Interdiction Models to Disrupt the Operations of Sex Trafficking and Other Forced Illicit Labor Networks

Author

Michael T. ClarkFollow

Date of Award

5-2022

Document Type

Thesis

Degree Name

Master of Science (MS)

Department

Industrial Engineering

Committee Chair/Advisor

Dr. Thomas Sharkey

Committee Member

Dr. Scott Mason

Committee Member

Dr. Yongjia Song

Abstract

Sex traffickers often force their victims to work in both commercial sex markets and perform other illicit activities (e.g., drug dealing, theft, and fraud). Current literature has failed to address interdiction models that aim to disrupt all components of a sex traffickers’ operation, including these other illicit activities. In this thesis, we present a interdiction problem, and its single-level linear optimization reformulation, to reduce the profit of a human trafficking network concurrently operating in the commercial sex market and other illicit activity markets. Our novel formulation aims to investigate the practical implications of interdiction decisions made to disrupt a human sex trafficking network operating in several illicit markets. Our work directly models inputs given by our Modeling Effective Network Disruptions (MEND) Advisory Group, whom are domain-level experts in the operations of sex trafficking networks. These suggestions highlight how sex traffickers will force victims to perform other illicit activities in addition to their commercial sex work. Once our interdiction model was created, we investigated several practical disruptions activities that reduced the capacity a victim could work in a targeted market which significantly reduced the profit of the trafficker. Our results show the importance of focusing interdiction activities on disrupting markets in which trafficker could potentially operate, especially market-level disruptions that reduce demand for commercial sex.

Recommended Citation

Clark, Michael T., "Interdiction Models to Disrupt the Operations of Sex Trafficking and Other Forced Illicit Labor Networks" (2022). All Theses. 3718.
https://open.clemson.edu/all_theses/3718