Proportional hesitant fuzzy linguistic term set for multiple criteria group decision making

Chen, Zhen‐Song; Chin, Kwai‐Sang; Li, Yanlai; Yang, Yi

doi:10.1016/j.ins.2016.04.006

Cited by 228 publications

(123 citation statements)

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“…Inspired by pioneer works, more and more attention has been paid to the linguistic distribution assessment 33,34,35 . Although the PHFSs are similarly defined to handle the proportional uncertainty problem, they are quite different from these studies † .…”

Section: Proportional Hesitant Fuzzy Setsmentioning

confidence: 99%

A Novel MAGDM Approach With Proportional Hesitant Fuzzy Sets

Xiong¹,

Chen²,

Chin³

2018

IJCIS

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In this paper, we propose an extension of hesitant fuzzy sets, i.e., proportional hesitant fuzzy sets (PHFSs), with the purpose of accommodating proportional hesitant fuzzy environments. The components of PHFSs, which are referred to as proportional hesitant fuzzy elements (PHFEs), contain two aspects of information provided by a decision-making team: the possible membership degrees in the hesitant fuzzy elements and their associated proportions. Based on the PHFSs, we provide a novel approach to addressing fuzzy multi-attribute group decision making (MAGDM) problems. Different from the traditional approach, this paper first converts fuzzy MAGDM (expressed by classical fuzzy numbers) into proportional hesitant fuzzy multi-attribute decision making (represented by PHFEs), and then solves the latter through the proposal of a proportional hesitant fuzzy TOPSIS approach. In this process, preferences of the decision-making team are calculated as the proportions of the associated membership degrees. Finally, a numerical example and a comparison are provided to illustrate the reliability and effectiveness of the proposed approach.

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Section: Proportional Hesitant Fuzzy Setsmentioning

confidence: 99%

A Novel MAGDM Approach With Proportional Hesitant Fuzzy Sets

Xiong¹,

Chen²,

Chin³

2018

IJCIS

Self Cite

View full text Add to dashboard Cite

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“…The definitions of stochastic variable and its expected value are introduced firstly [18][19][20]. Definition 1.…”

Section: Stochastic Variablesmentioning

confidence: 99%

Selecting Products Considering the Regret Behavior of Consumer: A Decision Support Model Based on Online Ratings

2018

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Abstract:With the remarkable promotion of e-commerce platforms, consumers increasingly prefer to purchase products online. Online ratings facilitate consumers to choose among products. Thus, to help consumers effectively select products, it is necessary to provide decision support methods for consumers to trade online. Considering the decision makers are bounded rational, this paper proposes a novel decision support model for product selection based on online ratings, in which the regret aversion behavior of consumers is formulated. Massive online ratings provided by experienced consumers for alternative products associated with several evaluation attributes are obtained by software finders. Then, the evaluations of alternative products in format of stochastic variables are conducted. To select a desirable alternative product, a novel method is introduced to calculate gain and loss degrees of each alternative over others. Considering the regret behavior of consumers in the product selection process, the regret and rejoice values of alternative products for consumer are computed to obtain the perceived utility values of alternative products. According to the prior order of the evaluation attributes provided by the consumer, the prior weights of attributes are determined based on the perceived utility values of alternative products. Furthermore, the overall perceived utility values of alternative products are obtained to generate a ranking result. Finally, a practical example from Zol.com.cn for tablet computer selection is used to demonstrate the feasibility and practically of the proposed model.

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“…These extended concepts and models support the construction of normative description, operation and aggregation of linguistic evaluation information, and improve the efficiency of solving LMAGDM problems. Furthermore, as the LMAGDM problems are getting complicated, in order to facilitate the integration of linguistic evaluation information provided by group experts, scholars have extended statistical methods such as probability theory, possibility theory, and proportional concepts to linguistic variables based on hesitant fuzzy sets [5], and proposed various corresponding distribution linguistic term sets (DLTSs) [6][7][8][9][10][11]. Decision-makers can apply these DLTSs based on the characteristics of MAGDM problems and linguistic evaluation information from experts.…”

Section: Introductionmentioning

confidence: 99%

The Linguistic Interval-Valued Intuitionistic Fuzzy Aggregation Operators Based on Extended Hamacher T-Norm and S-Norm and Their Application

2020

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Linguistic interval-valued intuitionistic fuzzy sets, as an extension of interval-valued intuitionistic fuzzy sets, have strong practical value in the management of complex uncertainty system with qualitative evaluation information. This study focuses on the development of several linguistic interval-valued intuitionistic fuzzy Hamacher (LIVIFH) aggregation operators based on the extended Hamacher t-norm and s-norm. First, the extended Hamacher t-norm and s-norm, which are applicable to linguistic information environment, are applied to define the linguistic interval-valued intuitionistic fuzzy Hamacher operational laws. Second, based on the proposed operational laws, this study defines the linguistic interval-valued intuitionistic fuzzy Hamacher weighted average (LIVIFHWA) operator and the linguistic interval-valued intuitionistic fuzzy Hamacher weighted geometric (LIVIFHWG) operator, and then investigates their properties. Furthermore, the degeneracy and monotonicity of the proposed operators with respect to the adjustable parameter are explored. Finally, a multiple attribute group decision-making (MAGDM) approach is developed based on the proposed LIVIFH aggregation operators, and then this approach is applied to a supplier selection problem. Parameter analysis indicates that the adjustable parameter in the proposed LIVIFH aggregation operators could reflect the attitudes of decision makers. The LIVIFHWA operator would be more appropriate to optimistic decision makers, and the LIVIFHWG operator to pessimistic decision makers. In addition, as the adjustable parameter increasing, both attitudes tend to be neutral. The proposed method is also compared with two other approaches to show its feasibility and efficiency.Keywords: extended Hamacher t-norm and s-norm; linguistic interval-valued intuitionistic fuzzy set; linguistic interval-valued intuitionistic fuzzy Hamacher operators; multi-attribute group decision-making

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Proportional hesitant fuzzy linguistic term set for multiple criteria group decision making

Cited by 228 publications

References 50 publications

A Novel MAGDM Approach With Proportional Hesitant Fuzzy Sets

A Novel MAGDM Approach With Proportional Hesitant Fuzzy Sets

Selecting Products Considering the Regret Behavior of Consumer: A Decision Support Model Based on Online Ratings

The Linguistic Interval-Valued Intuitionistic Fuzzy Aggregation Operators Based on Extended Hamacher T-Norm and S-Norm and Their Application

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