A Probabilistic Hesitant Fuzzy MCDM Approach to Selecting Treatment Policy For COVID-19

Ahmed M. Ali; Ahmed Abdelhafeez; Tamer H.M. Soliman; Khaled ELMenshawy

doi:10.31181/dmame712024917

Authors

Ahmed M. Ali Faculty of Computers and Informatics, Zagazig University, Zagazig, 44519, Egypt https://orcid.org/0000-0003-2737-5649
Ahmed Abdelhafeez Faculty of Info. Sys. & Comp. Science, October 6th University, Giza, 12585, Egypt https://orcid.org/0000-0001-6983-5645
Tamer H.M. Soliman AD Research & Development Center, Cairo, 11617, Egypt https://orcid.org/0000-0003-1098-2290
Khaled ELMenshawy Faculty of Info. Sys. & Comp. Science, October 6th University, Giza, 12585, Egypt https://orcid.org/0000-0002-7648-1328

DOI:

https://doi.org/10.31181/dmame712024917

Keywords:

Hesitant fuzzy set, Probabilistic hesitant fuzzy set, COVID-19, COPRAS, Treatment

Abstract

The global significant rise in the number of sick individuals and fatalities has made the ongoing struggle against the severe and lethal COVID-19 pandemic a global effort. There are several ongoing therapies for COVID-19, and more are being developed. However, selecting the best therapy option for COVID-19 patients is still needed. Patients may easily choose from the available COVID-19 therapies using the multi-criteria decision-making method. As a result, the present study provides an MCDM method that is created to determine COVID-19 therapies. Probabilistic Hesitant Fuzzy Set numbers, values, and ambiguity are introduced. Theorems and characteristics of PHFS numbers are also investigated in depth. The Complex Proportional Assessment technique is used, based on the PHFS, for dealing with ambiguity issues. This study uses ten criteria and three treatment methods: antibacterial medication and plasma treatment, vaccinations, as well as quarantine and in-house isolation. The study results reveal that quarantine and isolation at home mark the most effective treatment, followed by vaccinations with antibiotics and plasma therapy.

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References

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