D-ISN: TRACK 1: Collaborative Research: Discovery, Analysis, and Disruption of Illicit Narcotic Supply Networks

Michigan State University, East Lansing MI

Investigators

Abstract

As transnational drug cartels continue to grow in size and scope, their trafficking networks have become more complex and fragmented. This Disrupting Operations of Illicit Supply Networks (D-ISN) project takes a multi-disciplinary, scientific approach to build better insight and optimization of counter-narcotics efforts in the United States. It refines analytic methods to develop an understanding of the network structure and models of the flow of cocaine, which supports disruption strategies of anti-narcotics and other law enforcement agencies. The project analyzes the dynamics of narcotic supply networks and how interdiction strategies disrupt these networks. Employing a convergent approach that combines operations research, computer science, criminology, public policy, geographic, and economic perspectives, this research exploits network analysis of temporal and spatial cocaine price data to infer illicit supply chain network structure and flow. Artificial intelligence and learning models are applied on the empirical data to extract network behavior in response to interdiction activities, while game theoretic models blend combinatorial optimization and agent-based simulation to evaluate the outcomes of various interdiction strategies. Results will be integrated into a network optimization model to explain the structure of illicit drug supply chains and provide evidence to support successful disruption strategies. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.