Please use this identifier to cite or link to this item: https://scidar.kg.ac.rs/handle/123456789/21716
Title: Industrial and management applications of type-2 multi- 2 attribute decision-making techniques extended with type-2 3 fuzzy sets from 2013 to 2022
Authors: Aleksic, Aleksandar
Tadić, Danijela
Journal: Mathematics
Issue Date: 2023
Abstract: The ongoing research in the field of decision-making can be analyzed from different 8 perspectives. Research trends indicate that multi-attribute decision-making (MADM) methods have 9 a significant impact on engineering and management scientific areas. Since many of the problems 10 existing in the mentioned areas are associated with a certain level of uncertainty, type 2 fuzzy sets 11 represent a common solution for the enhancement of conventional MADM methods. In this way, 12 the decision-makers are encouraged to use linguistic expressions for the assessment of attributes' 13 relative importance and their values. The purpose of this paper is to review a determination of 14 attributes' relative importance, and their values, as well as the extension of ranking methods with 15 type 2 fuzzy sets. The papers are systematically adjoined to groups consisting of hybrid models with 16 the following characteristics: (1) indicating the procedure for modeling attribute relative importance 17 and their values, (2) determining the extension of MADM methods with type 2 fuzzy sets to 18 determine attributes’ vector weights, (3) extension of MADM for attributes ranking with type 2 19 fuzzy sets. This study reviewed a total of 42 papers in the domain of engineering and management 20 published from 2013 to 2023 in different journals indexed by the Springer, Science Direct, Emerald, 21 Wiley, ProQuest, Taylor, and Francis research platforms.
URI: https://scidar.kg.ac.rs/handle/123456789/21716
Type: article
DOI: https://doi.org/10.3390/math11102249
ISSN: 2227-7390
Appears in Collections:Faculty of Engineering, Kragujevac

Page views(s)

12

Downloads(s)

1

Files in This Item:
File Description SizeFormat 
mathematics-2371642-peer-review-r2.pdf810.18 kBAdobe PDFThumbnail
View/Open


Items in SCIDAR are protected by copyright, with all rights reserved, unless otherwise indicated.