Accessible location of mobile labs for COVID-19 testing

Dianne Villicaña-Cervantes () and Omar J. Ibarra-Rojas ()
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Dianne Villicaña-Cervantes: Universidad Autónoma de Nuevo León
Omar J. Ibarra-Rojas: Universidad Autónoma de Nuevo León

Health Care Management Science, 2024, vol. 27, issue 1, No 1, 19 pages

Abstract: Abstract In this study, we address the problem of finding the best locations for mobile labs offering COVID-19 testing. We assume that people within known demand centroids have a degree of mobility, i.e., they can travel a reasonable distance, and mobile labs have a limited-and-variable service area. Thus, we define a location problem concerned with optimizing a measure representing the accessibility of service to its potential clients. In particular, we use the concepts of classical, gradual, and cooperative coverage to define a weighted sum of multiple accessibility indicators. We formulate our optimization problem via a mixed-integer linear program which is intractable by commercial solvers for large instances. In response, we designed a Biased Random-Key Genetic Algorithm to solve the defined problem; this is capable of obtaining high-quality feasible solutions over large numbers of instances in seconds. Moreover, we present insights derived from a case study into the locations of COVID-19 testing mobile laboratories in Nuevo Leon, Mexico. Our experimental results show that our optimization approach can be used as a diagnostic tool to determine the number of mobile labs needed to satisfy a set of demand centroids, assuming that users have reduced mobility due to the restrictions because of the pandemic.

Keywords: Location; Accessibility; Mixed-integer linear program; BRKGA; COVID-19 testing; Operations research (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s10729-022-09614-3

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