Designing Antifragile Supply Chain Networks under Polycrisis: A Problem-Driven Agent-Based Model for Circular Rewiring

This study addresses a critical challenge in management science and operations analytics: designing supply chain networks capable of withstanding severe, systemic disruptions (polycrisis). Traditional centralized supply chains, optimized for steady-state efficiency, are highly vulnerable to cascading failures under extreme stress. To resolve the structural tension between operational efficiency and systemic resilience, we conceptualize decentralized circular rewiring as a core mechanism for network Antifragility. Given the unprecedented nature of modern systemic shocks, where historical empirical data is often insufficient to predict failure propagation, this study develops a problem-driven Agent-Based Model (ABM). Calibrated with empirical volatility data from the automotive sector (2011-2021), the simulation evaluates the viability of different network topologies. The results demonstrate that under extreme shock scenarios, decentralized adaptive networks utilizing local circular resource loops maintain 88.6% system viability, whereas centralized linear models suffer total collapse. Crucially, the model mathematically identifies an economic tipping point: a specific rewiring cost ( ) threshold beyond which the transactional friction of network reconfiguration negates its operational benefits. Ultimately, this study provides supply chain managers with an operations analytics framework and a quantifiable decision-support roadmap for restructuring fragile linear supply chains into antifragile, regenerative networks. .