The maximal covering location problem with accessibility indicators and mobile units

Salvador J. Vicencio-Medina, Yasmin A. Rios-Solis, Omar Jorge Ibarra-Rojas, Nestor M. Cid-Garcia and Leonardo Rios-Solis

Socio-Economic Planning Sciences, 2023, vol. 87, issue PB

Abstract: We study the Maximal Covering Location Problem with Accessibility Indicators and Mobile Units that maximizes the facilities coverage, the accessibility of the zones to the open facilities, and the spatial disaggregation. The main characteristic of our problem is that mobile units can be deployed from open facilities to extend the coverage, accessibility, and opportunities for the inhabitants of the different demand zones. We formulate the Maximal Covering Location Problem with Accessibility Indicators and Mobile Units as a mixed-integer linear programming model. To solve larger instances, we propose a matheuristic (combination of exact and heuristic methods) composed of an Estimation of Distribution Algorithm and a parameterized Maximal Covering Location Problem with Accessibility Indicators and Mobile Units integer model. To test our methodology, we consider the Maximal Covering Location Problem with Accessibility Indicators and Mobile Units model to cover the low-income zones with Severe Acute Respiratory Syndrome Coronavirus 2 patients. Using official databases, we made a set of instances where we considered the poverty index, number of population, locations of hospitals, and Severe Acute Respiratory Syndrome Coronavirus 2 patients. The experimental results show the efficiency of our methodologies. Compared to the case without mobile units, we drastically improve the coverage and accessibility for the inhabitants of the demand zones.

Keywords: Facility location problem; Matheuristic; COVID-19; Mixed-integer linear program; Accessibility; Estimation of distribution algorithm (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:soceps:v:87:y:2023:i:pb:s0038012123000976

DOI: 10.1016/j.seps.2023.101597

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