Abstract
This work presents a uncertainty-based optimization model for allocation of healthcare facilities to serve patients with different needs. Fuzzy uncertainty is considered in the location-allocation costs, utility and the available budget which are commonly defined by experts and are subject to adjustments and negotiation over time. A fuzzy optimization method based on the cumulative membership function of a fuzzy set is applied to solve the problem where an equilibrium between a fuzzy utility goal and fuzzy-budgets, covering and service constraints is reached.
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Figueroa–García, J.C., Franco, C., Neruda, R. (2022). An Optimization Model for Location-Allocation of Health Services Under Uncertainty. In: Verdegay, J.L., Brito, J., Cruz, C. (eds) Computational Intelligence Methodologies Applied to Sustainable Development Goals. Studies in Computational Intelligence, vol 1036. Springer, Cham. https://doi.org/10.1007/978-3-030-97344-5_7
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