Linguistic hesitant fuzzy multi-criteria decision-making method based on evidential reasoning

Zhou, Huan; Wang, Jianqiang; Zhang, Hongyu; Chen, Xiaohong

doi:10.1080/00207721.2015.1042089

Cited by 64 publications

(30 citation statements)

References 48 publications

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“…Hesitant fuzzy sets (HFSs) were introduced by Torra and Narukawa 8 to deal with situations where people are hesitant in expressing their preference regarding objects in a decision-making process. Moreover, all these extensions of FSs have been developed by authors working in various fields [9][10][11] with further extensions still being proposed [12][13][14][15][16][17] . In particular, Florentin Smarandache 18,19 introduced neutrosophic logic and neutrosophic sets (NSs) in 1995, with the latter being characterized by the functions of truth, indeterminacy and falsity.…”

Section: Introductionmentioning

confidence: 99%

An Improved Weighted Correlation Coefficient Based on Integrated Weight for Interval Neutrosophic Sets and its Application in Multi-criteria Decision-making Problems

Zhang¹,

Ji²,

Wang³

et al. 2015

IJCIS

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104

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This paper presents a new correlation coefficient measure, which satisfies the requirement of this measure equaling one if and only if two interval neutrosophic sets (INSs) are the same. And an objective weight of INSs is presented to unearth and utilize deeper information that is uncertain. Using the proposed weighted correlation coefficient measure of INSs, a decision-making method is developed, which takes into account the influence of the evaluations' uncertainty and both the objective and subjective weights.

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Section: Introductionmentioning

confidence: 99%

An Improved Weighted Correlation Coefficient Based on Integrated Weight for Interval Neutrosophic Sets and its Application in Multi-criteria Decision-making Problems

Zhang¹,

Ji²,

Wang³

et al. 2015

IJCIS

Self Cite

104

View full text Add to dashboard Cite

show abstract

“…What's more, because the HFLS can be deemed as one special case of linguistic HFSs (LHFSs) when the finite set which defined by HFLS only has one element, the ranking results based on the method proposed in Refs. and and the same illustrative example will be discussed.…”

Section: Illustrative Examplementioning

confidence: 99%

“…In Ref. , when

f_{1} false(s_{i} false) = θ_{i} = \frac{i}{2 t} false(0 \leq i \leq 2 t false)

, according to the method based on evidential reasoning (ER), the score values of the alternatives can be obtained as follows:

S_{1} = 0.287, S_{2} = 0.283, S_{3} = 0.411, S_{4} = 0.229, S_{5} = 0.438 .

…”

Section: Illustrative Examplementioning

confidence: 99%

Hesitant Fuzzy Linguistic Maclaurin Symmetric Mean Operators and their Applications to Multi-Criteria Decision-Making Problem

Zhang

Wang

2017

Int. J. Intell. Syst.

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Due to the limitation of knowledge and the vagueness of human being thinking, decision makers prefer to use hesitant fuzzy linguistic sets (HFLSs) to estimate alternatives. Some methods of HFLSs have been researched based on the more familiar means such as the arithmetic mean and the geometric mean; however, Maclaurin symmetric mean (MSM) that can be used to reflect the interrelationships among input arguments have not been applied to solve hesitant fuzzy linguistic multi‐criteria decision‐making problems. In this paper, two hesitant fuzzy linguistic harmonic averaging operators are proposed: the hesitant fuzzy linguistic MSM (HFLMSM) operator and the hesitant fuzzy linguistic weighted MSM (HFLWMSM) operator. Furthermore, an approach based on the HFLWMSM operator is proposed. Finally, to verify the validity and feasibility of the proposed approach, an illustrative example and corresponding comparison analysis are presented in the end.

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“…For example, s 5 ; f0:3; 0:5g h iis an HFLN, and 0.3 and 0.5 are the possible membership degrees to the linguistic term s 5 (slightly good). As the extensions of HFLSs, the associated membership degrees of one linguistic term can be sets of intervals (Wang et al 2014b) or sets of HFLNs (Meng et al 2014;Zhou et al 2016), instead of sets of crisp values. However, it is clear that HFLSs and their extensions are still unable to express the hesitancy existing in the non-membership and hesitant degrees of linguistic variables.…”

Section: Introductionmentioning

confidence: 99%

Intuitionistic hesitant linguistic sets and their application in multi-criteria decision-making problems

Zhou

Wang

et al. 2015

Oper Res Int J

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In practice, the use of linguistic information is flexible and definite due to the complexity of problems, and therefore the linguistic models have been widely studied and applied to solve multi-criteria decision-making (MCDM) problems under uncertainty. In this paper, intuitionistic hesitant linguistic sets (IHLSs) are defined on the basis of intuitionistic linguistic sets (ILSs) and hesitant fuzzy linguistic sets (HFLSs). As an evaluation value of one reference object, an intuitionistic hesitant linguistic number (IHLN) contains a linguistic term, a set of membership degrees and a set of non-membership degrees. There can be a consensus on the linguistic term and then decision makers can express their opinions on membership or non-membership degrees depending on their preferences. Therefore, by means of IHLSs, the flexibility in generating evaluation information under uncertainty can be achieved to a larger extent than either ILSs or HFLSs do. Besides, the basic operations and comparison method of IHLNs are studied, which is followed by the definitions of several aggregation operators, including the intuitionistic hesitant linguistic hybrid averaging (IHLHA) operator, the intuitionistic hesitant linguistic hybrid geometric (IHLHG) operator and the corresponding generalized operators. Using these operators, an approach to MCDM problems with intuitionistic hesitant linguistic information is proposed. Finally, an illustrative example is provided to verify the proposed approach and its accuracy and effectiveness have been demonstrated through the comparative analysis with ILSs and HFLSs.

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Linguistic hesitant fuzzy multi-criteria decision-making method based on evidential reasoning

Cited by 64 publications

References 48 publications

An Improved Weighted Correlation Coefficient Based on Integrated Weight for Interval Neutrosophic Sets and its Application in Multi-criteria Decision-making Problems

An Improved Weighted Correlation Coefficient Based on Integrated Weight for Interval Neutrosophic Sets and its Application in Multi-criteria Decision-making Problems

Hesitant Fuzzy Linguistic Maclaurin Symmetric Mean Operators and their Applications to Multi-Criteria Decision-Making Problem

Intuitionistic hesitant linguistic sets and their application in multi-criteria decision-making problems

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