Ekonomik Göstergelere Dayalı Tedarikçi Seçimi için Sezgisel Bulanık Yaklaşım

Abstract

Artan rekabet ortamında varlığını sürdürmek isteyen işletmeler için tedarikçi seçim ve değerlendirmeleri önemli bir yere sahiptir. İşletmeler uygun tedarikçi seçimi ile müşteri beklentilerini en iyi şekilde karşılamayı hedeflemektedir. Bu çalışmada, tedarikçi seçimi ve değerlendirmeleri için sezgisel bulanık kümelere dayalı bütünleşik bir yaklaşım önerilmektedir. Önerilen yaklaşım ile karar verici algı farklılıkları kaynaklı belirsizlikler ait olma ve ait olmama dereceleri ile detaylı şekilde incelenmektedir. Bu yaklaşım, inşaat sektöründe faaliyet gösteren bir işletmenin tedarikçi seçimi ve değerlendirmelerine uygulanmıştır. Uygulamada, ekonomik kriterlere dayalı karar verici öznel değerlendirmeleri ile işletme mevcut değerlendirme puanları birleştirilerek karma veritabanı oluşturulmuştur. Klasik ve bulanık öbekleme yaklaşımları ile tedarikçi firma sıralama ve sınıflandırmaları elde edilmiştir. Karma veritabanı için bulanık öbekleme yapısı %99,1; klasik öbekleme yapısı ise %94,4 doğruluk oranı ile oluşmuştur. Ayrıca, bulanık ve klasik öbekleme sonuçları içerisinde sadece tedarikçi değerlendirme puanlarına ait öbeklemenin, sırasıyla, %90,7 ve %74,1 doğruluk oranına sahip olduğu görülmüştür. Algı farklılıklarının tedarikçi seçimine yönelik karar almadaki etkileri önerilen bütünleşik yaklaşımla açıklanmıştır.

Keywords

• sezgisel bulanık küme
• tedarikçi seçimi
• belirsizlik
• bulanık öbek ortalamaları
• k-ortalamalar

Intuitionistic Fuzzy Approach for Supplier Selection Based on Economic Indicators

Abstract

Supplier selection and evaluation is an important issue for organizations to cope with increasing competitive environment. Companies aim to meet customer expectations with selection of appropriate supplier. In this study, an integrated approach based on intuitionistic fuzzy sets is proposed for supplier selection and evaluation. In the proposed approach, uncertainties arising from discrepancies in decision-makers' perception are examined in detail with belonging and non-belonging degrees. This approach was applied to supplier selection and evaluations of a construction company. In practice, a mixed database was created by combining the subjective evaluations of decision makers based on economic criteria and current evaluation scores of the company. Supplies were sorted and classified using the classical and fuzzy clustering approaches. For the mixed database, fuzzy and classical clustering structures were created with 99.1% and 94.4% accuracy rates, respectively. Besides, within the fuzzy and classical clustering-results, classification-accuracy rates of only supplier evaluation scores were found as 90.7% and 74.1%, respectively. The effects of perception discrepancies on decision making for supplier selection were explained by means of the proposed integrated approach.

Keywords

• Intuitionistic fuzzy set
• supplier selection
• uncertainty
• fuzzy c-means
• k-means

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