Date of Award
12-2025
Document Type
Dissertation
Degree Name
Doctor of Philosophy (PhD)
Department
Industrial Engineering
Committee Chair/Advisor
Dr. Emily Tucker
Committee Member
Dr. Yongjia Song
Committee Member
Dr. Hamed Rahimian
Committee Member
Dr. Thomas Sharkey
Abstract
Geopolitical strain has become a major driver of instability in global supply chains. High interdependence among countries has increased exposure to disruptions, including policy-induced disruptions such as export bans. These bans, often imposed to protect domestic supply, restrict international trade and limit access to essential goods worldwide. In the pharmaceutical industry, such disruptions threaten patient health, healthcare system performance and company operations. Despite these implications, existing supply chain optimization frameworks have not studied how to support company decision-making under geopolitical strain, including export bans, and there is a limited understanding of their firm-level effects. Unlike conventional disruptions, export bans often arise as secondary effects of supply interruptions, introducing new dynamics of global interdependence and uncertainty into supply chain planning. This dissertation addresses this gap by developing three optimization models for global supply chain design that incorporate export ban risks induced by capacity disruptions. This work focuses on the pharmaceutical industry, however the proposed models can be extended to other sectors. The first model integrates export ban risks triggered by a leading indicator of risk of shortage, i.e., the weighted average of global availability of raw materials. It also includes export ban-induced price increases, distinguishing between domestic and exported supply. The model is a two-stage stochastic program with continuous recourse. It is solved by integrating the Sample Average Approximation and the L-shaped methods. Structural properties are derived that identify the conditions under which demand will not be met and how supply is allocated between countries. With this model, policies, such as bilateral alliances, price supplements, and back-shoring strategies, are evaluated. The second model addresses the problem of global supply chain design under multi-type disruptions, including shortage-induced deterministic export bans, quality failures, and correlated natural disasters. It is formulated as a two-stage stochastic mixed-integer program, where the second stage contains one binary variable and continuous variables. This structure motivates tailored solution algorithms. A computational study is presented comparing the Alternating Integer L-shaped Cut, the Alternating Disjunctive Cut, and the Alternating Bilinear Cut methods, with results indicating that the Alternating Integer L-shaped Cut Method performs best for this near-continuous second-stage structure. The study further provides insights into the value of incorporating multi-type disruptions into supply chain planning. The third model extends the second formulation by considering shortage-induced stochastic export bans. In this model, endogenous (company) and exogenous (competitor) supply influence export ban risks, with lower global drug availability increasing the likelihood of such bans. A specific structure relating available drug supply to export ban probabilities is used for analyses. The model is first formulated as a three-stage stochastic program and then reformulated as a two-stage stochastic mixed-integer program. It is solved using the Alternating Integer L-shaped Method and enables the exploration of export ban risk intensity, modeling granularity, and market power. All models are evaluated through numerical experiments based on an oncology drug case study, offering practical insights. The results show that incorporating geopolitical strain into supply chain design improves resilience.
In summary, this dissertation advances the understanding of export ban risks induced by capacity disruptions and their effects on global pharmaceutical supply chains and drug shortages. It contributes new modeling frameworks for designing resilient supply chains under export ban risks and establishes a foundation for the emerging research area of supply chain exposure to geopolitical strain. The contributions span modeling, computational, and practical dimensions in supply chain optimization under disruptions.
Recommended Citation
Sabogal De La Pava, Martha L., "Stochastic Programming Approaches for Pharmaceutical Supply Chains Facing Geopolitical Strain" (2025). All Dissertations. 4134.
https://open.clemson.edu/all_dissertations/4134
Author ORCID Identifier
https://orcid.org/0000-0002-6223-3462