Ranking of fuzzy numbers by using value and angle in the epsilon-deviation degree method

Chutia, Rituparna

doi:10.1016/j.asoc.2017.07.025

Cited by 40 publications

(26 citation statements)

References 46 publications

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“…Namely, A i 1 : availability of land, A i 2 : financial support, A i 3 : availability of expert labor, A i 4 : availability of clean water, A i 5 : transportation, A i 6 : availability of electricity, A i 7 : food supply, and A i 8 : good poultry baby. These alternates are main factors that should be considered for a fruitful result from the poultry farming (Chutia, ; ; Chutia & Gogoi, ; ). As discussed earlier, probabilistic values of the alternates A i 1 , A i 2 ,…, A i 8 are not precise that lead to consider them as TrIFNs.…”

Section: Application Of the Proposed Methods In Risk Analysismentioning

confidence: 99%

Ranking intuitionistic fuzzy numbers at levels of decision‐making and its application

Chutia

Saikia

2018

Expert Systems

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In this paper, a new method of ranking trapezoidal intuitionistic fuzzy numbers has been introduced based on the concept of value and ambiguity at different levels of decision‐making. The concept of decision levels α for the membership function and β for the non‐membership function called as the flexibility parameters have been introduced in ranking these types of fuzzy numbers. If the flexibility parameters α is close to maximum membership degree of the membership function and β close to minimum membership degree of non‐membership function, then a high‐level decision is made. Likewise, if the flexibility parameters α is close to minimum membership degree of membership function and β close to maximum membership degree of non‐membership function, then a low‐level decision is made. Again, if the flexibility parameters α and β lie between minimum membership degree of the membership function and maximum membership degree of the non‐membership function, then an intermediate decision is made. This phenomenon of the proposed method is an attractive feature as it allows the decision‐maker to make a choice on the levels of decision. Further, the rationality validation of the proposed method has been checked by proving some of the Wang and Kerre's reasonable properties on ordering fuzzy quantities.

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Section: Application Of the Proposed Methods In Risk Analysismentioning

confidence: 99%

Ranking intuitionistic fuzzy numbers at levels of decision‐making and its application

Chutia

Saikia

2018

Expert Systems

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“…According to the literature, fair voting procedures should, in the ideal case, fulfil the criteria [40] listed below, where the term "candidate" has a context-related interpretation:…”

Section: Votingmentioning

confidence: 99%

“…Voting adaption possibilities are restricted (which is shown e.g., by the well-known Arrows impossibility theorem [42]). The authors of [40] demonstrate that no voting procedure exists which would satisfy all the above listed criteria simultaneously. However, it is usually possible to develop a quasi-fair estimation method.…”

Section: Votingmentioning

confidence: 99%

“…On top of that, we will need a method of comparing fuzzy numbers. This issue is rather complex and has been treated in a vast number of literature positions (e.g., [40,46,47]), as comparing fuzzy numbers is not unequivocal. Here, we propose to use one of many possible ways of defining the distance and the similarity degree between two triangular fuzzy numbers [48].…”

Section: Definitionmentioning

confidence: 99%

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Application of Fuzzy Sets to the Expert Estimation of Scrum-Based Projects

Rola

Kuchta

2019

Symmetry

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The paper is basically dedicated to the problem of effort estimation for the Product Backlog items of IT projects led accordingly to the Scrum framework. The effort estimation issue is important, because low quality estimation decreases the efficiency of project implementation. The paper proposes an estimation method for the Product Backlog items of Scrum-based IT projects (which can be adapted also to other projects), which has two original elements with respect to the state of art in Scrum estimation: the usage of fuzzy numbers and strict rules for consensus forming, combined with a space for human interaction. The assumptions of the method should be complied with and were formulated on the basis of literature and authors experience. Two case studies were used for an initial method validation. The case studies confirmed a high potential of the method to increase estimation quality in Scrum-based projects, as well as in other project types. The case studies were conducted using research methods fulfilling the symmetry principle. The paper is thus an example of symmetry in management research.

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“…This method of ranking fails when the decision level 1   and height 1 w  . Owing to some drawbacks of this method, a modified epsilon-deviation degree method is proposed by Chutia [27]. Bortolan & Degani [28]; Wang & Kerre [29] and Brunelli & Mezei [30] made a thorough review of the available methods, and observed some inappropriate and illogical conditions among them.…”

Section: Introductionmentioning

confidence: 99%

Defuzzification Index for Ranking of Fuzzy Numbers on the Basis of Geometric Mean

Veerraju¹,

Prasannam²,

Rallabandi³

2020

IJISA

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The importance of fuzzy numbers to express uncertainty in certain applications, concerned with decision making, is observed in a large number of problems of different kinds. In Decision making problems, the best of available alternatives is chosen to the possible extent. In the process of ordering the alternatives, ranking of fuzzy numbers plays a key role. A large volume of ranking methods, based on different features, have been available in this domain. Owing to the complicated nature of fuzzy numbers, the so far introduced methods suffered setbacks or posed difficulties or showed drawbacks in one context or other. In addition, some methods are lengthy and complicated to apply on concerned problems. In this article, a new ranking procedure based on defuzzification, stemmed from the concepts of geometric mean and height of a fuzzy number, is proposed. Finally, numerical comparisons are made with other existing procedures for testing and validation of proposed method with the support of some standard numerical examples.

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Ranking of fuzzy numbers by using value and angle in the epsilon-deviation degree method

Cited by 40 publications

References 46 publications

Ranking intuitionistic fuzzy numbers at levels of decision‐making and its application

Ranking intuitionistic fuzzy numbers at levels of decision‐making and its application

Application of Fuzzy Sets to the Expert Estimation of Scrum-Based Projects

Defuzzification Index for Ranking of Fuzzy Numbers on the Basis of Geometric Mean

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