A new hybrid risk-averse best-worst method and portfolio optimization to select temporary hospital locations for Covid-19 patients
提出一种结合风险规避最佳-最差方法和投资组合优化的两阶段混合方法，用于选择新冠肺炎临时医院地点，以最小化决策风险并优化患者覆盖，在伊朗马赞德兰省的实际案例中验证了有效性。
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.