Mitigation of Optimized Pharmaceutical Supply Chain Disruptions by Criminal Agents Abhisekh Rana 1(B ) , Hamdi Kavak 1 , Andrew Crooks 2 , Sean Luke 1 , Carlotta Domeniconi 1 , and Jim Jones 1 1 George Mason University, Fairfax, VA 22030, USA {arana6,sean,cdomenic,jjonesu}@gmu.edu 2 University at Buffalo, Buffalo, NY 14261, USA atcrooks@buffalo.edu Abstract. Disruption to supply chains can significantly influence the operation of the world economy and this has been shown to permeate and affect a large majority of countries and their citizens. We present ini- tial results from a model that explores the disruptions to supply chains by a criminal agent and possible mitigation strategies. We construct a model of a typical pharmaceutical manufacturing supply chain, which is implemented via discrete event simulation. The criminal agent optimizes its resource allocation to maximize disruption to the supply chain. Our findings show criminal agents can cause cascading damage and exploit vulnerabilities, which inherently exist within the supply chain itself. We also demonstrate how basic mitigation strategies can efficaciously allevi- ate this potential damage. Keywords: Pharmaceutical supply chains · Criminal agents · Evolutionary computation · Mitigation 1 Introduction and Background Supply chains are a critical part of modern society and the operation of the world economy. Recently, the COVID-19 pandemic has brought supply chains and disruptions to them front and center. These disruptions have not only led to massive shortages in critical goods such as semi-conductors, personal protective equipment and medical supplies, but also impacted the roll out of vaccinations [3, 12].Though the effects of disruptions to supply chains by natural disasters have been well studied (e.g., [6]), potential disruptions to their operations by nefarious criminal agents remains an area of limited research [9]. In this paper, we discuss our initial study of the effects of disruptions by a criminal agent to pharmaceutical supply chains and ways to mitigate their impact. We have developed a discrete event simulation model of a supply chain for drug production drawn from real systems in the pharmaceutical industry c  The Author(s), under exclusive license to Springer Nature Switzerland AG 2022 R. Thomson et al. (Eds.): SBP-BRiMS 2022, LNCS 13558, pp. 13–23, 2022. https://doi.org/10.1007/978-3-031-17114-7_2