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Novel Entropy Measure Definitions and Their Uses in a Modified Combinative Distance-Based Assessment (CODAS) Method Under Picture Fuzzy Environment
Volume 32, Issue 4 (2021), pp. 759–794
Sait Gül   Ali Aydoğdu  

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https://doi.org/10.15388/21-INFOR458
Pub. online: 4 August 2021      Type: Research Article      Open accessOpen Access

Received
1 January 2021
Accepted
1 July 2021
Published
4 August 2021

Abstract

From the perspective of multiple attribute decision analysis, the evaluation of decision alternatives should be based on the performance scores determined with respect to more than one attribute. Fuzzy logic concepts can equip the evaluation process with different scales of linguistic terms to let the decision-makers point out their ideas and preferences. A more recent one of fuzzy sets is the picture fuzzy set which covers three separately allocable elements: positive, neutral, and negative membership degrees. The novel and distinctive element included by a picture fuzzy set is the refusal degree which is equal to the difference between 1 and the sum of the other three. In this study, we aim to contribute to the literature of the picture fuzzy sets by (i) proposing two novel entropy measures that can be used in objective attribute weighting and (ii) developing a novel picture fuzzy version of CODAS (COmbinative Distance-based ASsessment) method which is empowered with entropy-based attribute weighting. The applicability of the method is shown in a green supplier selection problem. To clarify the differences of the proposed method, a comparative analysis is provided by considering traditional CODAS, spherical fuzzy CODAS, and spherical fuzzy TOPSIS with different entropy-based scenarios.

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Biographies

Gül Sait
https://orcid.org/
sait.gul@eng.bau.edu.tr

S. Gül is an assistant professor at Management Engineering Department of Bahçeşehir University Faculty of Engineering and Natural Sciences. He received his BSc degrees in maritime transport and management engineering (2007) and industrial engineering (2008) from Istanbul University and holds his MSc in engineering management (2012) and PhD in industrial engineering (2017), both from Istanbul Technical University. His research interests include operation research, multiple criteria decision analysis, fuzzy theory applications, knowledge management and big data analysis.

Aydoğdu Ali
aaydogdu@msu.edu.tr

A. Aydoğdu graduated from Kazım Karabekir Faculty of Education of Atatürk University, in 2008. He received his PhD degree in mathematics from the Institute of Natural and Applied Sciences of Atatürk University, in 2014. Presently, he is an assistant professor at Turkish National Defense University, İzmir. His research interests include fuzzy sets, fuzzy logic, number theory, math basics, and mathematical logic.


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Keywords
picture fuzzy sets CODAS entropy information measures expert judgment green supply chain management supplier selection

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