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Some Dombi aggregation of Q ‐rung orthopair fuzzy numbers in multiple‐attribute decision making
Author(s) -
Jana Chiranjibe,
Muhiuddin G.,
Pal Madhumangal
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.22191
Subject(s) - fuzzy logic , operator (biology) , mathematical optimization , mathematics , flexibility (engineering) , computer science , fuzzy set , fuzzy number , artificial intelligence , statistics , biochemistry , chemistry , repressor , transcription factor , gene
The operations of t ‐norm (TN) and t ‐conorm (TCN), developed by Dombi, are generally known as Dombi operations, which have an advantage of flexibility within the working behavior of parameter. In this paper, we use Dombi operations to construct a few Q ‐rung orthopair fuzzy Dombi aggregation operators: Q ‐rung orthopair fuzzy Dombi weighted average operator, Q ‐rung orthopair fuzzy Dombi order weighted average operator, Q ‐rung orthopair fuzzy Dombi hybrid weighted average operator, Q ‐rung orthopair fuzzy Dombi weighted geometric operator, Q ‐rung orthopair fuzzy Dombi order weighted geometric operator, and Q ‐rung orthopair fuzzy Dombi hybrid weighted geometric operator. The different features of these proposed operators are reviewed. At that point, we have used these operators to build up a model to solve the multiple‐attribute decision making issues under Q ‐rung orthopair fuzzy environment. Ultimately, a realistic instance is stated to substantiate the created model and to exhibit its applicability and viability.