Identification of a Multicriteria Decision-Making Model Using the Characteristic Objects Method
This paper presents a new, nonlinear, multicriteria, decision-making method: the characteristic objects (COMET). This approach, which can be characterized as a fuzzy reference model, determines a measurement standard for decision-making problems. This model is distinguished by a constant set of spec...
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Language: | English |
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Wiley
2014-01-01
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Series: | Applied Computational Intelligence and Soft Computing |
Online Access: | http://dx.doi.org/10.1155/2014/536492 |
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author | Andrzej Piegat Wojciech Sałabun |
author_facet | Andrzej Piegat Wojciech Sałabun |
author_sort | Andrzej Piegat |
collection | DOAJ |
description | This paper presents a new, nonlinear, multicriteria, decision-making method: the characteristic objects (COMET). This approach, which can be characterized as a fuzzy reference model, determines a measurement standard for decision-making problems. This model is distinguished by a constant set of specially chosen characteristic objects that are independent of the alternatives. After identifying a multicriteria model, this method can be used to compare any number of decisional objects (alternatives) and select the best one. In the COMET, in contrast to other methods, the rank-reversal phenomenon is not observed. Rank-reversal is a paradoxical feature in the decision-making methods, which is caused by determining the absolute evaluations of considered alternatives on the basis of the alternatives themselves. In the Analytic Hierarchy Process (AHP) method and similar methods, when a new alternative is added to the original alternative set, the evaluation base and the resulting evaluations of all objects change. A great advantage of the COMET is its ability to identify not only linear but also nonlinear multicriteria models of decision makers. This identification is based not on a ranking of component criteria of the multicriterion but on a ranking of a larger set of characteristic objects (characteristic alternatives) that are independent of the small set of alternatives analyzed in a given problem. As a result, the COMET is free of the faults of other methods. |
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institution | Kabale University |
issn | 1687-9724 1687-9732 |
language | English |
publishDate | 2014-01-01 |
publisher | Wiley |
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series | Applied Computational Intelligence and Soft Computing |
spelling | doaj-art-c8db8da421f4448f8a07178a33e4c6bd2025-02-03T05:45:39ZengWileyApplied Computational Intelligence and Soft Computing1687-97241687-97322014-01-01201410.1155/2014/536492536492Identification of a Multicriteria Decision-Making Model Using the Characteristic Objects MethodAndrzej Piegat0Wojciech Sałabun1Department of Artificial Intelligence Methods and Applied Mathematics, Faculty of Computer Science and Information Technology, West Pomeranian University of Technology, Ulica Żołnierska 49, 71-210 Szczecin, PolandDepartment of Artificial Intelligence Methods and Applied Mathematics, Faculty of Computer Science and Information Technology, West Pomeranian University of Technology, Ulica Żołnierska 49, 71-210 Szczecin, PolandThis paper presents a new, nonlinear, multicriteria, decision-making method: the characteristic objects (COMET). This approach, which can be characterized as a fuzzy reference model, determines a measurement standard for decision-making problems. This model is distinguished by a constant set of specially chosen characteristic objects that are independent of the alternatives. After identifying a multicriteria model, this method can be used to compare any number of decisional objects (alternatives) and select the best one. In the COMET, in contrast to other methods, the rank-reversal phenomenon is not observed. Rank-reversal is a paradoxical feature in the decision-making methods, which is caused by determining the absolute evaluations of considered alternatives on the basis of the alternatives themselves. In the Analytic Hierarchy Process (AHP) method and similar methods, when a new alternative is added to the original alternative set, the evaluation base and the resulting evaluations of all objects change. A great advantage of the COMET is its ability to identify not only linear but also nonlinear multicriteria models of decision makers. This identification is based not on a ranking of component criteria of the multicriterion but on a ranking of a larger set of characteristic objects (characteristic alternatives) that are independent of the small set of alternatives analyzed in a given problem. As a result, the COMET is free of the faults of other methods.http://dx.doi.org/10.1155/2014/536492 |
spellingShingle | Andrzej Piegat Wojciech Sałabun Identification of a Multicriteria Decision-Making Model Using the Characteristic Objects Method Applied Computational Intelligence and Soft Computing |
title | Identification of a Multicriteria Decision-Making Model Using the Characteristic Objects Method |
title_full | Identification of a Multicriteria Decision-Making Model Using the Characteristic Objects Method |
title_fullStr | Identification of a Multicriteria Decision-Making Model Using the Characteristic Objects Method |
title_full_unstemmed | Identification of a Multicriteria Decision-Making Model Using the Characteristic Objects Method |
title_short | Identification of a Multicriteria Decision-Making Model Using the Characteristic Objects Method |
title_sort | identification of a multicriteria decision making model using the characteristic objects method |
url | http://dx.doi.org/10.1155/2014/536492 |
work_keys_str_mv | AT andrzejpiegat identificationofamulticriteriadecisionmakingmodelusingthecharacteristicobjectsmethod AT wojciechsałabun identificationofamulticriteriadecisionmakingmodelusingthecharacteristicobjectsmethod |