Considering short-term and long-term uncertainties in location and capacity planning of public healthcare facilities
Alireza Motallebi Nasrabadi,
Mehdi Najafi and
Hossein Zolfagharinia
European Journal of Operational Research, 2020, vol. 281, issue 1, 152-173
Abstract:
This paper addresses a real-world problem faced by the public healthcare sector. The problem consists of both the patients’ and service provider's requirements (i.e., accessibility vs. costs) for locating healthcare facilities, allocating service units to those facilities, and determining the facilities’ capacities. The main contribution of this study is capturing both short-term and long-term uncertainties at the modelling stage. The queuing theory is incorporated to consider stochastic demand and service time as a short-term uncertainty, as well as a service level measurement. The developed nonlinear model is then converted into a linear model after introducing a new set of decision variables and proving the properties of the service level constraints. We also demonstrate a way in which a linearized model can become more efficient by eliminating excessive binary variables when service level constraints are approximated using their properties. Additionally, long-term demographic variations are captured through robust optimization in order to create a robust model. To solve the problem under investigation, an evolutionary solution method is designed, and its performance is investigated under different settings. We apply this solution method to determine the location and capacity of healthcare facilities in one of the provinces of Iran. The results illustrate that the suggested network can significantly improve the performance measures compared to the existing network. Furthermore, the importance of robust solution in maintaining the desired service level is demonstrated through examining three levels of demographic variations.
Keywords: Location; Healthcare facility location; Queuing theory; Robust optimization; Asymptotic approximation (search for similar items in EconPapers)
Date: 2020
References: Add references at CitEc
Citations: View citations in EconPapers (8)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0377221719306678
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:281:y:2020:i:1:p:152-173
DOI: 10.1016/j.ejor.2019.08.014
Access Statistics for this article
European Journal of Operational Research is currently edited by Roman Slowinski, Jesus Artalejo, Jean-Charles. Billaut, Robert Dyson and Lorenzo Peccati
More articles in European Journal of Operational Research from Elsevier
Bibliographic data for series maintained by Catherine Liu ().