Decision analysis review on the concept of class for bipolar soft set theory
Computational and Applied Mathematics, cilt.41, sa.5, 2022 (SCI-Expanded, Scopus)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 41 Sayı: 5
- Basım Tarihi: 2022
- Doi Numarası: 10.1007/s40314-022-01922-2
- Dergi Adı: Computational and Applied Mathematics
- Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Applied Science & Technology Source, Computer & Applied Sciences, zbMATH
- Anahtar Kelimeler: Algorithm, Bipolar soft classes, Bipolar soft rough classes, Decision making
- Kütahya Sağlık Bilimleri Üniversitesi Adresli: Hayır
Özet
To eliminate uncertainty, all data expressed by decision-makers must be processed correctly. The most useful mathematical models developed for this purpose are hybrid set types. Because they collect all the features of the set types they contain under a single model. In this paper, the bipolar soft rough sets, which are a combination of bipolar soft sets and rough sets, which have been actively preferred in studies aimed at eliminating uncertainty in recent years, have been taken into account. To use the bipolar soft rough sets discussed more actively in the decision-making process, the focus is on handling the data expressed by different decision-makers together. The aim of this paper is to develop the concept of "bipolar soft rough classes" to aim to highlight this contribution to bipolar soft rough set theory. Thus, the concept of bipolar soft rough classes is introduced and a more efficient decision-making algorithm for uncertainty problems is built. Moreover, many novel concepts such as bipolar soft class, bipolar soft partition and bipolar soft cover were proposed and some properties are examined in detail.