Scenario-Based CVaR Stress-Testing for Supply Network Design under Tariff and Sanction Uncertainty
Received: 26 February 2026 | Revised: 3 April 2026 | Accepted: 17 April 2026 | Online: 6 June 2026
Corresponding author: Sivalingam Thangavel
Abstract
Global distribution networks that are cost-effective under stable trade policy can become fragile when tariffs change rapidly or sanctions remove feasible trade lanes. This paper proposes a decision-analytic stress-testing framework for hub-and-lane supply network design under joint tariff and sanction uncertainty. A scenario-based mixed-integer programming model is formulated with here-and-now strategic decisions (hub opening and lane activation) and scenario-contingent recourse decisions (flow allocation with unmet-demand penalties) after a disruption state is realized. Tariff uncertainty is represented through scenario-dependent transportation cost adjustments, whereas sanction uncertainty is represented as explicit lane prohibitions that alter the feasible set. The model is parameterized using 2023 product-level HS6 trade-flow data (HS6 851712) as a demand proxy and evaluated across discrete tariff–sanction scenarios with equal weights for stress-testing. Downside exposure is quantified using Conditional Value-at-Risk (CVaR), enabling reporting of tail-cost outcomes alongside expected performance. Computational results show that, in the calibrated instance, the optimal hub footprint and activated lanes remain unchanged across the tested risk settings, suggesting structural robustness to the modeled tariff cost inflation and sanction-driven feasibility loss. A replication package is provided to reproduce the reported computational results.
Keywords:
supply network design, tariffs, sanctions, geopolitical risk, CVaR, scenario analysis, mixed-integer programming, distribution network designReferences
L. Dong and P. Kouvelis, "Impact of Tariffs on Global Supply Chain Network Configuration: Models, Predictions, and Future Research," Manufacturing & Service Operations Management, vol. 22, no. 1, pp. 25–35, Jan. 2020.
A. Nikian, H. Khademi Zare, M. M. Lotfi, and M. S. Fallah Nezhad, "Redesign of a sustainable and resilient closed-loop supply chain network under uncertainty and disruption caused by sanctions and COVID-19," Operations Management Research, vol. 16, no. 2, pp. 1019–1042, June 2023.
L. V. Snyder, Z. Atan, P. Peng, Y. Rong, A. J. Schmitt, and B. Sinsoysal, "OR/MS models for supply chain disruptions: a review," IIE Transactions, vol. 48, no. 2, pp. 89–109, Feb. 2016.
M. T. Melo, S. Nickel, and F. Saldanha-da-Gama, "Facility location and supply chain management – A review," European Journal of Operational Research, vol. 196, no. 2, pp. 401–412, July 2009.
L. V. Snyder and M. S. Daskin, "Reliability Models for Facility Location: The Expected Failure Cost Case," Transportation Science, vol. 39, no. 3, pp. 400–416, Aug. 2005.
M. S. Shahbaz, S. Sohu, F. Z. Khaskhelly, A. Bano, and M. A. Soomro, "A Novel Classification of Supply Chain Risks: A Review," Engineering, Technology & Applied Science Research, vol. 9, no. 3, pp. 4301–4305, June 2019.
L. Bednarski, S. Roscoe, C. Blome, and M. C. Schleper, "Geopolitical disruptions in global supply chains: a state-of-the-art literature review," Production Planning & Control, vol. 36, no. 4, pp. 536–562, Mar. 2025.
J. R. Birge and F. Louveaux, Introduction to Stochastic Programming, 2nd ed. New York, NY, USA: Springer, 2011.
A. Shapiro, D. Dentcheva, and A. Ruszczyński, Lectures on Stochastic Programming: Modeling and Theory, 2nd ed. Philadelphia, PA, USA: Society for Industrial and Applied Mathematics, 2014.
R. T. Rockafellar and S. Uryasev, "Optimization of conditional value-at-risk," Journal of Risk, vol. 2, no. 3, pp. 21–41, Mar. 2000.
R. T. Rockafellar and S. Uryasev, "Conditional value-at-risk for general loss distributions," Journal of Banking & Finance, vol. 26, no. 7, pp. 1443–1471, July 2002.
H. Soleimani and K. Govindan, "Reverse logistics network design and planning utilizing conditional value at risk," European Journal of Operational Research, vol. 237, no. 2, pp. 487–497, Sept. 2014.
D. Bertsimas and M. Sim, "The Price of Robustness," Operations Research, vol. 52, no. 1, pp. 35–53, Feb. 2004.
G. Gaulier and S. Zignago, "BACI: International Trade Database at the Product-Level. The 1994-2007 Version," CEPII, Paris, France, Working Papers 2010–23, Oct. 2010. [Online]. Available: https://www.cepii.fr/CEPII/en/bdd_modele/bdd_modele_item.asp?id=37.
S. Thangavel, "Replication Package: Scenario-Based CVaR Stress-Testing for Supply Network Design under Tariff and Sanction Uncertainty." Zenodo, Feb. 12, 2026.
S. Mitchell, M. O’Sullivan, and I. Dunning, "PuLP: A Linear Programming Toolkit for Python." Optimization Online, Sept. 22, 2011. [Online]. Available: https://optimization-online.org/?p=11731.
johnjforrest et al., "coin-or/Cbc: Version 2.10.5." Zenodo, Mar. 08, 2020.
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