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Weighted power means of q ‐rung orthopair fuzzy information and their applications in multiattribute decision making
Author(s) -
Du Wen Sheng
Publication year - 2019
Publication title -
international journal of intelligent systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.291
H-Index - 87
eISSN - 1098-111X
pISSN - 0884-8173
DOI - 10.1002/int.22167
Subject(s) - fuzzy logic , mathematics , bounded function , exponent , power (physics) , value (mathematics) , fuzzy set , multiple criteria decision analysis , flexibility (engineering) , computer science , mathematical optimization , statistics , artificial intelligence , mathematical analysis , physics , linguistics , philosophy , quantum mechanics
Weighted power means with weights and exponents serving as their parameters are generalizations of arithmetic means. Taking into account decision makers' flexibility in decision making, each attribute value is usually expressed by a q ‐rung orthopair fuzzy value ( q ‐ROFV, q ≥ 1 ), where the former indicates the support for membership, the latter support against membership, and the sum of their q th powers is bounded by one. In this paper, we propose the weighted power means of q ‐rung orthopair fuzzy values to enrich and flourish aggregations on q ‐ROFVs. First, the q ‐rung orthopair fuzzy weighted power mean operator is presented, and its boundedness is precisely characterized in terms of the power exponent. Then, the q ‐rung orthopair fuzzy ordered weighted power mean operator is introduced, and some of its fundamental properties are investigated in detail. Finally, a novel multiattribute decision making method is explored based on developed operators under the q ‐rung orthopair fuzzy environment. A numerical example is given to illustrate the feasibility and validity of the proposed approach, and it is shown that the power exponent is an index suggesting the degree of the optimism of decision makers.