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1644. An Approximate Dynamic Programming Approach for Managing Vaccine Distribution with Uncertain Supply and Limited Resources
Invited abstract in session WC-21: Infectious diseases and pandemics 2, stream OR in Humanitarian Operations (HOpe).
Wednesday, 12:30-14:00Room: 49 (building: 116)
Authors (first author is the speaker)
| 1. | Peiyan He
|
| Industrial Engineering, Tsinghua University | |
| 2. | Junlong Zhang
|
| Industrial Engineering, Tsinghua University |
Abstract
We study the vaccine distribution problem over a three-echelon network during a sudden pandemic outbreak. We consider uncertainties in vaccine supply due to delays in production, disruption in global supply chain or lockdown policies in the early phases of the pandemic outbreak. We also consider limited resources including cold trucks for vaccine transportation and healthcare workers for vaccine administration. The problem is to dynamically allocate these limited resources over the network such that vaccine can be transported and administrated in a timely and cost-effective manner. We formulate a dynamic programming model for this problem and propose solution algorithms based on approximate dynamic programming. We conduct a case study on a vaccine distribution network in Iran and report computational results that demonstrate the effectiveness of our solution approach over two benchmark approaches.
Keywords
- Supply Chain Management
- Humanitarian Applications
- Stochastic Optimization
Status: accepted
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