Novel Multi-Criteria Decision Making Method based on The Ranking Values of Interval Type-2 Fuzzy Sets: An Application of a Manager Selection for a Telecommunication Company

Type-2 fuzzy sets (T2FSs), characterized by a fuzzy membership function, are much useful tool for representing the decision knowledge in the decision making process. Interval Type-2 fuzzy sets (IT2FSs) are the most commonly used T2FSs. In this study, a method based upon ranking values of IT2FSs is used to tackle multi-criteria decision making (MCDM) problems. First, some basic concepts and arithmetic operations for IT2FSs are presented. Then, three kinds of fuzzy ranking methods, proposed by [1], based on arithmetic average (AA), geometric average (GA) and harmonic average (HA) operators to compute the ranking values of IT2FSs are applied. Finally, the outcomes of MCDM methods based on the ranking values of IT2FSs are obtained and also compared with the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method based on Type-1 fuzzy sets (T1FSs) for a numerical example.

Aralık Tip-2 Bulanık Kümelerin Sıralanmasına dayalı Yeni Bir Çok Kriterli Karar Verme Yöntemi: Bir Telekomünikasyon Şirketi için Yönetici Seçimi Uygulaması

Bulanık üyelik fonksiyonuna sahip olan Tip-2 bulanık kümeler, karar verme aşamasında karar matrisinin belirlenmesinde çok kullanışlı bir araçtır. Aralık Tip-2 bulanık kümeler, en yaygın olarak kullanılan Tip-2 bulanık kümelerdir. Bu çalışmada, çok kriterli karar verme (ÇKKV) problemlerini çözmek için aralık Tip-2 bulanık kümelerin sıralanmasına dayalı bir yöntem kullanıldı. İlk olarak, aralık Tip-2 bulanık kümeler için bazı temel kavramlar ve aritmetik işlemleri tanıtıldı. Daha sonra, aralık Tip-2 bulanık kümelerin sıralama değerlerini hesaplamak için [1] tarafından önerilen, aritmetik ortalama (AO), geometrik ortalama (GO) ve harmonik ortalama (HO) işlemlerine dayalı 3 çeşit bulanık sıralama yöntemi uygulandı. Son olarak, aralık Tip-2 bulanık kümelerin sıralanmasına dayalı ÇKKV yönteminin sonuçları elde edildi ve sayısal bir örnek ile Tip-1 bulanık kümelere dayalı ideal çözüme yakınlığa göre tercihlerin sıralanması (TOPSIS) yöntemi ile karşılaştırıldı.

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