Please use this identifier to cite or link to this item: https://hdl.handle.net/11499/47329
Title: The Novel Integrated Model of Plithogenic Sets and MAIRCA Method for MCDM Problems
Authors: Özçil, Abdullah
Tuş, Ayşegül
Öztaş, Gülin Zeynep
Aytaç Adalı, Esra
Öztaş, Tayfun
Keywords: Green supplier selection
MAIRCA
MCDM
Plithogenic sets
Automotive industry
Green manufacturing
Aggregation operation
Comparative analysis
Decision making process
Green supplier selections
Integrated modeling
Performance value
Real-world problem
Uncertain environments
Decision making
Publisher: Springer
Abstract: The most of the decision making processes contain uncertainty due to the real world problems. In order to deal with this uncertainty, different set theories have been introduced in the literature. Plithonegic set is the relatively newest one among them. The concept of plithogeny which was developed by Smarandache [4] is the generalizations of neutrosophic sets, logic, probability, and statistics. Two main elements, contradiction and appurtenance degrees, of plithogenic set help to improve the accuracy of the results under the uncertain environment. In this study, it is aimed to propose a model based on plithogenic sets and the MAIRCA (Multi-Attributive Ideal-Real Comparative Analysis) method. To the best of our knowledge plithonegic sets are integrated for the first time in this study with the MAIRCA method which aims to minimize the gap between ideal and empirical values. A case study about green supplier selection problem in the automotive industry adapted from Gupta et al. [18] is handled to show the applicability of the proposed model. The plithogenic aggregation operations are performed to aggregate different decision makers’ opinions on criteria performance values with respect to each green supplier. Results have showed that the MAIRCA method could be integrated with plithonegic sets efficiently. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.
Description: International Conference on Intelligent and Fuzzy Systems, INFUS 2020 -- 21 July 2020 through 23 July 2020 -- 242349
URI: https://doi.org/10.1007/978-3-030-51156-2_85
https://hdl.handle.net/11499/47329
ISBN: 9783030511555
ISSN: 2194-5357
Appears in Collections:İktisadi ve İdari Bilimler Fakültesi Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

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