Fuzzy Domination Graphs in Decision Support Tasks

In decision support tasks, one often has to deal with uncertainty due to fuzzy judgments of the decision maker or the expert. This paper proposes methods that allow you to rank the alternatives based on fuzzy evaluations. This is achieved by using fuzzy weighted summation, fuzzy implication, a compu...

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Main Authors: Vladimir Sudakov, Alexander Zhukov
Format: Article
Language:English
Published: MDPI AG 2023-06-01
Series:Mathematics
Subjects:
Online Access:https://www.mdpi.com/2227-7390/11/13/2837
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author Vladimir Sudakov
Alexander Zhukov
author_facet Vladimir Sudakov
Alexander Zhukov
author_sort Vladimir Sudakov
collection DOAJ
description In decision support tasks, one often has to deal with uncertainty due to fuzzy judgments of the decision maker or the expert. This paper proposes methods that allow you to rank the alternatives based on fuzzy evaluations. This is achieved by using fuzzy weighted summation, fuzzy implication, a computation graph showing the criteria, and a fuzzy dominance graph showing the alternatives. If the criteria have equal importance, then fuzzy graphs corresponding to the dominance of each of the criteria are used. An algorithm that is used for both the transition from fuzzy dominance graphs and the ranking of alternatives is proposed. This algorithm is based on the idea of constructing Kemeny medians or other concordant rankings at a given confidence level in the existence of corresponding arcs. Computational experiments have shown the performance of these approaches. It is reasonable to apply them in problems that require complex expert evaluations with a large number of alternatives and criteria.
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spelling doaj.art-bdc192a7655942dd8eb142eb930b7a852023-11-18T17:02:03ZengMDPI AGMathematics2227-73902023-06-011113283710.3390/math11132837Fuzzy Domination Graphs in Decision Support TasksVladimir Sudakov0Alexander Zhukov1Department of Data Analysis and Machine Learning, Financial University under the Government of the Russian Federation, 125167 Moscow, RussiaFGBSI The Federal Center of Analysis, 109316 Moscow, RussiaIn decision support tasks, one often has to deal with uncertainty due to fuzzy judgments of the decision maker or the expert. This paper proposes methods that allow you to rank the alternatives based on fuzzy evaluations. This is achieved by using fuzzy weighted summation, fuzzy implication, a computation graph showing the criteria, and a fuzzy dominance graph showing the alternatives. If the criteria have equal importance, then fuzzy graphs corresponding to the dominance of each of the criteria are used. An algorithm that is used for both the transition from fuzzy dominance graphs and the ranking of alternatives is proposed. This algorithm is based on the idea of constructing Kemeny medians or other concordant rankings at a given confidence level in the existence of corresponding arcs. Computational experiments have shown the performance of these approaches. It is reasonable to apply them in problems that require complex expert evaluations with a large number of alternatives and criteria.https://www.mdpi.com/2227-7390/11/13/2837fuzzy numbermulticriteria decision analysisfuzzy graphweighted sum modelranking
spellingShingle Vladimir Sudakov
Alexander Zhukov
Fuzzy Domination Graphs in Decision Support Tasks
Mathematics
fuzzy number
multicriteria decision analysis
fuzzy graph
weighted sum model
ranking
title Fuzzy Domination Graphs in Decision Support Tasks
title_full Fuzzy Domination Graphs in Decision Support Tasks
title_fullStr Fuzzy Domination Graphs in Decision Support Tasks
title_full_unstemmed Fuzzy Domination Graphs in Decision Support Tasks
title_short Fuzzy Domination Graphs in Decision Support Tasks
title_sort fuzzy domination graphs in decision support tasks
topic fuzzy number
multicriteria decision analysis
fuzzy graph
weighted sum model
ranking
url https://www.mdpi.com/2227-7390/11/13/2837
work_keys_str_mv AT vladimirsudakov fuzzydominationgraphsindecisionsupporttasks
AT alexanderzhukov fuzzydominationgraphsindecisionsupporttasks