An approach for decision making using intuitionistic trapezoidal fuzzy soft set
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초록
Introduction of soft sets by Molodtsov (1999) has evolved a revolution in the decision making paradigm. Researchers have used soft sets with different extensions of fuzzy sets to satisfy the various types of uncertainties involved with real life decision making problems. This paper introduces intuitionistic trapezoidal fuzzy soft set (ITrFSS) by combining intuitionistic trapezoidal fuzzy set (ITrFS) with soft set. Firstly, we generalize the adjustable approach applied to intuitionistic fuzzy soft set (IFSS) based decision making developed by Jiang et al. (2011) and then present an approach to ITrFSS based decision making using threshold ITrFSs and level soft sets. Moreover, we propose weighted ITrFSS and apply it in a decision making problem. Fuzzy analytic hierarchy process (AHP) has been used to derive the attribute weights. This paper has also validated the outcome of the adjustable approaches based on ITrFSS and weighted ITrFSS using closeness coefficient measure. Finally, two illustrative examples are provided to show the feasibility of the proposed approaches in real life decision making problems.
Abstract
Introduction of soft sets by Molodtsov (1999) has evolved a revolution in the decision making paradigm. Researchers have used soft sets with different extensions of fuzzy sets to satisfy the various types of uncertainties involved with real life decision making problems. This paper introduces intuitionistic trapezoidal fuzzy soft set (ITrFSS) by combining intuitionistic trapezoidal fuzzy set (ITrFS) with soft set. Firstly, we generalize the adjustable approach applied to intuitionistic fuzzy soft set (IFSS) based decision making developed by Jiang et al. (2011) and then present an approach to ITrFSS based decision making using threshold ITrFSs and level soft sets. Moreover, we propose weighted ITrFSS and apply it in a decision making problem. Fuzzy analytic hierarchy process (AHP) has been used to derive the attribute weights. This paper has also validated the outcome of the adjustable approaches based on ITrFSS and weighted ITrFSS using closeness coefficient measure. Finally, two illustrative examples are provided to show the feasibility of the proposed approaches in real life decision making problems.
참고문헌 (46)
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