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Density‐clusters ordered weighted averaging op erat or based on generalized trapezoidal fuzzy numbers
Author(s) -
Yi Pingtao,
Wang Lu,
Li Weiwei
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.22180
Subject(s) - operator (biology) , mathematics , centroid , fuzzy logic , cluster (spacecraft) , fuzzy number , algorithm , mathematical optimization , discrete mathematics , computer science , artificial intelligence , fuzzy set , biochemistry , chemistry , geometry , repressor , transcription factor , gene , programming language
Abstract To the problem of multi‐attribute decision making with fuzzy numbers, this paper proposes a new type of operator called the density‐clusters ordered weighted averaging (OWA) operator based on generalized trapezoidal fuzzy (GTF) numbers. This operator is abbreviated as the GTF‐DOWA operator. A primary characteristic of the GTF‐DOWA operator is that it considers the implicit structure of the GTF numbers to be aggregated by grouping the numbers to various local clusters. We discuss the grouping methods of the GTF numbers using the centroids of the numbers. The cluster weights are determined by the combined consideration of the decision maker's attitude and the scale of each local cluster. In addition, we discuss the primary properties of the GTF‐DOWA operator. Finally, a numerical example regarding the selection of optimal alternative is provided. The aggregations of the GTF‐DOWA operator are compared with those of the weighted arithmetic averaging (WAA) operator and the OWA operator based on GTF numbers to illustrate the validity of the GTF‐DOWA operator.