Location selection of field hospital for future pandemics using fuzzy combined MCDM methods

For thousands of years, human beings have struggled with many natural disasters such as earthquakes, floods, epidemics, and volcanic eruptions. Among these natural disasters, epidemics have caused the death of hundreds of people. Many epidemics, from the plague epidemic, also known as the Black Death to the Swine flu and today to the COVID-19 pandemic, have affected societies deeply by affecting a wide range of areas. Due to the rapid spread of the COVID-19 pandemic, which arised from Wuhan, China in December 2019, many hospitals around the world have exceeded their capacity and insufficient. Authorities of some countries have built field hospitals during the pandemic to find a solution to this problem. In this thesis study, field hospital location selection problem for pandemics that are predicted to increase in the future in the globalizing world was discussed and a real case study was conducted in Adana. Since the location selection problem, which is one of the topics of operations research, involves multiple conflicting criteria and a limited number of alternatives, Multi-Criteria Decision Making (MCDM) is one of the most effective classical methods known to solve such problems. Since these classical methods are insufficient to handle uncertain and imprecise situations in real life, it may be more realistic to make decisions based on fuzzy versions of these methods that take into account human judgments. Thus, in this study, a fuzzy FUCOM & fuzzy MARCOS model was suggested to solve the field hospital location selection problem. The weights of the criteria were calculated with the fuzzy FUCOM method. The alternative locations were then ranked with the fuzzy MARCOS method. According to the analysis results, it was determined that the best alternative location was TUYAP Adana Fair and Congress Center Surrounding. Lastly, a sensitivity analysis was conducted to test the accuracy and validity of the proposed model.