A family of models in support of realistic drug interdiction location decision?making

Long-standing federal drug-control policy aims to reduce the flow of narcotics into USA, in part by intercepting cocaine shipments en route from South American production regions North consumer markets. Drug interdiction efforts operate over a large geographic area, containing complex drug trafficking networks dynamic environment. The extant models operations research and location science literature do not realistically model objectives constraints on forces, therefore counterdrug organizations employ those their decision-making processes. This article presents three new built maximal covering problem (MCLP): for (MCLP-I), multiple-demand (MD-MCLP), multiple-type (MT-MCLP). These are novel formulations that permit multiple types demands facilities be covered, utility these is demonstrated context operations. Optimal locations determined within geography Central transit zone, using coupled GIS optimization framework. results identify optimal known or estimated can constrain differentiating among traffickers, resources, agency jurisdictions. both demonstrates flexibility designing alternative scenarios may extended other application areas operational contexts.