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Na Chen

Bio: Na Chen is an academic researcher from Southeast University. The author has contributed to research in topics: Fuzzy set & Fuzzy logic. The author has an hindex of 7, co-authored 7 publications receiving 1345 citations. Previous affiliations of Na Chen include Nanjing University of Finance and Economics.

Papers
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Journal ArticleDOI
TL;DR: A new type of fuzzy preference structure, called interval-valued hesitant preference relations, is introduced to describe uncertain evaluation information in group decision making (GDM) processes and is developed in order to consider the differences of opinions between individual decision makers.
Abstract: We introduce a new type of fuzzy preference structure, called interval-valued hesitant preference relations, to describe uncertain evaluation information in group decision making (GDM) processes. Moreover, it allows decision makers to offer all possible interval values that are not accounted for in current preference structure types when one compares two alternatives. We generalize the concept of hesitant fuzzy set (HFS) to that of interval-valued hesitant fuzzy set (IVHFS) in which the membership degrees of an element to a given set are not exactly defined, but denoted by several possible interval values. We give systematic aggregation operators to aggregate interval-valued hesitant fuzzy information. In addition, we develop an approach to GDM based on interval-valued hesitant preference relations in order to consider the differences of opinions between individual decision makers. Numerical examples are provided to illustrate the proposed approach.

466 citations

Journal ArticleDOI
TL;DR: The interval-valued HFSs and the corresponding correlation coefficient formulas are developed and demonstrated their application in clustering with intervals-valued hesitant fuzzy information through a specific numerical example.

449 citations

Journal ArticleDOI
TL;DR: Several series of aggregation operators are proposed and two methods are proposed to determine the aggregation weight vectors based on the support degrees among aggregation arguments, so that the weight vector of decision makers are obtained more objectively.
Abstract: Hesitancy is the most common problem in decision making, for which hesitant fuzzy set can be considered as a suitable means allowing several possible degrees for an element to a set. In this paper, we study the aggregation of the hesitancy fuzzy information. Several series of aggregation operators are proposed and the connections of them are discussed. To reflect the correlation of the aggregation arguments, two methods are proposed to determine the aggregation weight vectors. Based on the support degrees among aggregation arguments, the weight vector of decision makers are obtained more objectively. To deal with the correlation of criteria, we apply the Choquet integral to get the weights of criteria. A method is also proposed for group decision making under hesitant fuzzy environment.

406 citations

Journal ArticleDOI
TL;DR: A hesitant fuzzy ELECTRE I (HF-ELECTRE I) method is developed and applied to solve the MCDM problem under hesitant fuzzy environments using the concepts of hesitant fuzzy concordance and hesitant fuzzy discordance to determine the preferable alternative.
Abstract: Hesitant fuzzy set (HFS), which allows the membership degree of an element to a set represented by several possible values, is considered as a powerful tool to express uncertain information in the process of multi-criteria decision making (MCDM) problems. In this paper, we develop a hesitant fuzzy ELECTRE I (HF-ELECTRE I) method and apply it to solve the MCDM problem under hesitant fuzzy environments. The new method is formulated using the concepts of hesitant fuzzy concordance and hesitant fuzzy discordance which are based on the given score function and deviation function, and employed to determine the preferable alternative. Numerical examples are provided to demonstrate the application of the proposed method, and the influence of different numbers of alternatives on outranking relations is analyzed based on a derived sensitive parameter interval in which a change in the parameters has no effects on the set of the nonoutranked alternatives. The randomly generated numerical cases are also investigated in the framework of the HF-ELECTRE I method. Furthermore, the outranking relations obtained in the HF-ELECTRE I method with those derived from the aggregation operator-based approach and the ELECTRE III and ELECTRE IV methods are discussed.

78 citations

Journal ArticleDOI
TL;DR: This paper proposes a series of aggregation operators considering the confidence levels of the aggregated arguments and extends them to hesitant fuzzy environments in which there are some difficulties in determining the membership of an element to a set.
Abstract: This paper proposes a series of aggregation operators considering the confidence levels of the aggregated arguments. Due to the complex connections among the arguments, we further give two nonlinear aggregation operators and discuss their properties. Then we extend these aggregation operators to hesitant fuzzy environments in which there are some difficulties in determining the membership of an element to a set. Several numerical examples are used to compare the proposed aggregation operators.

