A Novel q-Rung Dual Hesitant Fuzzy Multi-Attribute Decision-Making Method Based on Entropy Weights

In recent years, the development of electric vehicles has received extensive attention. However, how to choose a suitable charging pile manufacturer for electric vehicles is a matter of concern. The selection of charging pile manufacturers involves many factors, and it is hard for decision makers (DMs) to provide accurate assessments due to the uncertainty of subjective or objective factors. As a combination of q-rung orthopair fuzzy set (q-ROFS) and dual hesitant fuzzy set (DHFS), q-rung dual hesitant fuzzy set (q-RDHFS) provides more possibilities for information expression and gives DMs greater decision-making freedom. Because of the advantages of q-RDHFS in expressing uncertain information, we propose a novel decision method to capture DMs’ hesitant information with q-rung dual hesitant fuzzy elements (q-RDHFEs) to obtain the optimal scheme. Firstly, Frank t-norm and t-conorm (FTT) is well known for its flexibility in coping with compatibility compared to traditional algebraic operation. Considering the advantages of FTT, we extend FTT to q-RDHFS and provide the definition of Frank operational rules of q-RDHFS. Subsequently, according to generalized power average (GPA) and generalized power geometric (GPG) operators, some corresponding operators based on the novel operational laws are proposed. Then, with the proposed operators, a novel multi-attribute decision-making (MADM) method under q-RDHFS environment is introduced and applied to the selection of charging pile manufacturers. Finally, compared with the existing methods, the method proposed in this paper can better handle extreme evaluation information and is more flexible in operation.

show abstract

“…Definition 4 [33]. If 𝑑 1 = (ℎ 1 , 𝑔 1 ) and 𝑑 2 = (ℎ 2 , 𝑔 2 ) are any two q-RDHFEs, then we can define the distance between 𝑑 1 and 𝑑 2 as…”

Section: The Q-rung Dual Hesitant Fuzzy Setsmentioning

confidence: 99%

A Novel Decision-Making Method for Selecting Charging Pile Manufacturer with q-Rung Dual Hesitant Information

Tan

Shang

Wang

et al. 2022

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…In addition, Kou et al [14] introduced the distance measurement method between any two q-RDHFEs. Definition 4 ([14]).…”

Section: Definition 2 ([12]mentioning

confidence: 99%

“…Q-RDHFSs adsorb the advantages of q-rung orthopair fuzzy sets [6] and dual hesitant fuzzy sets [8], and their characters and superiorities in depicting decision makers' fuzzy evaluation values are evident. Many methods, such as, Wang et al 's [13] method based on a dual hesitant q-rung orthopair fuzzy Muirhead mean operator, Kou et al's [14] novel q-rung dual hesitant fuzzy MADM method based on entropy weights, Yang et al's [15] extension TOPSIS method under a q-RDHFSs environment, and Shao et al's [16] general framework that investigated the multi-granulation rough decision-making method under q-RDHFSs situations, all demonstrate that q-RDHFSs have a wide application scope. However, existing methods of q-rung dual hesitant fuzzy elements (q-RDHFEs) only consider the homogeneous relationship, which are inadequate for resolving some realistic decision-making issues.…”

Section: Introductionmentioning

confidence: 99%

A Novel Decision-Making Method for Selecting Superintendent Based on a Q-Rung Dual Hesitant Fuzzy Power Partitioned Bonferroni Mean Operator

Chen

2022

Symmetry

View full text Add to dashboard Cite

The q-rung dual hesitant fuzzy (q-RDHF) set is famous for expressing information composed of asymmetry evaluations, because it allows for several possible evaluations in both the membership degree and non-membership degree. Compared with some existing extended fuzzy theories, the q-RDHF set is more superior and flexible because it can handle asymmetric assessments. In order to assemble the evaluation information expressed by q-RDHF elements, this paper aims to propose new operators to integrate q-RDHF elements. The partitioned Bonferroni mean (PBM) operator is well-known for its advantages in coping with the inhomogeneous relationship between asymmetry input arguments. In this paper, we combine the PBM operator with the power average operator, and propose a family of q-RDHF power PBM operators. Some theorems and special cases for the new proposed operators are discussed. Furthermore, we provide a general framework for dealing with multiple attribute decision-making (MADM) problems using the novel proposed method. To better show the calculation details, a numerical case study of the application of the proposed method in a superintendent selection problem is introduced. In addition, we utilize the proposed method to compare it with some existing methods in order to show its flexibility and superiority. The results show that our method is much more advantageous when considering flexible actual situations. Finally, the conclusion is given. The main contributions of this study are to propose an appropriate method to solve unbalanced and asymmetry information in a q-RDHF environment, and to apply it into a realistic superintendent selection problem.

show abstract

“…Generally, all these activities need to be evaluated with respect to several attributes, which are also known as MAGDM problems and are very common in our daily life. Therefore, MAGDM problems have received great attentions in the past few decades [ 4 , 5 , 6 ]. With the increase in the complexity of the actual world, fuzzy set (FS) theory, proposed by Zadeh in 1965 [ 7 ], which was designed to utilize the membership degree (MD) to represent DMs’ expression information, has drawn more and more attention.…”

Section: Introductionmentioning

confidence: 99%

A Novel MAGDM Method Based on Hesitant Picture Fuzzy Schweizer–Sklar Maclaurin Symmetric Mean Operators and Their Application

Chen

2022

Entropy

View full text Add to dashboard Cite

Multiple attribute group decision making (MAGDM) issues play important roles in our daily life. In order to solve the problem that decision makers (DMs) may feel hesitant to select the appropriate evaluation values from several possible values in the process of providing evaluations, fuzzy theory and its extensions are widely applied in MAGDM problems. In this study, we first proposed hesitant picture fuzzy sets (HPFSs), which is a combination of the hesitant fuzzy set and picture fuzzy set. Subsequently, we introduced a novel Schweizer–Sklar t-norm and t-conorm operation rules of HPFSs and proposed a family of hesitant picture fuzzy Schweizer–Sklar Maclaurin symmetric mean operators. To show the application procedure of the proposed method to practical MAGDM issues, a numerical example about enterprise informatization level evaluation was employed to elaborate the calculation process with the proposed method. Finally, through the parameter analysis, validity analysis, and comparative analysis with some existing methods, we found that our method is more superior in providing DMs a greater decision-making freedom and relaxing the constraints on expressing personal preferences. This study provides a general framework of the proposed method to MAGDM problems under hesitant picture fuzzy environment, which enriches the fuzzy theory and its applications.

show abstract

A Novel q-Rung Dual Hesitant Fuzzy Multi-Attribute Decision-Making Method Based on Entropy Weights

Cited by 8 publications

References 56 publications

A Novel Decision-Making Method for Selecting Charging Pile Manufacturer with q-Rung Dual Hesitant Information

A Novel Decision-Making Method for Selecting Charging Pile Manufacturer with q-Rung Dual Hesitant Information

A Novel Decision-Making Method for Selecting Superintendent Based on a Q-Rung Dual Hesitant Fuzzy Power Partitioned Bonferroni Mean Operator

A Novel MAGDM Method Based on Hesitant Picture Fuzzy Schweizer–Sklar Maclaurin Symmetric Mean Operators and Their Application

Contact Info

Product

Resources

About