Some
            <i>q</i>
            ‐rung orthopair fuzzy Hamy mean operators in multiple attribute decision‐making and their application to enterprise resource planning systems selection

Wang, Jie; Wei, Guiwu; Lu, Jianping; Alsaadi, Fuad E.; Hayat, Tasawar; Wei, Cun; Zhang, Yi

doi:10.1002/int.22155

Cited by 92 publications

(42 citation statements)

References 79 publications

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“…It is difficult to solve these problems simply by one decision-maker. Multiple decision makers making decisions together can not only reduce errors, but also improve the accuracy of decisions [54][55][56][57][58][59]. Therefore, it is of great significance to apply the MAGDM method of PULTS to green supplier selection.…”

Section: A Case Studymentioning

confidence: 99%

EDAS Method for Multiple Attribute Group Decision Making with Probabilistic Uncertain Linguistic Information and Its Application to Green Supplier Selection

Yan¹,

Lei²,

Wei³

et al. 2019

IJCIS

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In order to adapt to the development of the new times, enterprises should not only care for the economic benefits, but also properly cope with environmental and social problems to achieve the integration of environmental, economic and social performance of sustainable development, so as to maximize the efficiency of resource use and minimize the negative effects of environmental pollution. Hence, in order to select a proper green supplier, integration of the information entropy and Evaluation based on Distance from Average Solution (EDAS) under probabilistic uncertain linguistic sets (PULTSs) offered a novel integrated model, in which information entropy is used for deriving priority weights of each attribute and EDAS with PULTSs is employed to obtain the final ranking of green supplier. Furthermore, in order to show the applicability of the proposed method, it is validated by a case study for green supplier selection along with some comparative analysis. Thus, the advantage of this proposed method is that it is simple to understand and easy to compute. The proposed method can also contribute to the selection of suitable alternative successfully in other selection issues.

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Section: A Case Studymentioning

confidence: 99%

EDAS Method for Multiple Attribute Group Decision Making with Probabilistic Uncertain Linguistic Information and Its Application to Green Supplier Selection

Yan¹,

Lei²,

Wei³

et al. 2019

IJCIS

Self Cite

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“…Among these theories and models, the orthopair fuzzy set (OFS) [28][29][30] allows the membership degree, non-membership degree and hesitancy degree to be [0, 1] × [0, 1], which results in the orthopair fuzzy set generalization of the intuitionistic fuzzy set and Pythagorean fuzzy set and giving great freedom to the modelers of systems in order to capture human knowledge. In this way, the orthopair fuzzy set is able to deal with the uncertainties more flexibly and accurately, has been widely applied in many fields [31,32], such as uncertainty multi-attribute decision making [33], enterprise resource planning systems selection [34], potential evaluation of emerging technology commercialization [35], green suppliers selection [36], scheme selection of construction project [37], venture capital in real estate market [38], medical diagnosis [39] and so on.…”

Section: Introductionmentioning

confidence: 99%

Refined Expected Value Decision Rules under Orthopair Fuzzy Environment

Xue

Deng

2020

Mathematics

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Refined expected value decision rules can refine the calculation of the expected value and make decisions by estimating the expected values of different alternatives, which use many theories, such as Choquet integral, PM function, measure and so on. However, the refined expected value decision rules have not been applied to the orthopair fuzzy environment yet. To address this issue, in this paper we propose the refined expected value decision rules under the orthopair fuzzy environment, which can apply the refined expected value decision rules on the issues of decision making that is described in the orthopair fuzzy environment. Numerical examples were applied to verify the availability and flexibility of the new refined expected value decision rules model. The experimental results demonstrate that the proposed model can apply refined expected value decision rules in the orthopair fuzzy environment and solve the decision making issues with the orthopair fuzzy environment successfully.

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“…In light of this situation, Hara et al [54] initially developed the Hamy mean operator, which can capture the correlation of multiarguments and have an alterable parameter that enables the decision procedure more flexible. Recently, the HM operator has been investigated to fuse fuzzy information under various fuzzy settings, such as Interval type-2 context [55], 2-tuple linguistic neutrosophic [56], linguistic intuitionistic fuzzy number [57], and q-rung orthopair fuzzy environment [58]. Up to now, to the best of our knowledge, no study has been investigated on the HM operator under HFLS setting.…”

Section: Introductionmentioning

confidence: 99%

Hesitant Fuzzy Linguistic Hamy Mean Aggregation Operators and Their Application to Linguistic Multiple Attribute Decision-Making

Run-zhang

Pei

Liu

2020

Mathematical Problems in Engineering

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Linguistic aggregation operator is a paramount appliance to fix linguistic multiple attribute decision-making (MADM) issues. In the article, the Hamy mean (HM) operator is utilized to fuse hesitant fuzzy linguistic (HFL) information and several novel HFL aggregation operators including the hesitant fuzzy linguistic Hamy mean (HFLHM) operator, weighted hesitant fuzzy linguistic Hamy mean (WHFLHM) operator, hesitant fuzzy linguistic dual Hamy mean (HFLDHM) operator, and weighted hesitant fuzzy linguistic dual Hamy mean (WHFLDHM) operator are proposed. Besides, several paramount theorems and particular cases of these aggregation operators are investigated in detail, and then a novel MADM approach is presented by using the proposed aggregation operators. Ultimately, a practical example is utilized to manifest the effectiveness and practicability of the propounded method.

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Some q ‐rung orthopair fuzzy Hamy mean operators in multiple attribute decision‐making and their application to enterprise resource planning systems selection

Cited by 92 publications

References 79 publications

EDAS Method for Multiple Attribute Group Decision Making with Probabilistic Uncertain Linguistic Information and Its Application to Green Supplier Selection

EDAS Method for Multiple Attribute Group Decision Making with Probabilistic Uncertain Linguistic Information and Its Application to Green Supplier Selection

Refined Expected Value Decision Rules under Orthopair Fuzzy Environment

Hesitant Fuzzy Linguistic Hamy Mean Aggregation Operators and Their Application to Linguistic Multiple Attribute Decision-Making

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