KALİTE VE MİKTAR BELİRSİZLİKLERİ ALTINDA GERİ DÖNÜŞÜM AĞ TASARIMI

Günümüzde tersine lojistik (TL) önemli bir karlı ve sürdürülebilir iş stratejisi olarak giderek artan bir şekilde önem kazanmaktadır. İşletmeler ise politik, ekonomik ve çevresel baskılardan dolayı TL faaliyetlerini uygulamak zorunda kalmaktadırlar. TL ağlarının en karakteristik özelliği ise ağ tasarımında kullanılan bazı parametre değerlerinin bilinmediği durumlarda ortaya çıkan belirsizliktir. TL ağları geri dönen ürünün zaman, miktar ve kalitesi ile ilgili yüksek oranda belirsizlik içermektedir. Deterministik modeller ise doğasında belirsizlikleri içeren TL ağlarını tasarlamakta yetersiz kalmaktadır. Bu çalışmada belirsizlikler altında çok aşamalı, çok ürünlü, kapasite ve tesis sayısı kısıtlı iki aşamalı stokastik programlama modeli önerilmiştir. Önerilen modelin çözümünde örneklem yakınsama yaklaşımı şeması kullanılmıştır. Çalışmada geliştirilen genel TL ağ tasarım modeli Türkiye’de elektrikli ve elektronik atıkların geri dönüşümü alanında hizmet vermekte olan tersine lojistik firmasının ağ tasarım problemi için uygulanmıştır. Sonuçlar geliştirilen stokastik programlama modelinin ekonomik açıdan etkin olduğunu göstermekte ve belirsizlikleri gidererek yöneticilere stratejik yatırım kararı almada yardımcı olabileceğini göstermektedir

Anahtar Kelimeler:

Tersine Lojistik Ağ Tasarımı, Stokastik Programlama, Örneklem Ortalama Yakınsaması

KALİTE VE MİKTAR BELİRSİZLİKLERİ ALTINDA GERİ DÖNÜŞÜM AĞ TASARIMI

In recent years, reverse logistics (RL) has received increasing attentions in supply chain management area due to economic, political, and environmental reasons. In RL, the time, quantity, and quality of returned products have a high degree of uncertainty. Deterministic models for reverse network design lack the ability to incorporate such uncertainties. In this study, we considered reverse logistics network design (RLND) problem under return quantity and quality uncertainties. We presented multi-stage, multi-product and the capacity constraited two stage stochastic programing model to take into consideration uncertainties in RLND as a real world case study of waste of electric and the waste of electrical and electronic equipment recycling firm in Turkey to minimize total cost. Sample average approximation schema was developed in solution process. The results show that the developed two stage stochastic programming model provides acceptable solutions to make efficient decisions under quantity and quality uncertainties

Keywords:

Reverse Logistics Network Design, Stochastic Programming, Sample Average Approximation,

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