Computational Intelligence Methodologies Applied to Sustainable Development Goals

0558163 - ÚI 2023 RIV CH eng M - Monography Chapter
Figueroa–García, J. C. - Franco, C. - Neruda, Roman
An Optimization Model for Location-Allocation of Health Services Under Uncertainty.
Computational Intelligence Methodologies Applied to Sustainable Development Goals. Cham: Springer, 2022 - (Verdegay, J.; Brito, J.; Cruz, C.), s. 97-108. Studies in Computational Intelligence, 1036. ISBN 978-3-030-97344-5
Institutional support: RVO:67985807
Keywords : Fuzzy optimization * Healthcare location-allocation * Health services
OECD category: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

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.
Permanent Link: http://hdl.handle.net/11104/0331954