A fuzzy-set approach to treat determinacy and consistency of linguistic terms in multi-criteria decision making

Ma, Jun; Ruan, Da; Xu, Yang; Zhang, G.

doi:10.1016/j.ijar.2006.07.007

Cited by 82 publications

(45 citation statements)

References 35 publications

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“…In order to face these restrictions, different proposals that facilitate the elicitation of elaborated linguistic preferences with complex linguistic expressions have been introduced in the literature 20,33,38,42,49 . Such proposals focus their performance on very different points of view that can be used by decision makers according to their needs in each specific problem.…”

Section: Modelling Complex Linguistic Preferencesmentioning

confidence: 99%

“…As it has been previously mentioned Ma et al 20 also pointed out that the use of predefined linguistic terms facilitates the elicitation of linguistic information, but it limits to decision makers to express their preferences freely, because they have to select one linguistic term from the predefined linguistic term set, that might not matching with his/her opinion, and he/she might think in several linguistic terms at the same time. Consequently, a new approach that increases the flexibility of the linguistic expressions allowing to use more than one linguistic term was proposed.…”

Section: A Fuzzy-set Approach To Treat Determinacy and Consistency Ofmentioning

confidence: 99%

“…Thus, CW has been applied as computational basis to decision making problems that deal with linguistic information 22,26 , because it provides tools close to human beings reasoning processes related to decision making, enhances the reliability and flexibility of classical decision models and improves the resolution of decision making under uncertainty with linguistic information. Consequently, different linguistic computational models have been developed to manage linguistic decision making 14,20,37,41,43 .…”

Section: Introductionmentioning

confidence: 99%

“…Hence, recently different researchers have proposed different attempts to facilitate the elicitation of linguistic preferences by expressions to some extent more elaborated than simple labels 20,33,38,42,49 . Such extensions have used different fuzzy tools to model and compute with such linguistic expressions in a closer way to decision makers' needs.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

An Overview on Fuzzy Modelling of Complex Linguistic Preferences in Decision Making

Rodríguez¹,

Labella²,

Martínez³

2016

IJCIS

192

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Decision makers involved in complex decision making problems usually provide information about their preferences by eliciting their knowledge with different assessments. Usually, the complexity of these decision problems implies uncertainty that in many occasions has been successfully modelled by means of linguistic information, mainly based on fuzzy based linguistic approaches. However, classically these approaches just allow the elicitation of simple assessments composed by either one label or a modifier with a label. Nevertheless, the necessity of more complex linguistic expressions for eliciting decision makers' knowledge has led to some extensions of classical approaches that allow the construction of expressions and elicitation of preferences in a closer way to human beings cognitive process. This paper provides an overview of the broadest fuzzy linguistic approaches for modelling complex linguistic preferences together some challenges that future proposals should achieve to improve complex linguistic modelling in decision making.

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Section: Modelling Complex Linguistic Preferencesmentioning

confidence: 99%

Section: A Fuzzy-set Approach To Treat Determinacy and Consistency Ofmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

An Overview on Fuzzy Modelling of Complex Linguistic Preferences in Decision Making

Rodríguez¹,

Labella²,

Martínez³

2016

IJCIS

192

View full text Add to dashboard Cite

show abstract

“…However, some problems present also qualitative aspects that are complex to assess by means of precise and exact values. In these cases, the fuzzy linguistic approach [19,34,41,49,50,55,56,57] can be used to obtain a better solution. This is the case, for instance, when experts try to evaluate the "comfort" of a car, where linguistic terms like "good", "fair", "poor" are used [40].…”

Section: Introductionmentioning

confidence: 99%

Managing the consensus in group decision making in an unbalanced fuzzy linguistic context with incomplete information

Cabrerizo

Pérez

Liu

2010

Knowledge-Based Systems

293

114

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To solve group decision making problems we have to take in account different aspects. On the one hand, depending on the problem, we can deal with different types of information. In this way, most group decision making problems based on linguistic approaches use symmetrically and uniformly distributed linguistic term sets to express experts' opinions. However, there exist problems whose assessments need to be represented by means of unbalanced linguistic term sets, i.e., using term sets which are not uniformly and symmetrically distributed. On the other hand, there may be cases in which experts do not have an in-depth knowledge of the problem to be solved. In such cases, experts may not put their opinion forward about certain aspects of the problem and, as a result, they may present incomplete information. The aim of this paper is to present a consensus model to help experts in all phases of the consensus reaching process in group decision making problems in an unbalanced fuzzy linguistic context with incomplete information. As part of this consensus model, we propose an iterative procedure using consistency measures to estimate the incomplete information.In addition, the consistency measures are used together with consensus measures to guided the consensus model.The main novelty of this consensus model is that it supports the management of incomplete unbalanced fuzzy linguistic information and it allows to achieve consistent solutions with a great level of agreement.

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Hesitant Fuzzy Sets: State of the Art and Future Directions

Rodríguez

Martínez

Torra

et al. 2014

Int. J. Intell. Syst.

413

159

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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. C 2014 Wiley Periodicals, Inc.

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A fuzzy-set approach to treat determinacy and consistency of linguistic terms in multi-criteria decision making

Cited by 82 publications

References 35 publications

An Overview on Fuzzy Modelling of Complex Linguistic Preferences in Decision Making

An Overview on Fuzzy Modelling of Complex Linguistic Preferences in Decision Making

Managing the consensus in group decision making in an unbalanced fuzzy linguistic context with incomplete information

Hesitant Fuzzy Sets: State of the Art and Future Directions

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