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An interval‐valued exceedance method in MCDM with uncertain satisfactions
Author(s) -
Liu Zeyi,
Xiao Fuyuan
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.22171
Subject(s) - normalization (sociology) , interval (graph theory) , probabilistic logic , computer science , operator (biology) , multiple criteria decision analysis , mathematical optimization , selection (genetic algorithm) , value (mathematics) , interval arithmetic , data mining , mathematics , artificial intelligence , machine learning , biochemistry , chemistry , repressor , combinatorics , sociology , anthropology , transcription factor , gene , mathematical analysis , bounded function
Multicriteria decision‐making problems have been applied to many applications for its practicality. Nevertheless, when the evaluated satisfactions are more complex, such as interval‐valued distributions, how to reasonably obtain the aggregation results of alternatives is still an open issue. In this paper, an interval‐valued exceedance method is proposed to solve such a question based on the Golden Rule representative value and probabilistic exceedance method. Due to good performance of expressing uncertain information, the Golden Rule representative value method is used to order interval‐valued satisfactions after an effective normalization process. In addition, a quantifier‐based ordered weighted averaging operator is also introduced to consider the preferences of decision makers. A realistic application of supplier selection is shown to illustrate the practicality of the proposed method.