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Location-allocation models for healthcare facilities with long-term demand

Author

Listed:
  • Ruilin Ouyang
  • Tasnim Ibn Faiz
  • Md. Noor-E-Alam

Abstract

Healthcare facility location decisions are of great importance due to their impact on direct and social cost of people's well-being in a region. Optimal location decisions considering only current demand may become suboptimal as demand distribution changes. Considering future demand realisations in the decision making process can ensure long-term optimality. We present three mathematical models which follow grid-based location approach, and consider current and future demands in providing optimal location-allocation decisions. The first model considers allocations of present and future patients only to the nearest facilities. The second model allows patients to travel to facilities within allowable distance. The third model allows allocation of patients from one location to multiple facilities. The models are implemented with AMPL and numerical instances are solved with the CPLEX solver. Results show that the models are capable of solving medium size problems and the third model performs better in providing high quality solutions.

Suggested Citation

  • Ruilin Ouyang & Tasnim Ibn Faiz & Md. Noor-E-Alam, 2020. "Location-allocation models for healthcare facilities with long-term demand," International Journal of Operational Research, Inderscience Enterprises Ltd, vol. 38(3), pages 295-320.
    • Handle: RePEc:ids:ijores:v:38:y:2020:i:3:p:295-320
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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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