<![CDATA[Optimization studies often report cost savings under deterministic conditions, leaving their robustness to real-world uncertainty insufficiently explored. This study evaluates the robustness of a previously developed Mixed-Integer Linear Programming (MILP) procurement model for Company XYZ, a protective apparel manufacturer operating in Madagascar’s Export Processing Zone. The model is stress-tested under three scenarios: adverse supplier cost shifts, demand fluctuations of ±15%, and the loss of the lowest-cost supplier in each material category. Across five material categories, the optimal supplier allocation remains robust to moderate cost and demand shocks. However, supplier disruptions reveal substantial differences in resilience across materials. Thread and fabric retain most of their cost savings, whereas zippers, buckles, and Velcro lose most or all of their cost advantage when their lowest-cost supplier becomes unavailable. These findings demonstrate that supplier-diversification constraints can limit exposure to supplier-related risks but are insufficient to ensure procurement resilience. The study also identifies material categories where backup-supplier qualification should be prioritized to strengthen supply chain resilience while preserving procurement cost advantages. Keywords: Supply Chain Resilience; Sensitivity Analysis; Supplier Disruption; Procurement Optimization; Mixed-Integer Linear Programming]]>
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