Date of Award

8-2025

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Industrial Engineering

Committee Chair/Advisor

Thomas C. Sharkey (Co-advisor)

Committee Member

Yongjia Song (Co-advisor)

Committee Member

Emily L. Tucker

Committee Member

Hamed Rahimian

Abstract

In this dissertation, we study a series of bilevel network interdiction problems motivated by applications in human trafficking disruption. First, we consider a bilevel network interdiction problem where the follower aims to maximize the amount of flow from the source node to the sink node and the leader aims to minimize the number of arcs from a critical set that have positive flow on them in the solution obtained by the follower. This problem models the situation where an anti-trafficking agent wants to minimize the number of people affected by the trafficking operations whereas the trafficker wants to maximize trafficking revenue. We consider both the optimistic and pessimistic variants of this bilevel optimization problem and develop their respective single-level reformulations. Next, we study three bi-objective bilevel network interdiction models involving a coalition of anti-trafficking agents, who aim to optimize key metrics by removing individuals from a sex trafficking network, and traffickers, who seek to maximize their trafficking revenue. Then, we investigate a robust bilevel network interdiction problem where the follower, who operates the network, solves a minimum cost flow problem, and the leader, who interdicts the network, minimizes the total flow on arcs from a special set in the solution obtained by the follower. The problem includes uncertainty as the leader does not know the follower’s operational cost but only knows that it belongs to an uncertainty set. For each problem, we present solution methods and conduct extensive computational experiments to draw computational and domain-specific insights.

Author ORCID Identifier

https://orcid.org/0000-0001-5140-1064

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