Construction of nonreciprocal fuzzy preference relations with the use of preference functions

Parreiras, Roberta; Ekel, Petr

doi:10.1590/s0101-74382013000200010

Cited by 5 publications

(3 citation statements)

References 19 publications

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“…Other approaches to building R p matrices are presented by Parreiras and Ekel [59] and Kokshenev et al [66]. If estimates F p (X k ), p = 1, 2,..., q, X k ∈ X are defined on a unit value scale, these approaches allow one to obtain µ R p (X k , X l ), p = 1, 2,..., q, X k , X l ∈ X as follows:…”

Section: Models and Their Constructionmentioning

confidence: 99%

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Fuzzy-Set-Based Multi-Attribute Decision-Making, Its Computing Implementation, and Applications

Ferreira,

Ribeiro,

Schuffner

et al. 2024

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This paper reflects the results of research analyzing models of multi-attribute decision-making based on fuzzy preference relations. Questions of constructing the corresponding multi-attribute models to deal with quantitative information concomitantly with qualitative information based on experts’ knowledge are considered. Human preferences may be represented within the fuzzy preference relations and by applying diverse other preference formats. Considering this, so-called transformation functions reduce any preference format to fuzzy preference relations. This paper’s results can be applied independently or as part of a general approach to solving a wide class of problems with fuzzy coefficients, as well as within the framework of a general scheme of multi-criteria decision-making under conditions of uncertainty. The considered techniques for fuzzy preference modeling are directed at assessing, comparing, choosing, prioritizing, and/or ordering alternatives. These techniques have served to develop a computing system for multi-attribute decision-making. It has been implemented in the C# programming language, utilizing the “.NET” framework. The computing system allows one to represent decision-makers’ preferences in one of five preference formats. These formats and quantitative estimates are reduced to nonreciprocal fuzzy preference relations, providing homogeneous preference information for decision procedures. This paper’s results have a general character and were applied to analyze power engineering problems.

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Section: Models and Their Constructionmentioning

confidence: 99%

“…Reciprocal fuzzy preference relation is a fuzzy preference relation that satisfies the property of additive reciprocity (see expression in [59]).…”

mentioning

confidence: 99%

Fuzzy-Set-Based Multi-Attribute Decision-Making, Its Computing Implementation, and Applications

Ferreira,

Ribeiro,

Schuffner

et al. 2024

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“…permits one, using the expressions (32) and (33), to construct R p , 1, 2, , p q =  . Other our approaches to constructing matrices R p are discussed in [39] [40].…”

Section: Problems With Fuzzy Coefficientsmentioning

confidence: 99%

Generalized Algorithms of Discrete Optimization and Their Power Engineering Applications

Berredo¹,

Ekel²,

Ferreira³

et al. 2015

ENG

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Generalized algorithms for solving problems of discrete, integer, and Boolean programming are discussed. These algorithms are associated with the method of normalized functions and are based on a combination of formal and heuristic procedures. This allows one to obtain quasioptimal solutions after a small number of steps, overcoming the NP-completeness of discrete optimization problems. Questions of constructing so-called "duplicate" algorithms are considered to improve the quality of discrete problem solutions. An approach to solving discrete problems with fuzzy coefficients in objective functions and constraints on the basis of modifying the generalized algorithms is considered. Questions of applying the generalized algorithms to solve multicriteria discrete problems are also discussed. The results of the paper are of a universal character and can be applied to the design, planning, operation, and control of systems and processes of different purposes. The results of the paper are already being used to solve power engineering problems.

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Multiobjective and multiattribute decision making in a fuzzy environment and their power engineering applications

Ekel

Kokshenev²,

Parreiras

et al. 2016

Information Sciences

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Construction of nonreciprocal fuzzy preference relations with the use of preference functions

Cited by 5 publications

References 19 publications

Fuzzy-Set-Based Multi-Attribute Decision-Making, Its Computing Implementation, and Applications

Fuzzy-Set-Based Multi-Attribute Decision-Making, Its Computing Implementation, and Applications

Generalized Algorithms of Discrete Optimization and Their Power Engineering Applications

Multiobjective and multiattribute decision making in a fuzzy environment and their power engineering applications

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