A Web-based Decision Support Center for Electrical Energy Companies

Kokshenev, Illya; Parreiras, Roberta; Ekel, Petr; Alves, Gladstone B.; Menicucci, Stefano V.

doi:10.1109/tfuzz.2014.2312984

Cited by 10 publications

(6 citation statements)

References 33 publications

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“…It is also important to highlight that applying the three preference modeling techniques in a fuzzy environment directly applies to decision-making problems in a multi-criteria group [10]. This is a considerable advantage, as most decision-making problems involve groups of experts [63][64][65].…”

Section: Construction and Analysis Of < X R > Modelsmentioning

confidence: 99%

Multi-Criteria Decision under Uncertainty as Applied to Resource Allocation and Its Computing Implementation

Ekel,

Libório,

Ribeiro

et al. 2024

Mathematics

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This research addresses the problem of multi-objective resource allocation or resource deficits, offering robust answers to planning decisions that involve the elementary question: “How is it done?”. The solution to the problem is realized using the general scheme of multi-criteria decision-making in uncertain conditions. The bases of the proposed scheme are associated with the possibilistic approach, which involves the generalization of fuzzy sets from the classical approach to process the uncertainty of information to produce robust (non-dominated) solutions in multi-criteria analysis. Applying this general scheme makes it possible to reduce regions of decision uncertainty through the maximum use of available quantitative information. In the case where quantitative information analysis is insufficient to obtain a unique solution, the proposed approach presupposes the appropriation of qualitative data extracted from experts, who express their opinions considering their knowledge, experience, and intuition. The information on the qualitative character can be represented in diverse preference formats processed by transformation functions to provide homogeneous information for decision procedures used at the final decision stage. The presented results have been implemented within the system of multi-criteria decision-making under uncertain conditions described in the paper. Its functioning is illustrated by solving the typical problem in investment planning activities.

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Section: Construction and Analysis Of < X R > Modelsmentioning

confidence: 99%

Multi-Criteria Decision under Uncertainty as Applied to Resource Allocation and Its Computing Implementation

Ekel,

Libório,

Ribeiro

et al. 2024

Mathematics

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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%

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

Ferreira,

Ribeiro,

Schuffner

et al. 2024

Axioms

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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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“…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%

“…The indicated procedures have served for developing other techniques: the analysis of alternatives with fuzzy ordering of criteria [17] [24]; the analysis of alternatives based on the concept of fuzzy majority (based on the application of the so-called OWA operator, originally proposed in [44]) [17] [40]; the analysis of alternatives based on an outranking approach (by a means of a fuzzy version of the PROMETHEE [45]) [17].…”

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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A Web-based Decision Support Center for Electrical Energy Companies

Cited by 10 publications

References 33 publications

Multi-Criteria Decision under Uncertainty as Applied to Resource Allocation and Its Computing Implementation

Multi-Criteria Decision under Uncertainty as Applied to Resource Allocation and Its Computing Implementation

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

Generalized Algorithms of Discrete Optimization and Their Power Engineering Applications

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