Instances and results of "The maximal covering location problem with accessibility indicators and mobile units"

We study the Maximal Covering Location Problem with Accessibility Indicators and Mobile Units (MCLPAMU) 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 MCLPAMU 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 MCLPAMU integer model. To test our methodologies, we consider the real case of distributing COVID-19 tests to the hospitals in Mexico to maximize the coverage and accessibility of the lower-income population and favor the zones with more COVID-19 patients. The experimental results show the efficiency of our methodologies. Compared to the case without mobile unit facilities, we drastically improve the coverage and the accessibility for the inhabitants of the demand zones.