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Issue title: Special section: Decision Making Using Intelligent and Fuzzy Techniques
Guest editors: Cengiz Kahraman
Article type: Research Article
Authors: Ercan-Teksen, Haticea; * | Anagün, Ahmet Sermetb
Affiliations: [a] Department of Industrial Engineering, Eskisehir Osmangazi University, Meselik Campus, Odunpazari, Eskisehir, Turkey | [b] Department of Industrial Engineering, Izmir University of Economics, Sakarya Street, Balcova, Izmir, Turkey
Correspondence: [*] Corresponding author. Hatice Ercan-Teksen, Department of Industrial Engineering, Eskisehir Osmangazi University, Meselik Campus, Odunpazari, Eskisehir, Turkey. E-mail: [email protected].
Abstract: Control chart is one of the statistical methods to analyze the process. The use of fuzzy sets in control charts, which are divided into qualitative and quantitative data, has been applied in many studies recently. Especially for qualitative control charts, data collection is more difficult and more subjective. Therefore, fuzzy sets are used to reduce losses in data. There are many control chart studies created by type-1 fuzzy sets available in the literature. In recent years, examples of fuzzy control charts with extensions of fuzzy sets have been found. The aim of this study is to obtain c-control chart for intuitionistic fuzzy sets. For this purpose, defuzzification and likelihood methods are used. In particular, with the application of the likelihood method to intuitionistic fuzzy control charts, this will be considered as a pioneering study in the literature. In addition, a novel likelihood method was developed for intuitionistic fuzzy sets and used here to provide flexibility.
Keywords: Intuitionistic fuzzy sets, fuzzy control charts, intuitionistic fuzzy comparison methods
DOI: 10.3233/JIFS-189110
Journal: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 5, pp. 6465-6473, 2020
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