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A partial coverage hierarchical location allocation model for health services

Author

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  • Orhan Karasakal
  • Esra Karasakal
  • Özgün Töreyen

Abstract

We consider a hierarchical maximal covering location problem (HMCLP) to locate health centres and hospitals so that the maximum demand is covered by two levels of services in a successively inclusive hierarchy. We extend the HMCLP by introducing the partial coverage and a new definition of the referral. The proposed model may enable an informed decision on the healthcare system when dynamic adaptation is required, such as a COVID-19 pandemic. We define the referral as coverage of health centres by hospitals. A hospital may also cover demand through referral. The proposed model is solved optimally for small problems. For large problems, we propose a customised genetic algorithm. Computational study shows that the GA performs well, and the partial coverage substantially affects the optimal solutions. [Submitted: 20 January 2021; Accepted: 15 January 2022]

Suggested Citation

  • Orhan Karasakal & Esra Karasakal & Özgün Töreyen, 2023. "A partial coverage hierarchical location allocation model for health services," European Journal of Industrial Engineering, Inderscience Enterprises Ltd, vol. 17(1), pages 115-147.
    • Handle: RePEc:ids:eujine:v:17:y:2023:i:1:p:115-147
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    Cited by:

    1. Afshin Kordi & Arash Nemati, 2024. "Simultaneous sensitivity analysis of mixed-integer location-allocation models using machine learning tools: cancer hospitals’ network design," Operational Research, Springer, vol. 24(2), pages 1-32, June.

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