Abstract

Today, recycling of used products and materials has become an increasingly important sector. Mankind, who uses the natural resources unconsciously, has found ways to improve recycling techniques when they realized that resources are becoming increasingly depleted. In the automotive sector, which is one of the largest sectors in the world, natural resources are being used to a great extent. According to the statistics, in 2009, approximately 9 million end-of-life vehicles (ELV) in Europe were withdrawn from traffic. Undoubtedly, this figure shows the necessity and importance of designing reverse logistics network optimized for ELVs. This research aims to determine the gaps in the literature by examining the studies made from the past to the present day in the field of reverse logistic network design for vehicles that have completed their life cycle. In this article, the studies in the fieldare analyzed based on objective functions, decision variables, constraint handling metod, optimization methods used. Considered studies in this work are clustered using a special artificial neural network tool, Self-Organizing Maps (SOM), and the frequencies of the characteristics are shown in the study. This study, which includes a review of the literature and a clustering of studies, aims to guidethe researchers working on the design of rreverse logistics networks for ELVs.

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