Integrating three representation models in fuzzy multipurpose decision making based on fuzzy preference relations

Chiclana, Francisco; Herrera, Francisco; Herrera‐Viedma, Enrique

doi:10.1016/s0165-0114(96)00339-9

Cited by 688 publications

(380 citation statements)

References 11 publications

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“…Also, based on the OWA operator and the BUM function Q, Chiclana et al presented the quantifier guided non-dominance degree for a RPR [10]. Therefore, it is possible to implement the concept of non-dominance to the case of an IRPR by using the associated SRPR.…”

Section: Selection Processmentioning

confidence: 99%

Multiplicative consistency of intuitionistic reciprocal preference relations and its application to missing values estimation and consensus building

Chiclana

2014

Knowledge-Based Systems

152

121

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Section: Selection Processmentioning

confidence: 99%

Multiplicative consistency of intuitionistic reciprocal preference relations and its application to missing values estimation and consensus building

Chiclana

2014

Knowledge-Based Systems

152

121

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“…The resolution of a classical group decision making problem, according with the principles established in [6], is developed in the following two steps:…”

Section: Twofold Group Decision Makingmentioning

confidence: 99%

“…In a classical group decision making problem ( [6,10]), some information provided by several experts is considered in order to choose the alternative which is most accepted by these specialists.…”

Section: Introductionmentioning

confidence: 99%

Applications of finite interval-valued hesitant fuzzy preference relations in group decision making

Pérez‐Fernández

Alonso

Bustince

et al. 2016

Information Sciences

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The main purpose of this paper is to present the twofold group decision making problem, which is a new point of view of the group decision making problem where several experts and criteria can be considered at the same time. This problem is based on the study of nitely generated sets and nite interval-valued hesitant fuzzy preference relations. Furthermore, the Extended Weighted Voting Method, which is used in the exploitation phase of a classical group decision making problem, is generalized to the twofold case.

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“…In particular, the value a = 1/2 is suggested to be used to represent the fuzzy linguistic quantifier 'most of'. Based on this methodology, a fuzzy quantifier guided nondominance degree, which extends Orlovsky's non-dominance concept, for a FPR was presented in [8].…”

Section: Fuzzy Quantifier Guided Selection Approaches Based On Dommentioning

confidence: 99%

Choice degrees in decision-making: A comparison between intuitionistic and fuzzy preference relations approaches

Chiclana

Ureña

Herrera‐Viedma

2016

2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

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Abstract-Preference modelling based on Atanassov's intuitionistic fuzzy sets are gaining increasing relevance in the field of group decision making as they provide experts with a flexible and simple tool to express their preferences on a set of alternative options, while allowing, at the same time, to accommodate experts' preference uncertainty, which is inherent to all decision making processes. A key issue within this framework is the provision of efficient methods to rank alternatives, from best to worse, taking into account the peculiarities that this type of preference representation format presents. In this contribution we analyse the relationships between the main method proposed and used by researchers to rank alternatives using intuitionistic fuzzy sets, the score degree function, and the well known choice degree based on Orlovsky's non-dominance concept for the case when the preferences are expressed by means of fuzzy preference relations. This relationship study will provide the necessary theoretical results to support the implementation of Orlovsky's non-dominance concept to define the fuzzy quantifier guided non-dominance choice degree for intuitionistic fuzzy preference relations.

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Integrating three representation models in fuzzy multipurpose decision making based on fuzzy preference relations

Cited by 688 publications

References 11 publications

Multiplicative consistency of intuitionistic reciprocal preference relations and its application to missing values estimation and consensus building

Multiplicative consistency of intuitionistic reciprocal preference relations and its application to missing values estimation and consensus building

Applications of finite interval-valued hesitant fuzzy preference relations in group decision making

Choice degrees in decision-making: A comparison between intuitionistic and fuzzy preference relations approaches

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