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Title: An extended step-wise weight assessment ratio analysis with symmetric interval Type-2 fuzzy sets for determining the subjective weights of criteria in Multi-Criteria Decision-Making problems
Authors: Keshavarz-Ghorabaee, Mehdi
Amiri, Maghsoud
Zavadskas, Edmundas Kazimieras
Turskis, Zenonas
Antuchevičienė, Jurgita
Keywords: multi-criteria decision-making (MCDM)
group decision-making
interval type-2 fuzzy set (IT2FS)
subjective weights
criteria weights
Step-wise Weight Assessment Ratio Analysis (SWARA)
Issue Date: 2018
Publisher: MDPI
Citation: Keshavarz-Ghorabaee, M.; Amiri, M.; Zavadskas, E.K.; Turskis,Z.; Antucheviciene, J. 2018. An extended step-wise weight assessment ratio analysis with symmetric interval Type-2 fuzzy sets for determining the subjective weights of criteria in Multi-Criteria Decision-Making problems, MDPI 10(4): 1-15
Series/Report no.: 10;4
Abstract: Determination of subjective weights, which are based on the opinions and preferences of decision-makers, is one of the most important matters in the process of multi-criteria decision-making (MCDM). Step-wise Weight Assessment Ratio Analysis (SWARA) is an efficient method for obtaining the subjective weights of criteria in the MCDM problems. On the other hand, decision-makers may express their opinions with a degree of uncertainty. Using the symmetric interval type-2 fuzzy sets enables us to not only capture the uncertainty of information flexibly but also to perform computations simply. In this paper, we propose an extended SWARA method with symmetric interval type-2 fuzzy sets to determine the weights of criteria based on the opinions of a group of decision-makers. The weights determined by the proposed approach involve the uncertainty of decision-makers’ preferences and the symmetric form of the weights makes them more interpretable. To show the procedure of the proposed approach, it is used to determine the importance of intellectual capital dimensions and components in a company. The results show that the proposed approach is efficient in determining the subjective weights of criteria and capturing the uncertainty of information.
URI: http://dspace.vgtu.lt/handle/1/3749
ISSN: 2073-8994
Appears in Collections:Moksliniai straipsniai / Research articles

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