Disrupting Illicit Supply Networks: Exploring Behavioral Responses in Narco-Trafficking Operating Networks in a Spatial Optimization and Simulation Testbed Environment

Keywords: spatial optimization, spatial decision support systems, interdiction
Session Type: Virtual Paper Abstract
Day: Sunday
Session Start / End Time: 2/27/2022 08:00 AM (Eastern Time (US & Canada)) - 2/27/2022 09:20 AM (Eastern Time (US & Canada))
Room: Virtual 6

Abstract

Cocaine- or ‘narco’-trafficking through the Central American corridor supplies over 80% of the cocaine consumed in North America. Despite numerous related national security concerns, efforts to stem the flow of cocaine into the U.S. have not been sufficiently successful. Recent advances within diverse fields, such as operations research, criminology, and data science, are advancing knowledge of the scope, structure, and history of cocaine demand and supply between cocaine production and consumption regions. However, there remain significant gaps in the understanding of the behavioral nature of the actors within the illicit drug trafficking networks, of the complex operational environment of those charged with disrupting those networks, and in the ability to model, predict, and plan for the outcomes of the interactions between these opposing forces. This work presents the effort to model these interactions in a replica testbed of the operational environment in such a way as to 1) access a range of solution procedures both heuristic and guaranteed optimal, 2) use the state-of-the-art data scientific techniques to manage the massive intermediate data generated by the solution procedures, and 3) support the analysis of results of tests of interdiction/trafficking behaviors over many scenarios. The testbed environment presented combines spatial analytic techniques, optimization, agent-based modeling, and high-performance computing in the context of military and law enforcement operations, in a manner not as of yet observed in the literature.