Interdicting Restructuring Networks with Applications in Illicit Trafficking

Abstract

We consider a new class of max flow network interdiction problems, where the defender is able to introduce new arcs to the network after the attacker has made their interdiction decisions. We provide an example of when interdiction can result in an increase to the maximum flow, and prove properties of when this restructuring will not increase the value of the minimum cut, which has important practical interpretations for problems of disrupting drug or human trafficking networks. In particular, it demonstrates that disrupting lower levels of these networks will not impact their operations when replacing the disrupted participants is easy. For the bilevel mixed integer linear programming formulation of this problem, we devise a column-and-constraint generation (C&CG) algorithm to solve it. Our approach uses partial information on the feasibility of restructuring plans and is shown to be orders of magnitude faster than previous C&CG methods. We apply this algorithm to the application of disrupting drug trafficking networks. We demonstrate that applying decisions from standard max flow network interdiction problems can result in significantly higher flows than interdictions that account for the restructuring. We also show that interdicting lower level participants is less impactful when recruitment of new participants is allowed.

A Transdisciplinary Approach for Generating Synthetic but Realistic Domestic Sex Trafficking Networks

“…This paradox aligns with the theoretical analysis in Kosmas et al (Kosmas et al 2020), where they observed that current law enforcement policy typically recommended interdicting participants in drug smuggling networks that would trigger restructuring arcs that would cross the minimum cut. We find that a similar situation occurs for our conceptualizations of sex trafficking networks, thus indicating that both disrupting current operations and their ability to restructure (especially recruit) is critial.…”

“…The other player, the defender, then operates the network as per the max flow problem. Max flow network interdiction has successfully been applied to disrupting illicit drug trafficking networks (Baycik et al 2018, Malaviya et al 2012, Shen et al 2021, Kosmas et al 2020, and has been identified as an analytical tool to help address sex trafficking (Smith & Song 2020). Some max flow network interdiction models have been proposed for disrupting human trafficking (Mayorga et al 2019, Tezcan & Maass 2020.…”

“…Some max flow network interdiction models have been proposed for disrupting human trafficking (Mayorga et al 2019, Tezcan & Maass 2020. We apply the model of Kosmas et al (Kosmas et al 2020), max flow network interdiction with restructuring (MFNIP-R), to sample outputs of our network generator. Their model accounts for how drug traffickers will respond to disruption efforts.…”

“…Kosmas et al (Kosmas et al 2020) defines MFNIP-R as the following. Given a network G = (N, A) with source node s, sink node t, set of restructure-able arcs A R , and node and arc capacities…”

Improving Access to Housing and Supportive Services for Runaway and Homeless Youth: Reducing Vulnerability to Human Trafficking in New York City

“…Research related to OR and analytics efforts to reduce homelessness and the supply of sex and labor trafficking victims has only recently received attention and largely focus on three broad areas: the scope of the problem (Kosmas et al, 2020;Brelsford and Parakh, 2018), frameworks for addressing the crisis (Taylor, 2018;Kővári and Pruyt, 2014), and appropriate allocation of scarce resources to combat HT and homelessness (Chan et al, 2018;Petry et al, 2021). A second body of OR literature focuses on detection of hidden HT victims (Keskin et al, 2021;Kapoor et al, 2017;Mensikova and Mattmann, 2017), movement patterns of covert traffickers (McDonald et al, 2021;Yao et al, 2021;Amin, 2010) and long-term intervention approaches to prevent trafficking or retrafficking by increasing the efficiency and effectiveness of public services (Amadasun, 2020), as well as improving access to supportive and rehabilitative services (Azizi et al, 2018).…”