Abstract
Due to economies of scale and all kinds of collaboration benefits, chemical plants are usually geographically clustered, forming chemical industrial parks or so-called ‘chemical clusters’. Some examples of such clusters are the Antwerp port chemical cluster in Belgium, the Rotterdam port chemical cluster in the Netherlands, the Houston chemical cluster in the US, or the Tianjin chemical cluster in China. Besides fixed security countermeasures within every plant, the patrolling of security guards is also scheduled, for securing these chemical facilities at different points and times, e.g. at night. The patrolling can either be single-plant oriented, which can be completely scheduled by the plant itself, or it can be multiple-plants oriented, which should be scheduled by an institute at a higher level than the single-plant level, for instance a multiple plant council (MPC) [1] Both types of patrolling have a drawback of not being able to deal with intelligent attackers. Some patrollers follow a fixed patrolling route, and in this case the adversary is able to predict the patroller’s position at a certain time. Other patrollers purely randomize their patrolling, without taking into consideration the hazardousness level that each installation/facility/plant holds, and if this is the case, the adversary may focus to attack the most dangerous installations/facilities/plants since all installations/facilities/plants are equally patrolled.
This chapter is mainly based on the paper of Zhang and Reniers [6]
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Reniers G, Pavlova Y. Using game theory to improve safety within chemical industrial parks. London: Springer; 2013.
Shieh E, An B, Yang R, Tambe M, Baldwin C, DiRenzo J, et al., editors. Protect: a deployed game theoretic system to protect the ports of the United States. In: Proceedings of the 11th international conference on autonomous agents and multiagent systems-volume 1. International Foundation for Autonomous Agents and Multiagent Systems; 2012.
Fang F, Stone P, Tambe M, editors. When security games go green: designing defender strategies to prevent poaching and illegal fishing. IJCAI; 2015.
Rezazadeh A, Zhang L, Reniers G, Khakzad N, Cozzani V. Optimal patrol scheduling of hazardous pipelines using game theory. Process Saf Environ Prot. 2017;109:242–56.
Alpern S, Morton A, Papadaki K. Patrolling games. Oper Res. 2011;59(5):1246–57.
Zhang L, Reniers G. CCP game: a game-theoretical model for improving chemical clusters patrolling. Accepted for publication in Reliability Engineering and System Safety; 2018.
API. Security risk assessment methodology for the petroleum and petrochemical industries. In: 780 ARP, editor. 2013.
Conitzer V, Sandholm T, editors. Computing the optimal strategy to commit to. In: Proceedings of the 7th ACM conference on Electronic commerce. ACM; 2006.
Nguyen TH, Jiang AX, Tambe M, editors. Stop the compartmentalization: unified robust algorithms for handling uncertainties in security games. In: Proceedings of the 2014 international conference on autonomous agents and multi-agent systems. International Foundation for Autonomous Agents and Multiagent Systems; 2014.
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG, part of Springer Nature
About this chapter
Cite this chapter
Zhang, L., Reniers, G. (2018). Multi-plant Protection: A Game-Theoretical Model for Improving Chemical Clusters Patrolling. In: Game Theory for Managing Security in Chemical Industrial Areas. Advanced Sciences and Technologies for Security Applications. Springer, Cham. https://doi.org/10.1007/978-3-319-92618-6_6
Download citation
DOI: https://doi.org/10.1007/978-3-319-92618-6_6
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-92617-9
Online ISBN: 978-3-319-92618-6
eBook Packages: Economics and FinanceEconomics and Finance (R0)