Robust global supply chain reconfiguration under tariff and geopolitical uncertainty
Abstract
Global supply chains are increasingly exposed to trade policy shocks and physical disruptions arising from common geopolitical events. We develop a robust optimization framework with two decision stages for strategic supply chain reconfiguration. Supplier qualification and transportation arc activation decisions are made before uncertainty is realized, while operational flows adapt afterward. Geopolitical uncertainty is represented through country level shocks that can jointly trigger tariff escalation, policy induced restrictions on cross border capacity, facility disruptions, and physical transportation failures. The resulting min max min problem is reformulated by dualizing the operational recourse problem, yielding a nonconvex mixed integer bilinear adversarial problem solved within a column and constraint generation procedure. Comparison with complete enumeration verifies the implementation on small instances, while experiments on 60 synthetic supply chain networks of varying sizes assess computational performance. The results show that omitting geopolitical transmission channels during strategic design can lead to substantial deterioration in cost and service under full geopolitical stress. Broader protection is achieved primarily through changes in transportation network configuration rather than increased supplier qualification. Robust performance also depends on the severity and composition of geopolitical consequences, with restrictions on cross border capacity exerting a stronger effect than comparable proportional changes in tariff severity over the tested ranges. A geographically grounded case analysis further shows that the value of individual uncertainty channels depends on network structure and geographic exposure.
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BibTeX
@misc{chandra2026robust,
title = {{Robust global supply chain reconfiguration under tariff and geopolitical uncertainty}},
author = {Ashish Chandra},
howpublished = {arXiv},
year = {2026},
month = oct,
doi = {10.48550/arxiv.2610.36977},
eprint = {2610.36977},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2610.36977},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - Robust global supply chain reconfiguration under tariff and geopolitical uncertainty
AU - Ashish Chandra
PY - 2026
DA - 2026/10/27
PB - arXiv
DO - 10.48550/arxiv.2610.36977
UR - https://arxiv.org/abs/2610.36977
AB - Global supply chains are increasingly exposed to trade policy shocks and physical disruptions arising from common geopolitical events. We develop a robust optimization framework with two decision stages for strategic supply chain reconfiguration. Supplier qualification and transportation arc activation decisions are made before uncertainty is realized, while operational flows adapt afterward. Geopolitical uncertainty is represented through country level shocks that can jointly trigger tariff escalation, policy induced restrictions on cross border capacity, facility disruptions, and physical transportation failures. The resulting min max min problem is reformulated by dualizing the operational recourse problem, yielding a nonconvex mixed integer bilinear adversarial problem solved within a column and constraint generation procedure. Comparison with complete enumeration verifies the implementation on small instances, while experiments on 60 synthetic supply chain networks of varying sizes assess computational performance. The results show that omitting geopolitical transmission channels during strategic design can lead to substantial deterioration in cost and service under full geopolitical stress. Broader protection is achieved primarily through changes in transportation network configuration rather than increased supplier qualification. Robust performance also depends on the severity and composition of geopolitical consequences, with restrictions on cross border capacity exerting a stronger effect than comparable proportional changes in tariff severity over the tested ranges. A geographically grounded case analysis further shows that the value of individual uncertainty channels depends on network structure and geographic exposure.
ER -