A Software Package and Data Set for the Personal Protective Equipment Matching Problem During COVID-19

Michele Samorani (), Ram Bala (), Rohit Jacob () and Shuhan He ()
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Michele Samorani: Leavey School of Business, Santa Clara University, Santa Clara, California 95053
Ram Bala: Leavey School of Business, Santa Clara University, Santa Clara, California 95053
Rohit Jacob: Project Stanley Inc., Pleasanton, California 94566
Shuhan He: Massachusetts General Hospital, Department of Emergency Medicine, Boston, Massachusetts 02114; Harvard Medical School, Boston, Massachusetts 02115

INFORMS Journal on Computing, 2022, vol. 34, issue 5, 2754-2761

Abstract: During the COVID-19 pandemic, Get Us PPE provided a platform aimed at connecting prospective donors of personal protective equipment (PPE) to prospective recipients of PPE. Requests by donors and recipients were collected over time, and periodically, the PPE matching problem was solved in order to instruct each donor to ship a certain quantity of PPE to a given recipient. The objectives of the PPE matching problem include maximizing the recipients’ fill rate, minimizing the total shipping distance, minimizing the holding time of PPE, and minimizing the number of shipments of each donor. This paper presents a software framework to facilitate the development of methodologies to solve the PPE matching problem and their testing on a real-world data set collected by Get Us PPE during the COVID-19 pandemic. Both software and data set are available on GitHub.

Keywords: COVID-19; PPE supply chain; PPE matching problem (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (1)

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