TY - JOUR
T1 - Hesitant fuzzy power Maclaurin symmetric mean operators in the framework of Dempster-Shafer theory for multiple criteria decision making
AU - Zhong, Yanru
AU - Cao, Liangbin
AU - Zhang, Huanan
AU - Qin, Yuchu
AU - Huang, Meifa
AU - Luo, Xiaonan
N1 - Funding Information:
This work was supported by the National Natural Science Foundation of China (No. 62033001), the Guangxi Colleges and Universities Key Laboratory of Intelligent Processing of Computer Images and Graphics (No. GIIP201703), and the Innovation Key Project of Guangxi Province (No. AA18118039-2)
Publisher Copyright:
© 2021, The Author(s), under exclusive licence to Springer-Verlag GmbH, DE part of Springer Nature.
Copyright:
Copyright 2021 Elsevier B.V., All rights reserved.
PY - 2022/4/1
Y1 - 2022/4/1
N2 - In this paper, a hesitant fuzzy power Maclaurin symmetric mean operator and a hesitant fuzzy weighted power Maclaurin symmetric mean operator are presented. The properties of these operators are explored and proved, and their special cases are discussed. Based on the presented operators, a new method is proposed to solve the multiple criteria decision making problems with hesitant fuzzy numbers. A numerical example is introduced to elucidate the application of the method. The advantages of the method are demonstrated via comparisons with some of the existing methods under a set of numerical examples. The demonstration results show that the proposed method has the capabilities to reduce the influence of biased evaluation values and consider the interrelationships between criteria, and more importantly it is free of the limitations of conventional operational laws of hesitant fuzzy numbers and appliable for the multiple criteria decision making problems where criterion weights are in the form of hesitant fuzzy numbers
AB - In this paper, a hesitant fuzzy power Maclaurin symmetric mean operator and a hesitant fuzzy weighted power Maclaurin symmetric mean operator are presented. The properties of these operators are explored and proved, and their special cases are discussed. Based on the presented operators, a new method is proposed to solve the multiple criteria decision making problems with hesitant fuzzy numbers. A numerical example is introduced to elucidate the application of the method. The advantages of the method are demonstrated via comparisons with some of the existing methods under a set of numerical examples. The demonstration results show that the proposed method has the capabilities to reduce the influence of biased evaluation values and consider the interrelationships between criteria, and more importantly it is free of the limitations of conventional operational laws of hesitant fuzzy numbers and appliable for the multiple criteria decision making problems where criterion weights are in the form of hesitant fuzzy numbers
KW - Hesitant fuzzy number
KW - Dempster-Shafer theory
KW - Multiple criteria decision making
KW - Power average operator
KW - Maclaurin symmetric mean operator
KW - Jousselme distance
KW - Dempster–Shafer theory
UR - http://www.scopus.com/inward/record.url?scp=85101495157&partnerID=8YFLogxK
U2 - 10.1007/s12652-021-02932-4
DO - 10.1007/s12652-021-02932-4
M3 - Article
VL - 13
SP - 1777
EP - 1797
JO - Journal of Ambient Intelligence and Humanized Computing
JF - Journal of Ambient Intelligence and Humanized Computing
SN - 1868-5137
IS - 4
ER -
