Cardinality inverse soft matrix theory and its applications in multicriteria group decision making
Yazarlar (4)
Doç. Dr. Hüseyin Kamacı Yozgat Bozok Üniversitesi, Türkiye
Kader Saltık
Bozok Üniversitesi, Türkiye
Doç. Dr. Hürmet Fulya Akız Yozgat Bozok Üniversitesi, Türkiye
Prof. Dr. Akın Osman ATAGÜN Kırşehir Ahi Evran Üniversitesi, Türkiye
Makale Türü Özgün Makale (SSCI, AHCI, SCI, SCI-Exp dergilerinde yayınlanan tam makale)
Dergi Adı JOURNAL OF INTELLIGENT & FUZZY SYSTEMS (Q3)
Dergi ISSN 1064-1246 Dergi Bilgileri (2018)
Dergi Tarandığı Indeksler SCI-Expanded
Makale Dili İngilizce Basım Tarihi 01-2018
Kabul Tarihi Yayınlanma Tarihi 22-03-2018
Cilt / Sayı / Sayfa 34 / 3 / 2031–2049 DOI 10.3233/JIFS-17876
Makale Linki http://www.medra.org/servlet/aliasResolver?alias=iospressdoi=10.3233/JIFS-17876
UAK Araştırma Alanları
Cebir ve Sayılar Teorisi
Özet
The main objective of this paper is to present a novel decision making algorithm using matrix representation of the inverse soft set defined in . Therefore, we first introduce cardinality inverse soft matrix theory and its operations, products and algebraic structures in detail. Afterwards, an algorithmic solution employing the cardinality inverse soft matrix to find the optimum object and the ranking order of objects is proposed. The performance of algorithm named soft sum-row decision making algorithm is demonstrated by solving various decision problems. Also, we compare it with existing algorithms based on the soft set theory, soft matrix theory and inverse soft set theory. Moreover, we give Scilab codes of the algorithm and argue that this codes make the process of decision making composed of many objects, criteria and decision makers faster and easier.
Anahtar Kelimeler
cardinality inverse soft matrix | Inverse soft set | operations of cardinality inverse soft matrix | soft sum-row decision making
BM Sürdürülebilir Kalkınma Amaçları
Atıf Sayıları
Web of Science 25
Scopus 27
Google Scholar 46
Cardinality inverse soft matrix theory and its applications in multicriteria group decision making

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