The distance measures between q‐rung orthopair hesitant fuzzy sets and their application in multiple criteria decision making

Liu, Donghai; Peng, Dan; Liu, Zaiming

doi:10.1002/int.22133

Cited by 66 publications

(45 citation statements)

References 39 publications

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“…Based on Dombi aggregation, Jana et al [14] developed q-rung orthopair fuzzy Dombi weighted averaging operator and q-rung orthopair fuzzy Dombi order weighted averaging operator. Some distance measures in q-rung orthopair fuzzy environment have been investigated [15]- [18]. Peng et al [18] proposed q-rung orthopair fuzzy weighted distance-based approximation method.…”

Section: Some Q-rung Orthopair Fuzzy Bonferroni Mean Operatorsmentioning

confidence: 99%

New q-Rung Orthopair Fuzzy Bonferroni Mean Dombi Operators and Their Application in Multiple Attribute Decision Making

Yang

Pang

2020

IEEE Access

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Some q-rung orthopair fuzzy Bonferroni mean Dombi aggregation operators have been developed based on the Bonferroni mean, Dombi T-norm and T-conorm in q-rung orthopair fuzzy environment. The q-rung orthopair fuzzy Bonferroni mean Dombi averaging (q-ROFBMDA) operator and the q-rung orthopair fuzzy geometric Bonferroni mean Dombi averaging (q-ROFGBMDA) operator are first developed. Then the q-rung orthopair fuzzy weighted Bonferroni mean Dombi averaging (q-ROFWBMDA) operator and the q-rung orthopair fuzzy weighted geometric Bonferroni mean Dombi averaging (q-ROFWGBMDA) operator have been developed. Based on the partitioned operation, the q-rung orthopair fuzzy partitioned Bonferroni mean Dombi averaging (q-ROFPBMDA) operator and the q-rung orthopair fuzzy partitioned geometric Bonferroni mean Dombi averaging (q-ROFPGBMDA) operator have been presented. Some desirable properties of the new aggregation operators have been studied. A new multiple attribute decision making method based on the q-ROFWBMDA (q-ROFWGBMDA) operator is proposed. Finally, a numerical example of new campus site selection has been presented to illustrate the new method. INDEX TERMS q-rung orthopair fuzzy sets, Dombi, Bonferroni mean, aggregation operator.

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Section: Some Q-rung Orthopair Fuzzy Bonferroni Mean Operatorsmentioning

confidence: 99%

New q-Rung Orthopair Fuzzy Bonferroni Mean Dombi Operators and Their Application in Multiple Attribute Decision Making

Yang

Pang

2020

IEEE Access

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“…On same lines Liu et al [13] developed the distance measures to solve the decision making problems under HFLTSs. As q-rung orthopair hesitant fuzzy set (q-ROHFS) is an extension of HFS, developed by Liu et al [14], taking the advantage of q-ROHFS, Liu et al [14] introduced the distance measures for application in decision making. Bonferroni [15] introduced the Bonferroni mean (BM) for real number domain.…”

Section: Introductionmentioning

confidence: 99%

Distance Measures for Multiple-Attributes Decision-Making Based on Connection Numbers of Set Pair Analysis With Dual Hesitant Fuzzy Sets

et al. 2020

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Dual hesitant fuzzy sets (DHFSs) is the refinement and extension of hesitant fuzzy sets and encompasses fuzzy sets, intuitionistic fuzzy sets, hesitant fuzzy sets, and fuzzy multisets as a special case. DHFSs have two parts, that is, the membership function and the non-membership function, in which each function is defined by two sets of some feasible values. Therefore, according to the practical demand, DHFSs are more adjustable than the existing ones and provide the information regarding different objects in much better way. The set pair analysis (SPA) illustrates unsureness in three angles, called ''identity'', ''discrepancy'' and ''contrary'', and the connection number (CN) is one of its main features. In the present article, the axiom definition of distance measure between DHFSs and CN is introduced. The distance measures are established on the basis of Hamming distance, Hausdorff distance and Euclidean distance. The previous identities and relationship between them are discussed in detail. On the basis of the geometric distance model, the settheoretic approach, and the matching functions several novel distance formulas of CN are introduced. The novel distance formulas are then applied to multiple-attribute decision making for dual hesitant fuzzy environments. Finally, to demonstrate the validity of the introduced measures, a practical example of decisionmaking is presented. The benefits of the new measures over the past measures are additionally talked about.

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“…Considering the better ability of q-ROFS in depicting fuzzy information, q-ROFS has been extensively studied from different perspectives. For example, some extended forms have been investigated such as q-rung orthopair hesitant fuzzy set [7], q-rung orthopair uncertain linguistic set [8], q-rung orthopair normal fuzzy set [9], etc. Based on q-ROFSs, Liu et al [10] explored consensus reaching process combined with fuzzy behavioral TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) method.…”

Section: Introductionmentioning

confidence: 99%

An Extended VIKOR Method Based on q-Rung Orthopair Shadowed Set and Its Application to Multi-Attribute Decision Making

Wang¹,

Zhang²,

Yao³

2020

Symmetry

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In the multi-attribute decision making (MADM) process, the attribute values are sometimes provided by experts or the public in the form of words. To model the linguistic evaluation more accurately, this paper proposes the q-rung orthopair shadowed set (q-ROSS) to represent attribute values and extends the VIKOR (VIsekriterijumska optimizacija i KOmpromisno Resenje) method to solve MADM problems in the q-ROSS context. First, we propose the q-ROSS to express evaluation information. Some basic operation rules and distance measures are investigated accordingly. When the amount of data is large, the left and right endpoints of the collected interval numbers will obey symmetric normal distribution. Secondly, based on the normal distribution assumption, the collected data intervals are mapped to shadowed sets through a data processing approach. Furthermore, we extend the VIKOR model to tackle the MADM problem where the evaluation values are expressed by q-rung orthopair shadowed numbers. A location selection problem verifies the practicability of our method, and the effectiveness and superiority of the presented approach are reflected through comparative analysis.

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The distance measures between q‐rung orthopair hesitant fuzzy sets and their application in multiple criteria decision making

Cited by 66 publications

References 39 publications

New q-Rung Orthopair Fuzzy Bonferroni Mean Dombi Operators and Their Application in Multiple Attribute Decision Making

New q-Rung Orthopair Fuzzy Bonferroni Mean Dombi Operators and Their Application in Multiple Attribute Decision Making

Distance Measures for Multiple-Attributes Decision-Making Based on Connection Numbers of Set Pair Analysis With Dual Hesitant Fuzzy Sets

An Extended VIKOR Method Based on q-Rung Orthopair Shadowed Set and Its Application to Multi-Attribute Decision Making

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