well as due to the existence of dangerous materials. Patrolling is scheduled for better securing chemical clusters. However, the current patrolling strategies fail on competing with intelligent attackers and therefore can be non-optimal. The so-called chemical cluster patrolling (CCP) game is proposed in this paper. The CCP game employs game theory as a methodology, aiming at randomly but strategically scheduling security patrols in chemical clusters. The patroller and the attacker are modelled as the two rational players in the CCP game. The patroller's strategy is defined as probabilistically traveling within the cluster or patrolling some plants while the attacker's strategy is formulated as a combination of an attack target, the start time of the attack, and the attack scenario to be used. The Stackelberg equilibrium and a robust solution which takes into consideration of the patroller's distribution-free uncertainties on the attacker's parameters are defined for predicting the outcome of the CCP game. Results of the case study indicate that the patrolling strategy suggested by the CCP game outperforms both the fixed patrolling route strategy and the purely randomized patrolling strategy.

Suggested Citation

  • Zhang, Laobing & Reniers, Genserik & Chen, Bin & Qiu, Xiaogang, 2019. "CCP game: A game theoretical model for improving the scheduling of chemical cluster patrolling," Reliability Engineering and System Safety, Elsevier, vol. 191(C).
  • Handle: RePEc:eee:reensy:v:191:y:2019:i:c:s0951832018303314
    DOI: 10.1016/j.ress.2018.06.014
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    References listed on IDEAS

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    1. Laobing Zhang & Genserik Reniers, 2016. "A Game‐Theoretical Model to Improve Process Plant Protection from Terrorist Attacks," Risk Analysis, John Wiley & Sons, vol. 36(12), pages 2285-2297, December.
    2. Reniers, G.L.L. & Sörensen, K. & Khan, F. & Amyotte, P., 2014. "Resilience of chemical industrial areas through attenuation-based security," Reliability Engineering and System Safety, Elsevier, vol. 131(C), pages 94-101.
    3. Landucci, Gabriele & Reniers, Genserik & Cozzani, Valerio & Salzano, Ernesto, 2015. "Vulnerability of industrial facilities to attacks with improvised explosive devices aimed at triggering domino scenarios," Reliability Engineering and System Safety, Elsevier, vol. 143(C), pages 53-62.
    4. van Staalduinen, Mark Adrian & Khan, Faisal & Gadag, Veeresh & Reniers, Genserik, 2017. "Functional quantitative security risk analysis (QSRA) to assist in protecting critical process infrastructure," Reliability Engineering and System Safety, Elsevier, vol. 157(C), pages 23-34.
    5. Argenti, Francesca & Landucci, Gabriele & Reniers, Genserik & Cozzani, Valerio, 2018. "Vulnerability assessment of chemical facilities to intentional attacks based on Bayesian Network," Reliability Engineering and System Safety, Elsevier, vol. 169(C), pages 515-530.
    6. Katerina Papadaki & Steve Alpern & Thomas Lidbetter & Alec Morton, 2016. "Patrolling a Border," Operations Research, INFORMS, vol. 64(6), pages 1256-1269, December.
    7. Genserik Reniers & Yulia Pavlova, 2013. "Using Game Theory to Improve Safety within Chemical Industrial Parks," Springer Series in Reliability Engineering, Springer, edition 127, number 978-1-4471-5052-7, January.
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    Cited by:

    1. Wang, Jian & Cui, Lei, 2023. "Patrolling games with coordination between monitoring devices and patrols," Reliability Engineering and System Safety, Elsevier, vol. 233(C).
    2. Tao Zeng & Guohua Chen & Yunfeng Yang & Genserik Reniers & Yixin Zhao & Xia Liu, 2020. "A Systematic Literature Review on Safety Research Related to Chemical Industrial Parks," Sustainability, MDPI, vol. 12(14), pages 1-27, July.
    3. Dong, Mingxin & Zhang, Zhen & Liu, Yi & Zhao, Dong Feng & Meng, Yifei & Shi, Jihao, 2023. "Playing Bayesian Stackelberg game model for optimizing the vulnerability level of security incident system in petrochemical plants," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
    4. Casson Moreno, Valeria & Marroni, Giulia & Landucci, Gabriele, 2022. "Probabilistic assessment aimed at the evaluation of escalating scenarios in process facilities combining safety and security barriers," Reliability Engineering and System Safety, Elsevier, vol. 228(C).

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