A New Fuzzy Inventory Model for the Recycling Process

Abstract

Making products that have reached the end of their lifespan reusable after several processes provide many benefits to human beings in environmental, economic, and social areas. The importance of the recycling industry is increasing worldwide due to its benefits such as environmental protection, reduction of raw material needs, economical use of resources, and reduction of pollution. In this study, a fuzzy inventory model including the recycling process is proposed. Firstly, an expanded production/recycling model with fixed demand and return rates developed by Dobos and Richter (2003) is rearranged in terms of the waste disposal process and the level of stock to be created. Then, the model is fuzzified by taking the demand, marginal recovery, and marginal utilization rate parameters as trapezoidal fuzzy numbers. The graded mean integration representation method was used for the defuzzification process. Thus, the total cost per unit time and the optimal cycle time are expressed as deterministic values. When the results of the solved problem are evaluated, it is observed that the proposed fuzzy stock model gives better results for cycle times compared to the deterministic stock model based on.

Keywords

• Inventory Model
• Recycling
• Fuzzy Logic
• GMIR Model

Geri Dönüşüm Süreci İçin Yeni Bir Bulanık Envanter Modeli

Abstract

Kullanım ömrü sona eren ürünlerin çeşitli işlemlerden sonra yeniden kullanılabilir hale getirilmesi çevresel, ekonomik ve sosyal alanlarda insanoğluna birçok fayda sağlar. Çevrenin korunması, hammadde ihtiyacının azalması, kaynakların ekonomik kullanımı ve kirliliğin azaltılması gibi faydaları nedeniyle de geri dönüşüm sektörünün önemi dünya çapında giderek artmaktadır. Bu çalışmada, geri dönüşüm sürecini içeren bulanık bir stok modeli önerilmiştir. İlk olarak, Dobos ve Richter (2003) tarafından geliştirilen sabit talep ve geri dönüş oranlarına sahip genişletilmiş bir üretim/geri dönüşüm modeli atıkların yok edilme süreci ve oluşacak stok düzeyi bakımından yeniden düzenlenmiştir. Ardından talep, marjinal geri alma ve marjinal kullanım oranı parametreleri yamuk bulanık sayı olarak kabul edilip model bulanıklaştırılmıştır. Durulaştırma işlemi için kademeli ortalama entegrasyon temsil yöntemi kullanılmıştır. Böylece birim zamandaki toplam maliyet ve optimal çevrim süresi deterministik değerler olarak ifade edilmiştir. Çözülen problemin sonuçları değerlendirildiğinde, önerilen bulanık stok modelinin temel alınan deterministik stok modeline kıyasla çevrim süresi bakımından daha iyi sonuçlar verdiği gözlemlenmiştir.

Keywords

• Stok modeli
• Geri Dönüşüm
• Bulanık Mantık
• GMIR Modeli
• Inventory Model
• Recycling
• Fuzzy Logic
• GMIR Model

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