Integration of fuzzy-weighted zero-inconsistency and fuzzy decision by opinion score methods under a q-rung orthopair environment: A distribution case study of COVID-19 vaccine doses

A S Albahri; O S Albahri; A A Zaidan; Alhamzah Alnoor; H A Alsattar; Rawia Mohammed; A H Alamoodi; B B Zaidan; Uwe Aickelin; Mamoun Alazab; Salem Garfan; Ibraheem Y Y Ahmaro; M A Ahmed

doi:10.1016/j.csi.2021.103572

Integration of fuzzy-weighted zero-inconsistency and fuzzy decision by opinion score methods under a q-rung orthopair environment: A distribution case study of COVID-19 vaccine doses

Comput Stand Interfaces. 2022 Mar:80:103572. doi: 10.1016/j.csi.2021.103572. Epub 2021 Aug 25.

Authors

A S Albahri^{1

2}, O S Albahri¹, A A Zaidan¹, Alhamzah Alnoor³, H A Alsattar¹, Rawia Mohammed¹, A H Alamoodi¹, B B Zaidan¹, Uwe Aickelin⁴, Mamoun Alazab⁵, Salem Garfan¹, Ibraheem Y Y Ahmaro⁶, M A Ahmed⁷

Affiliations

¹ Department of Computing, Faculty of Arts, Computing and Creative Industry, Universiti Pendidikan Sultan Idris, Tanjung Malim 35900, Malaysia.
² Informatics Institute for Postgraduate Studies (IIPS), Iraqi Commission for Computers and Informatics (ICCI), Baghdad, Iraq.
³ School of Management, Universiti Sains Malaysia, Pulau Pinang, Malaysia.
⁴ School of Computing and Information Systems, University of Melbourne, 700 Swanston Street, Victoria 3010 Australia.
⁵ College of Engineering, IT and Environment, Charles Darwin University, NT, Australia.
⁶ Computer Science Department, College of Information Technology, Hebron University, Hebron, Palestine.
⁷ Department of Computer Science, Computer Science and Mathematics College, Tikrit University, Tikrit, Iraq.

Abstract

Owing to the limitations of Pythagorean fuzzy and intuitionistic fuzzy sets, scientists have developed a distinct and successive fuzzy set called the q-rung orthopair fuzzy set (q-ROFS), which eliminates restrictions encountered by decision-makers in multicriteria decision making (MCDM) methods and facilitates the representation of complex uncertain information in real-world circumstances. Given its advantages and flexibility, this study has extended two considerable MCDM methods the fuzzy-weighted zero-inconsistency (FWZIC) method and fuzzy decision by opinion score method (FDOSM) under the fuzzy environment of q-ROFS. The extensions were called q-rung orthopair fuzzy-weighted zero-inconsistency (q-ROFWZIC) method and q-rung orthopair fuzzy decision by opinion score method (q-ROFDOSM). The methodology formulated had two phases. The first phase 'development' presented the sequential steps of each method thoroughly.The q-ROFWZIC method was formulated and used in determining the weights of evaluation criteria and then integrated into the q-ROFDOSM for the prioritisation of alternatives on the basis of the weighted criteria. In the second phase, a case study regarding the MCDM problem of coronavirus disease 2019 (COVID-19) vaccine distribution was performed. The purpose was to provide fair allocation of COVID-19 vaccine doses. A decision matrix based on an intersection of 'recipients list' and 'COVID-19 distribution criteria' was adopted. The proposed methods were evaluated according to systematic ranking assessment and sensitivity analysis, which revealed that the ranking was subject to a systematic ranking that is supported by high correlation results over different scenarios with variations in the weights of criteria.

Keywords: COVID-19; FDOSM; FWZIC; Multicriteria decision-making; Vaccine; q-Rung orthopair fuzzy.