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Considering short-term and long-term uncertainties in location and capacity planning of public healthcare facilities

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  • Motallebi Nasrabadi, Alireza
  • Najafi, Mehdi
  • Zolfagharinia, Hossein

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.

Suggested Citation

  • Motallebi Nasrabadi, Alireza & Najafi, Mehdi & Zolfagharinia, Hossein, 2020. "Considering short-term and long-term uncertainties in location and capacity planning of public healthcare facilities," European Journal of Operational Research, Elsevier, vol. 281(1), pages 152-173.
    • Handle: RePEc:eee:ejores:v:281:y:2020:i:1:p:152-173
    DOI: 10.1016/j.ejor.2019.08.014
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    Citations

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    Cited by:

    1. Seyyed-Mahdi Hosseini-Motlagh & Mohammad Reza Ghatreh Samani & Behnam Karimi, 2023. "Resilient and social health service network design to reduce the effect of COVID-19 outbreak," Annals of Operations Research, Springer, vol. 328(1), pages 903-975, September.
    2. Mendoza-Gómez, Rodolfo & Ríos-Mercado, Roger Z., 2022. "Regionalization of primary health care units with multi-institutional collaboration," Socio-Economic Planning Sciences, Elsevier, vol. 83(C).
    3. Sagarkumar Hirpara & Monit Vaishnav & Pratik J. Parikh & Nan Kong & Priti Parikh, 2022. "Locating trauma centers considering patient safety," Health Care Management Science, Springer, vol. 25(2), pages 291-310, June.
    4. Dominic J. Breuer & Khedidja Seridi & Nadia Lahrichi & Mohit Shukla & James C. Benneyan, 2022. "Robust multi-period capacity, location, and access of rural cardiovascular services under uncertainty," Flexible Services and Manufacturing Journal, Springer, vol. 34(4), pages 1013-1039, December.
    5. Mina Haghshenas & Arash Nemati & Ebrahim Asadi-Gangraj, 2024. "Using new fuzzy regression aptness and healthcare equity indices in cancer hospitals network design: a fuzzy multi-objective mathematical model," OPSEARCH, Springer;Operational Research Society of India, vol. 61(3), pages 1472-1506, September.
    6. Kaushal Kumar, 2023. "Location Analysis of Primary Health Care Centers: A Case Study of Mohalla Clinics in Delhi," SN Operations Research Forum, Springer, vol. 4(2), pages 1-29, June.
    7. Yashoda Devi & Sabyasachi Patra & Surya Prakash Singh, 2022. "A location-allocation model for influenza pandemic outbreaks: A case study in India," Operations Management Research, Springer, vol. 15(1), pages 487-502, June.
    8. Karakaya, Şakir & Meral, Sedef, 2022. "A biobjective hierarchical location-allocation approach for the regionalization of maternal-neonatal care," Socio-Economic Planning Sciences, Elsevier, vol. 79(C).

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