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Abstract
This paper combines the q-rung orthopair hesitant fuzzy sets (q-ROHFSs) with the uncertain linguistic variables, and proposes the q-rung orthopair hesitant fuzzy uncertain linguistic sets (q-ROHFULSs). In addition, the Schweizer-Sklar T-norm is introduced, and a multi-attribute decision-making method based on the q-rung orthopair hesitant fuzzy uncertain linguistic Schweizer-Sklar aggregation operators is established. Firstly, based on the Schweizer-Sklar T-norm, the operational properties of q-rung orthopair hesitant fuzzy uncertain linguistic elements are defined, and the score function, accuracy function and ranking method of the q-rung orthopair hesitant fuzzy uncertain linguistic elements are proposed. Secondly, the q-rung orthopair hesitant fuzzy uncertain linguistic Schweizer-Sklar Bonferroni mean (BM) operator and geometric Bonferroni mean (GBM) operator, Maclaurin symmetric mean (MSM) operator and dual Maclaurin symmetric mean (DMSM) operator, Maclaurin mean (MM) operator and dual Maclaurin mean (DMM) operator are defined. The calculation formulas of the operators are given, the related properties are studied, and the special forms of the operators are discussed. Finally, a multi-attribute decision-making model based on the q-rung orthopair hesitant fuzzy uncertain linguistic aggregation operators is established, and the feasibility and effectiveness of the decision-making method are demonstrated through calculation examples and comparative analyses.
Highlights
Multi-attribute decision-making refers to the decisionmaking problem of sorting alternatives and choosing the best while considering multiple attributes
Case 4: When P = (1, 1, .., 1, 0, . . . , 0), the q-ROHFULSSMM operator reduces to the q-rung orthopair hesitant fuzzy uncertain linguistic Schweizer-Sklar Maclaurin symmetric mean (q-ROHFULSSMSM) operator which can be presented (45), as shown at the bottom of the page
Case 4: When P = (1, 1, .., 1, 0, . . . , 0), the q-ROHFULSSDMM operator reduces to the q-rung orthopair hesitant fuzzy uncertain linguistic Schweizer-Sklar dual Maclaurin symmetric mean (q-ROHFULSSDMSM) operator which can be presented (52), as shown at the bottom of the page
Summary
Multi-attribute decision-making refers to the decisionmaking problem of sorting alternatives and choosing the best while considering multiple attributes. Liu et al [32] studied the aggregation operators of the q-rung orthopair fuzzy uncertain linguistic sets and their applications in multi-attribute decision-making. The Schweizer-Sklar T-norm is introduced into the q-rung orthopair hesitant fuzzy uncertain linguistic sets, and the Schweizer-Sklar Bonferroni mean (BM) operator, Maclaurin symmetric mean (MSM) operator and Maclaurin mean (MM) operator of are defined, and the multiple attributes decision-making methods of the q-rung orthopair hesitant fuzzy uncertain linguistic Schweizer-Sklar aggregation operator are established. 2) The q-rung orthopair hesitant fuzzy uncertain linguistic Schweizer-Sklar aggregation operator can flexibly select different parameter values according to the decision-making situation to meet the requirements of different decision-making problems in practice.
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