• Journal of KIISE:Software and Applications
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• v.28 no.12
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• pp.930-937
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• 2001

For ranking fuzzy numbers, comparisons between numbers are necessary However, the comparison results can be vague since fuzzy numbers represent vague numeric values. Thus, ranking results of fuzzy numbers which are based on comparisons between fuzzy numbers, could also be vague. This means that there could be several possible ranking sequences of fuzzy numbers. There have been proposed many ranking methods for fuzzy numbers. However, most of them generate only ranking sequence. In this paper, we present a ranking method for fuzzy numbers using the fuzzy satisfaction function, Our method generates several possible ranking sequences of the given fuzzy numbers using the fuzzy satisfaction function.

• Journal of applied mathematics & informatics
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• v.41 no.2
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• pp.311-320
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• 2023

In this article, a new penalty and different ranking algorithms are used to find the lowest transportation costs for the fuzzy transportation problem. This approach utilises different ranking techniques when dealing with triangular fuzzy numbers. Also, we find that the fuzzy transportation solution of the proposed method is the same as the Fuzzy Modified Distribution Method (FMODI) solution. Finally, examples are used to show how a problem is solved.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2006.05a
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• pp.94-95
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• 2006

A great deal of research has been made to model the vagueness and uncertainty in information retrieval. One such research is fuzzy ranking models, which have been showing their superior performance in handling the uncertainty involved in the retrieval process. In this study we develop a new fuzzy ranking model based on the user preference. Through the experiments on the TREC-2 collection of Wall Street Journal documents, we show that the proposed method outperforms the conventional fuzzy ranking models.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.3
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• pp.326-331
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• 2006

A great deal of research has been made to model the vagueness and uncertainty in information retrieval. One such research is fuzzy ranking models, which have been showing their superior performance in handling the uncertainty involved in the retrieval process. In this study we develop a new fuzzy ranking model based on the user preference. Through the experiments on the TREC-2 collection of Wall Street Journal documents, we show that the proposed method outperforms the conventional fuzzy ranking models.

• Korean Journal of Mathematics
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• v.28 no.2
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• pp.343-359
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• 2020

The paper aim is to resolve the issue of ranking to the fuzzy numbers in decision analysis, artificial intelligence and optimization. In the literature lot of ideologies have been established for ranking to the fuzzy numbers, that ideologies have some restrictions and limitations. In this paper, we proposed a method based on cubic picture fuzzy information's, for ranking to defeat the existing restrictions. Further introduced some cubic picture fuzzy algebraic and cubic picture fuzzy algebraic^* aggregated operators for aggregated the information. Finally, a multi-attribute decision making problem is assumed as a practical application to establish the appropriateness and suitability of the proposed ranking approach.

• Communications of the Korean Mathematical Society
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• v.29 no.1
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• pp.187-193
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• 2014

In this paper, we want to represent a method for ranking of two exponential trapezoidal fuzzy numbers. In this study a new Cardinality between exponential trapezoidal fuzzy numbers is proposed. Cardinality in this method is relatively simple and easier in computation and ranks various types of exponential fuzzy numbers. For the validation the results of the proposed approach are compared with different existing approaches.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2002.05a
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• pp.145-148
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• 2002

Type-1 fuzzy value is used to show the uncertainty in a given value. But there exist many situations that it needs to be extended to type-2 fuzzy value because it is difficult to determine the crisp membership function itself. Intrinsically type-2 fuzzy values are more expressive and powerful than type-1 fuzzy values, but, at the same time, more difficult to be compared or ranked . In this paper, a ranking method for type-2 fuzzy values is proposed. It is based on the satisfaction function which shows the possibility that one type-2 fuzzy value is greater than the other type-2 fuzzy value Some properties of the proposed method are also analyzed .

• Journal of applied mathematics & informatics
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• v.26 no.3_4
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• pp.767-778
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• 2008

Comparison between two or more fuzzy numbers, along with their ranking, is an important subject discussed in scholarly articles. We endeavor in this paper to present a simple yet effective parametric method for comparing fuzzy numbers. This method offer significant advantages over similar methods, in comparing intersected fuzzy numbers, rendering the comparison between fuzzy numbers possible in different decision levels. In the process, each fuzzy number will be given a parametric value in terms of $\alpha$, which is dependent on the related $\alpha$-cuts. We have compared this method to Cheng's centroid point method [5] (The relation of calculating centroid point of a fuzzy number was corrected later on by Wang [12]). The proposed method can be utilized for all types of fuzzy numbers whether normal, abnormal or negative.

• Journal of the Korean Operations Research and Management Science Society
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• v.17 no.2
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• pp.35-43
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• 1992

In this paper fuzzy ranking method using dominance relation is suggested. This method is compared to the existing fuzzy number comparing methods. All ten methods with the suggested method are evaluated using six example based on four criteria.

• Proceedings of the Korean Radioactive Waste Society Conference
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• 2004.06a
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• pp.188-188
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• 2004

In the present study, a multicriteria decision-making (MCDM) problem of ranking of important radionuclide release scenarios in a low and intermediate radioactive waste repository is to treat on the basis of non-additive fuzzy measures and fuzzy integral theory. Ranking of important scenarios can lead to the provision of more effective safety measure in a design stage of the repository. The ranking is determined by a relative degree of appropriateness of scenario alternatives.(omitted)