Modelling uncertainties with TOPSIS and GRA based on q-rung orthopair m-polar fuzzy soft information in COVID-19
Muhammad Riaz
Department of Mathematics, University of the Punjab, Lahore, Pakistan
Search for more papers by this authorCorresponding Author
Harish Garg
School of Mathematics, Thapar Institute of Engineering and Technology, Deemed University, Patiala, Punjab, India
Correspondence
Harish Garg, School of Mathematics, Thapar Institute of Engineering and Technology, Deemed University, Patiala 147004, Punjab, India.
Email: [email protected]
Search for more papers by this authorMuhammad Tahir Hamid
Department of Mathematics & Statistics, The University of Lahore, Lahore, Pakistan
Search for more papers by this authorDeeba Afzal
Department of Mathematics & Statistics, The University of Lahore, Lahore, Pakistan
Search for more papers by this authorMuhammad Riaz
Department of Mathematics, University of the Punjab, Lahore, Pakistan
Search for more papers by this authorCorresponding Author
Harish Garg
School of Mathematics, Thapar Institute of Engineering and Technology, Deemed University, Patiala, Punjab, India
Correspondence
Harish Garg, School of Mathematics, Thapar Institute of Engineering and Technology, Deemed University, Patiala 147004, Punjab, India.
Email: [email protected]
Search for more papers by this authorMuhammad Tahir Hamid
Department of Mathematics & Statistics, The University of Lahore, Lahore, Pakistan
Search for more papers by this authorDeeba Afzal
Department of Mathematics & Statistics, The University of Lahore, Lahore, Pakistan
Search for more papers by this authorAbstract
Fuzzy hybrid models are strong mathematical tools to address vague and uncertain information in real-life circumstances. The aim of this article is to introduce a new fuzzy hybrid model named as of q-rung orthopair m-polar fuzzy soft set (q-RO-m-PFSS) as a robust fusion of soft set (SS), m-polar fuzzy set (m-PFS) and q-rung orthopair fuzzy set (q-ROFS). A q-RO-m-PFSS is a new approach towards modelling uncertainties in the multi-criteria decision making (MCDM) problems. Some fundamental operations on q-RO-m-PFSSs, their key properties, and related significant results are introduced. Additionally, the complexity of logistics and supply chain management during COVID-19 is analysed using TOPSIS (technique for ordering preference through the ideal solution) and GRA (grey relational analysis) with the help of q-RO-m-PFS information. The linguistic terms are used to express q-RO-m-PFS information in terms of numeric values. The proposed approaches are worthy efficient in the selection of ventilator's manufacturers for the patients suffering from epidemic disease named as COVID-19. A practical application of proposed MCDM techniques is demonstrated by respective numerical examples. The comparison analysis of the final ranking computed by proposed techniques is also given to justify the feasibility, applicability and reliability of these techniques.
CONFLICT OF INTEREST
The authors declare no potential conflict of interest.
Open Research
DATA AVAILABILITY STATEMENT
Data sharing not applicable to this article as no datasets were generated or analysed during the current study.
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