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A new hybrid risk-averse best-worst method and portfolio optimization to select temporary hospital locations for Covid-19 patients

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  • Siamak Kheybari
  • Alessio Ishizaka
  • Amirhossein Salamirad

Abstract

Choosing the right place to set up temporary hospitals is one of the most important and urgent measures for pandemic response. To solve this problem, we propose a new hybrid approach based on two steps. Firstly, since human health is highly sensitive to the impact of decisions about temporary hospital locations and a mistake may pose severe threat to human lives, we propose a new risk-averse multi-criteria decision-making (MCDM) approach. To choose the alternatives with the fewest possible weaknesses, a comprehensive hierarchal structure of relevant criteria categorized into environmental, social, economic, and infrastructural, along with a new risk-averse best-worst method (BWM), are presented as the two components of the MCDM approach. Secondly, considering the output of risk-averse BWM and the distance between the selected centres for better patient coverage as parameters, a portfolio optimization model is used for the hospital selection locations. Our new approach has been applied to a real case study to select cities in Mazandaran, a northern Iranian province seriously affected by the Coronavirus (COVID-19), as places to build temporary hospitals.

Suggested Citation

  • Siamak Kheybari & Alessio Ishizaka & Amirhossein Salamirad, 2023. "A new hybrid risk-averse best-worst method and portfolio optimization to select temporary hospital locations for Covid-19 patients," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 74(2), pages 509-526, February.
    • Handle: RePEc:taf:tjorxx:v:74:y:2023:i:2:p:509-526
    DOI: 10.1080/01605682.2021.1993758
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