ÇOK PERİYOTLU ÇOK ÜRÜNLÜ KAPALI DÖNGÜ TEDARİK ZİNCİRİ İÇİN YENİ BİR ÇİFT-AMAÇLI MODEL

Kapalı döngü tedarik zinciri (KDTZ), bir lojistik ağ içinde ürünlerin ileri ve geri akışlarını içeren bir tür tedarik zinciridir. KDTZ'nin karar verme sürecinde, stratejik, taktik ve operasyonel kararlarla başa çıkmak için lokasyon, envanter kontrolü ve taşıma konuları ele alınmaktadır. Bu araştırma, aynı anda hem toplam maliyet minimizasyonu hem de hizmet seviyesi maksimizasyonu dikkate alınarak çok periyotlu ve çok ürünlü bir CLSC tasarım problemini formüle etmek için yeni bir çift-amaçlı karma tamsayılı doğrusal programlama (KTDP) modelini kullanmaktadır. Modelin iki yönlülüğünü sağlamak adına hedefe ulaşma yöntemi (GAM) kullanılmış ve daha sonra Gurobi Python API kullanılararak önerilen modelin üç farklı ölçekteki (küçük, orta ve büyük) problemler üzerinde uygulanabilirliği test edilmiştir. Önerilen metodolojinin farklı problemler için en uygun çözümleri maksimum 500 saniyede bulabildiği gösterilmiştir. Son olarak, amaç fonksiyonlarının davranışlarını değerlendirmek ve yönetimsel öngörüler ve karar destek çıkarımları sağlamak için anahtar parametreler üzerinde bir dizi duyarlılık analizi yapılmaktadır. onuçlar modelin talep parametresine yüksek oranda bağlı olduğunu göstermektedir. Öyle ki, talepteki bir artış toplam talepteki artışla ve aynı anda servis seviyesinde görülen aşağı yönlü trendle yakında ilişkilidir.

A NOVEL BI-OBJECTIVE MODEL FOR A MULTI-PERIOD MULTI-PRODUCT CLOSED-LOOP SUPPLY CHAIN

Closed-loop supply chain (CLSC) is a kind of supply chain which contains forward and backward flows of commodities within a logistics network. In the decision-making process of CLSC, locational, inventory control and transportation issues are addressed to deal with strategic, tactical and operational decisions. This paper utilizes a novel bi-objective mixed-integer linear programming (MILP) model to formulate a multi-period multi-product CLSC design problem considering aggregate cost minimization and service level maximization at the same time. To tackle the bi-objectiveness of the model, goal attainment method (GAM) is applied which is then executed by Gurobi Python API to test the applicability of the suggested model for three different scales (small, medium and large). It is demonstrated that the proposed methodology can find the optimal solutions for different problems in a maximum of 500 seconds. Finally, a set of sensitivity analyses is carried out on the main parameters in order to test the behaviors of the objective functions and suggest managerial insights as well as decision aids. The results reveal that the model is highly dependent on the demand parameter, that is, an increase in demand is closely related to an increase in the aggregate cost and a simultaneous downward trend in the service level.

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