Dynamic Shock Recovery in IO Networks with Priority Constraints

2025-04-23

AI Summary

This paper addresses cascading disruptions and dynamic recovery in global supply chains triggered by physical climate and geophysical risks—such as droughts, floods, and earthquakes. We propose the first dynamic input-output (IO) model capable of capturing both progressive propagation of shocks and synchronous recovery across sectors. Methodologically, the framework integrates structured IO network modeling, a novel constrained optimization rationing algorithm (“Priority with Constraint”) ensuring minimum supply to all customers, and simulations of demand stickiness and inventory buffering. Key findings reveal that the alignment between supply and demand recovery rates critically determines both the depth and duration of economic disruption; moreover, industry-proportional rationing exhibits an intrinsic buffering effect. The study delivers a quantifiable theoretical framework and algorithmic toolkit for designing resilient supply chains and informing optimal timing of policy interventions.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Reasoning under Uncertainty: Stochastic Optimization
• Constraint Satisfaction and Optimization: Distributed CSP/Optimization

Application Category

• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web

Abstract

Physical risks, such as droughts, floods, rising temperatures, earthquakes, infrastructure failures, and geopolitical conflicts, can ripple through global supply chains, raising costs, and constraining production across industries. Assessing these risks requires understanding not only their immediate effects, but also their cascading impacts. For example, a localized drought can disrupt the supply of critical raw materials such as cobalt or copper, affecting battery and electric vehicle production. Similarly, regional conflicts can impede cross-border trade, leading to broader economic consequences. Building on an existing model of simultaneous supply and demand shocks, we introduce a new propagation algorithm, Priority with Constraint, which modifies standard priority-based rationing by incorporating a minimum supply guarantee for all customers, regardless of their size or priority ranking. We also identify a buffer effect inherent in the Industry Proportional algorithm, which reflects real-world economic resilience. Finally, we extend the static shock propagation model to incorporate dynamic processes. We introduce mechanisms for gradual shock propagation, reflecting demand stickiness and the potential buffering role of inventories, and gradual recovery, modeling the simultaneous recovery of supply capacity and the inherent tendency for demand to return to pre-shock levels. Simulations demonstrate how the interplay between demand adjustment speed and supply recovery speed significantly influences the severity and duration of the economic impact after a shock.

Problem

• Assessing cascading impacts of physical risks on global supply chains
• Introducing Priority with Constraint algorithm for shock propagation
• Modeling dynamic shock recovery with demand and supply adjustments

Innovation

• Priority with Constraint algorithm for shock propagation
• Dynamic shock propagation with gradual recovery
• Buffer effect in Industry Proportional algorithm