55 citations


Cited by
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Journal ArticleDOI
TL;DR: A novel approach based on TOPSIS and the maximizing deviation method for solving MADM problems, in which the evaluation information provided by the decision maker is expressed in hesitant fuzzy elements and the information about attribute weights is incomplete is developed.
Abstract: Hesitant fuzzy set (HFS), which allows the membership degree of an element to a set represented by several possible values, is considered as a powerful tool to express uncertain information in the process of multi-attribute decision making (MADM) problems. In this paper, we develop a novel approach based on TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) and the maximizing deviation method for solving MADM problems, in which the evaluation information provided by the decision maker is expressed in hesitant fuzzy elements and the information about attribute weights is incomplete. There are two key issues being addressed in this approach. The first one is to establish an optimization model based on the maximizing deviation method, which can be used to determine the attribute weights. According to the idea of the TOPSIS of Hwang and Yoon [1], the second one is to calculate the relative closeness coefficient of each alternative to the hesitant positive-ideal solution, based on which the considered alternatives are ranked and then the most desirable one is selected. An energy policy selection problem is used to illustrate the detailed implementation process of the proposed approach, and demonstrate its validity and applicability. Finally, the extended results in interval-valued hesitant fuzzy situations are also pointed out.

553 citations

Journal ArticleDOI
Guiwu Wei1
TL;DR: This paper develops some prioritized aggregation operators for aggregating hesitant fuzzy information, and applies them to develop some models for hesitant fuzzy multiple attribute decision making (MADM) problems in which the attributes are in different priority level.
Abstract: In this paper, we investigate the hesitant fuzzy multiple attribute decision making (MADM) problems in which the attributes are in different priority level. Motivated by the ideal of prioritized aggregation operators [R.R. Yager, Prioritized aggregation operators, International Journal of Approximate Reasoning 48 (2008) 263-274], we develop some prioritized aggregation operators for aggregating hesitant fuzzy information, and then apply them to develop some models for hesitant fuzzy multiple attribute decision making (MADM) problems in which the attributes are in different priority level. Finally, a practical example about talent introduction is given to verify the developed approaches and to demonstrate its practicality and effectiveness.

494 citations

Journal ArticleDOI
TL;DR: Several series of aggregation operators are proposed and two methods are proposed to determine the aggregation weight vectors based on the support degrees among aggregation arguments, so that the weight vector of decision makers are obtained more objectively.
Abstract: Hesitancy is the most common problem in decision making, for which hesitant fuzzy set can be considered as a suitable means allowing several possible degrees for an element to a set. In this paper, we study the aggregation of the hesitancy fuzzy information. Several series of aggregation operators are proposed and the connections of them are discussed. To reflect the correlation of the aggregation arguments, two methods are proposed to determine the aggregation weight vectors. Based on the support degrees among aggregation arguments, the weight vector of decision makers are obtained more objectively. To deal with the correlation of criteria, we apply the Choquet integral to get the weights of criteria. A method is also proposed for group decision making under hesitant fuzzy environment.

406 citations

Journal ArticleDOI
TL;DR: An overview on hesitant fuzzy sets is presented with the aim of providing a clear perspective on the different concepts, tools and trends related to this extension of fuzzy sets.
Abstract: The necessity of dealing with uncertainty in real world problems has been a long-term research challenge that has originated different methodologies and theories. Fuzzy sets along with their extensions, such as type-2 fuzzy sets, interval-valued fuzzy sets, and Atanassov's intuitionistic fuzzy sets, have provided a wide range of tools that are able to deal with uncertainty in different types of problems. Recently, a new extension of fuzzy sets so-called hesitant fuzzy sets has been introduced to deal with hesitant situations, which were not well managed by the previous tools. Hesitant fuzzy sets have attracted very quickly the attention of many researchers that have proposed diverse extensions, several types of operators to compute with such types of information, and eventually some applications have been developed. Because of such a growth, this paper presents an overview on hesitant fuzzy sets with the aim of providing a clear perspective on the different concepts, tools and trends related to this extension of fuzzy sets.

405 citations

Journal ArticleDOI
TL;DR: The definition and basic properties of the different types of fuzzy sets that have appeared up to now in the literature are reviewed and the relationships between them are analyzed.
Abstract: In this paper, we review the definition and basic properties of the different types of fuzzy sets that have appeared up to now in the literature. We also analyze the relationships between them and enumerate some of the applications in which they have been used.

386 citations