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q ‐Rung orthopair fuzzy Choquet integral aggregation and its application in heterogeneous multicriteria two‐sided matching decision making
Author(s) -
Liang Decui,
Zhang Yinrunjie,
Cao Wen
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.22194
Subject(s) - choquet integral , fuzzy measure theory , fuzzy logic , mathematics , entropy (arrow of time) , matching (statistics) , fuzzy set , fuzzy number , mathematical optimization , computer science , artificial intelligence , statistics , physics , quantum mechanics
In the real decision making, q ‐rung orthopair fuzzy sets ( q ‐ROFSs) as a novel effective tool can depict and handle uncertain information in a broader perspective. Considering the interrelationships among the criteria, this paper extends Choquet integral to the q ‐rung orthopair fuzzy environment and further investigates its application in multicriteria two‐sided matching decision making. To determine the fuzzy measures used in Choquet integral, we first define a pair of q ‐rung orthopair fuzzy entropy and cross‐entropy. Then, by utilizing λ ‐fuzzy measure theory, we propose an entropy‐based method to calculate the fuzzy measures upon criteria. Furthermore, we discuss q ‐rung orthopair fuzzy Choquet integral operator and its properties. Thus, with the aid of q ‐rung orthopair fuzzy Choquet integral, we consider the preference heterogeneity of the matching subjects and further explore the corresponding generalized model and approach for the two‐sided matching. Finally, a simulated example of loan market matching is given to illustrate the validity and applicability of our proposed approach.