Mean field control problems for vaccine distribution
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Abstract (arXiv)
With the invention of the COVID-19 vaccine, shipping and distributing are crucial in controlling the pandemic. In this paper, we build a mean-field variational problem in a spatial domain, which controls the propagation of pandemic by the optimal transportation strategy of vaccine distribution. Here we integrate the vaccine distribution into the mean-field SIR model designed in our previous paper arXiv:2006.01249. Numerical examples demonstrate that the proposed model provides practical strategies in vaccine distribution on a spatial domain.
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). First posted on arXiv 24 Apr 2021.
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Citing papers per year: 2023: 2; 2024: 0; 2025: 2.
4 papers.
- 2023A Policy Gradient Framework for Stochastic Optimal Control Problems with Global Convergence Guaranteecited by 10
- 2023Decoding Mean Field Games from Population and Environment Observations By Gaussian Processescited by 2
- 2025Learning Surrogate Potential Mean Field Games via Gaussian Processes: A Data-Driven Approach to Ill-Posed Inverse Problemscited by 2
- 2025Gaussian process policy iteration with additive Schwarz acceleration for forward and inverse HJB and mean field game problemscited by 0
- 2025Gaussian process policy iteration with additive Schwarz acceleration for forward and inverse HJB and mean field game problems1 May 2025
- 2025Learning Surrogate Potential Mean Field Games via Gaussian Processes: A Data-Driven Approach to Ill-Posed Inverse Problems17 Feb 2025
- 2023Decoding Mean Field Games from Population and Environment Observations By Gaussian Processes8 Dec 2023
- 2023A Policy Gradient Framework for Stochastic Optimal Control Problems with Global Convergence Guarantee11 Feb 2023