Year: 2025
Type: preprint
Abstract: Modelling how shocks propagate in supply chains is an increasingly important challenge in economics. Its relevance has been highlighted in recent years by events such as Covid-19 and the Russian invasion of Ukraine. Agent-based models (ABMs) are a promising approach for this problem. However, calibrating them is hard. We show empirically that it is possible to achieve speed ups of over 3 orders of magnitude when calibrating ABMs of supply networks by running them on GPUs and using automatic differentiation, compared to non-differentiable baselines. This opens the door to scaling ABMs to model the whole global supply network.
Source: arXiv (Cornell University)
Authors: Hamid, Saad, Moran, José, Mungo, Luca, Quera-Bofarull, Arnau, Towers, Sebastian
Subfield: Strategy and Management
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W7104687971
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