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Recent geopolitical shifts have forced supply chains toward resilient, dual-sourcing strategies, trading continuous nearshore costs for crisis mitigation. We model this trade-off using a continuous-time optimal control framework with regime switching. Crucially, the transition rates between normal and disrupted regimes are endogenous to the firm’s accumulated nearshore capacity. We employ Physics-Informed Neural Networks to solve the model numerically, yielding insights into optimal capacity scaling and operational resilience under endogenous macroeconomic risk.

Keywords: Resilience; Dual Sourcing; Optimal Control; Regime-Switching; Neural Network