Sezgisel bulanık çok uzmanlı & çok ölçütlü karar verme metodolojisi: sağlık sektöründe bir uygulama

Bulanık küme uzantıları son yıllarda çok sayıda araştırmada kullanılan, belirsizliği ele alma araçlarından biridir. Fakat bu uzantılar arasındaki ilişkilerin ve geçişlerin yazında yeteri kadar tartışılmadığı da bir gerçektir. 1990’lı yıllardan itibaren bulanık karar verme teorisi yazında en çok araştırılan konulardan biri olmuştur. Özellikle son yıllarda çok sayıda bulanık karar verme modeli yeni bulanık küme uzantıları kullanılarak önerilmiştir. Çok ölçütlü karar verme modelleri, bu uzantıların sıkça kullanıldığı bir araştırma alanı olmuştur. Bu çalışmada, üçgensel sezgisel bulanık kümeler kullanılarak tanımlanmış bir bütünleşik AHY-TOPSIS metodolojisi, aralık değerli üçgensel bulanık sayıların kullanılabileceği bir metodolojiye dönüştürülmüştür. Uygulama alanı olarak, İstanbul’da faaliyet gösteren bir hastaneler grubunun yeni açacağı hastane için ameliyat robotu değerlendirme ve seçim problemi incelenmiştir. Elde edilen sonuçlar, farklı bulanık küme uzantı tabanlı veri kümelerinin birbirlerine dönüştürülerek aynı metodolojide başarıyla kullanılabileceğini göstermiştir. Bu çalışmada ayrıca karşılaştırma ve duyarlılık analizleri yapılmış ve önerilen modelin sonuçlarının oldukça gürbüz ve tutarlı olduğu gözlemlenmiştir.

Intuitionistic fuzzy multi-expert & multi-criteria decision making methodology: an application in healthcare industry

Fuzzy set extensions have been one of the uncertainty handling tools used in many studies in recent years. However, it is a fact that the relations and transformations between these extensions have not been discussed sufficiently in the literature. Since the 1990s, fuzzy decision making theory has been one of the most studied topics in the literature. Specifically in recent years, many fuzzy decision making models have been proposed by using new fuzzy set extensions. Multi-criteria decision making models have been a research area where these extensions are frequently used. In this study, an integrated AHP-TOPSIS methodology employing triangular intuitionistic fuzzy numbers has been transformed into a methodology in which interval-valued triangular fuzzy numbers can be used. As an application, a surgery robot evaluation and selection problem for a newly founded private hospital to be a part of a hospital chain in Istanbul, has been analyzed. The obtained results showed that different fuzzy set extension based datasets can be successfully used in the same methodology by converting them to each other. In this study, comparison and sensitivity analyses are also performed and it has been observed that the results of the proposed model are quite robust and consistent.

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