Investigation of Cotton Production Companies Transition to Industry 4.0 Using the Intuitionistic Fuzzy TOPSIS

Author(s):  
Merve Çil ◽  
Babak Daneshvar Rouyendegh
2019 ◽  
Vol 6 (2) ◽  
pp. 20-32
Author(s):  
Daniel Osezua Aikhuele

In this article, the effectiveness of the intuitionistic fuzzy TOPSIS model (IF-TOPSISEF) is tested for addressing, capturing, and resolving the effect of correlation between attributes, otherwise called the dependency of attributes. This was achieved by using several normalization methods in the implementation of the IF-TOPSISEF model. Furthermore, the result of the computation is compared with the one obtained when the normalization methods are implemented using a traditional TOPSIS model. The study contributes and extends the state of the art in TOPSIS method study, by addressing, capturing and resolving the effect of correlation between attributes otherwise called dependency of attributes.


“Intuitionistic Fuzzy Set” (IFS) is used to manage nebulousness and indecision. In current investigation, another intuitionistic fuzzy TOPSIS method is proposed for decision making by utilizing entropy weight. Current model permits estimating the degree of membership and non-membership of various alternatives assessed over a criterion set. A case study has been carried out to diagnosis of vector borne disease. Criteria’s have been selected according to relevant disease and weight has been assigned to them by medical expert’s committee. It has been established that TOPSIS method can diagnose the VBD diseases using specific symptoms as criteria and VBDs as alternatives. The suggested methodology can help in correct and timely diagnosis of VBDs and provides doctors an innovative diagnostic tool (WHO, 2004; WHO, 2014). The result is validated by applying fuzzy VIKOR method.


2019 ◽  
Vol 25 (3) ◽  
pp. 22-32
Author(s):  
EZGİ GÜLER ◽  
SELEN AVCI ◽  
ZERRİN ALADAĞ

In this study, we examined the project selection process in a mould manufacturing company. We ranked 12 criteria via Analytic Hierarchy Process (AHP) and evaluated the most important 8 criteria. Then we applied Intuitionistic Fuzzy TOPSIS (IF-TOPSIS) method, which is the extended version of the TOPSIS method in intuitionistic fuzzy environment. After expressing the decision makers' evaluations in linguistic terms, we turned them into intuitive fuzzy numbers. In the last step, we obtained the project rankings by calculating the closeness coefficient for 5 projects.


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