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10.1016/j.csi.2021.103572

http://scihub22266oqcxt.onion/10.1016/j.csi.2021.103572
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suck abstract from ncbi


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pmid34456503      Comput+Stand+Interfaces 2022 ; 80 (ä): 103572
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  • 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 #MMPMID34456503
  • Albahri AS; Albahri OS; Zaidan AA; Alnoor A; Alsattar HA; Mohammed R; Alamoodi AH; Zaidan BB; Aickelin U; Alazab M; Garfan S; Ahmaro IYY; Ahmed MA
  • Comput Stand Interfaces 2022[Mar]; 80 (ä): 103572 PMID34456503show ga
  • 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.
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