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Cyclic sequential process of pairwise comparisons with application to multi-criteria decision making.
- Source :
- International Journal of Machine Learning & Cybernetics; Apr2023, Vol. 14 Issue 4, p1391-1405, 15p
- Publication Year :
- 2023
-
Abstract
- The technique of paired comparisons is commonly used for finding an optimal solution to multi-criteria decision-making (MCDM) problems. The process of comparing alternatives is worth investigations due to the limitation and complexity of human cognition. In this paper, we propose a cyclic sequential process of pairwise comparisons to produce a real-valued preference relation without reciprocal property. The non-reciprocal property characterizes the uncertainty experienced by the decision maker (DM). The concepts of consistency and approximate consistency are defined by considering the inherent property of the derived uncertain preference relation. An optimization model is given to elicit the priority vector from uncertain preference relations. A novel yet effective possibility degree formula is established to rank interval numbers. A new decision making model is constructed and illustrated by carrying out numerical examples. As compared to the existing works, a novel process of pairwise comparisons is proposed to generate an uncertain preference relation and cope with the uncertainty in a decision making problem. The proposed model can be used to reduce the workload of providing pairwise comparisons for the DM and reach an acceptable decision. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 18688071
- Volume :
- 14
- Issue :
- 4
- Database :
- Complementary Index
- Journal :
- International Journal of Machine Learning & Cybernetics
- Publication Type :
- Academic Journal
- Accession number :
- 162508812
- Full Text :
- https://doi.org/10.1007/s13042-022-01705-5