A Family of Models in Support of Realistic Drug Interdiction Location Decision Making

Keywords: consolidated counterdrug database, counterdrug interdiction, location covering models, spatial optimization
Session Type: Virtual Paper Abstract
Day: Monday
Session Start / End Time: 2/28/2022 02:00 PM (Eastern Time (US & Canada)) - 2/28/2022 03:20 PM (Eastern Time (US & Canada))
Room: Virtual 26

Abstract

Longstanding federal drug-control policy aims to reduce the flow of narcotics into the US, in part, by intercepting cocaine shipments en route from South American production regions to North American consumer markets. Drug interdiction efforts operate over a large geographic area, containing complex drug trafficking networks, in a dynamic environment. The extant interdiction models in the operations research and location science literature do not realistically model the objectives and constraints on the interdiction forces, and therefore counterdrug organizations do not employ those models in their decision-making processes. This article presents three new models built on the Maximal Covering Location Problem (MCLP): Maximal Covering for Interdiction (MCI), Maximal Covering for Interdiction of Cartels (MCIC), and Multiple Type Maximal Covering for Interdiction (MTMCI). These models identify the optimal interdiction locations given known or estimated drug shipments and can constrain the location by differentiating among drug traffickers, the types of interdiction resources, and agency jurisdictions. Optimal interdiction locations are determined within the geography of the Central American transit zone, within a coupled GIS and optimization framework. This research both demonstrates the flexibility in designing alternative interdiction scenarios and presents novel covering models that may be extended to other application areas.