ÜÇÜNCÜ TARAF LOJİSTİK SAĞLAYICI SEÇİMİNDE PFAHP-GTOPSIS YÖNTEMLERİNİN UYGULANMASI

Year 2024, Volume: 14 Issue: 1, 393 - 413, 25.03.2024

Sinan Çizmecioğlu , Esra Boz , Ahmet Çalık

https://doi.org/10.30783/nevsosbilen.1435092

Abstract

Küresel pazarlardaki rekabet, daha kaliteli ürün kullanımı ve artan müşteri talepleri nedeniyle tedarik zincirlerini güncellemek için temel becerilerine odaklanarak riskten korunmanın maliyet yaratması ve verimliliği artırması nedeniyle şirketler artık dış kaynak kullanma seçeneğini değerlendiriyor. Bu şirketler lojistikle ilgili birçok görevi Üçüncü Taraf Lojistik Sağlayıcılarına (3TLS) devretmeden önce hangi şirketle iş birliği yapacaklarını dikkatlice seçmeli ve belirlemelidirler. Ancak 3TLS seçim problemlerinde belirsizliklerin ve insan etkisinin varlığı, bulanık veya ilgili küme teorilerinin kullanılmasına yol açmaktadır. Çok Kriterli Karar Verme (ÇKKV) yöntemlerinin bulanık sayılar ve gri sayılarla birleştirilmesiyle, öznel yargıların belirsizliğini giderecek pratik araçlar oluşturulabilir. Bu perspektiften bakıldığında, 3PLP değerlendirme ve seçimine ışık tutacak bütünleşmiş bir ÇKKV modeli önerilmiştir. Önerilen model, Pisagor bulanık sayıları ve gri sayılardan oluşan entegre bir çerçeveden oluşmaktadır ve ilgili model gıda endüstrisindeki bir şirkette müşteri siparişlerini teslim etmek için kullanılan 3TLS'ye uygulanmıştır. Değerlendirme kriterleri ağırlıkları, Pisagor Bulanık Analitik Hiyerarşi Süreci (PBAHS) yöntemi kullanılarak hesaplanır ve 3PLP'ler, en iyi 3TLS'yi bulmak için Gri İdeal Çözüme Benzerliğe Göre Sipariş Tercihi Tekniği (GTOPSIS) yöntemleri kullanılarak sıralanır. Analizler ve bulgular, maliyet, hizmet kalitesi ve zamanında teslimatın en büyük etkiye sahip üç kriter olduğu sonucuna varmıştır.

Keywords

Gri TOPSIS, Çok Kriterli Karar Verme, Pisagor Bulanık AHP, Üçüncü Taraf Lojistik Sağlayıcısı.

APPLICATION OF PFAHP-GTOPSIS METHODS FOR THIRD-PARTY LOGISTICS PROVIDER SELECTION

Abstract

Companies are now considering the option of outsourcing as hedges cost and increase productivity by concentrating on their core skills to update their supply chains due to the competition in global markets, the use of higher-quality products, and rising customer demands. They must carefully select and identify which company to collaborate with before outsourcing their numerous logistics-related tasks to Third-Party Logistics Providers (3PLP). However, the existence of uncertainties and human influence in 3PLP selection problems leads to the usage of fuzzy or related set theories. By incorporating Multi-Criteria Decision Making (MCDM) methods with fuzzy numbers and grey numbers, practical tools can be composed to address the imprecision of subjective judgments. From this perspective, an integrated MCDM model is proposed to provide insight into the 3PLP evaluation and selection. The model comprises an integrated framework with Pythagorean fuzzy numbers and grey numbers. The proposed model has applied a 3PLP a company in the food industry to fulfill customer orders. The evaluation criteria weights are calculated using the Pythagorean Fuzzy Analytic Hierarchy Process (PFAHP) method, and the 3PLPs are ranked using the grey Technique for Order Preference by Similarity to Ideal Solution (GTOPSIS) methods to find the best 3PLP. The analyses and findings concluded that cost, service quality, and on-time delivery were the three criteria that had the greatest influence

Keywords

Grey TOPSIS, Multi-Criteria Decision-Making, Pythagorean Fuzzy AHP, Third-Party Logistics Provider

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