Optimization of reverse logistics network of End of Life Vehicles under fuzzy supply: A case study for Istanbul Metropolitan Area


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Kusakci A. O. , Ayvaz B., Cin E., AYDIN N.

JOURNAL OF CLEANER PRODUCTION, cilt.215, ss.1036-1051, 2019 (SCI İndekslerine Giren Dergi) identifier identifier

  • Cilt numarası: 215
  • Basım Tarihi: 2019
  • Doi Numarası: 10.1016/j.jclepro.2019.01.090
  • Dergi Adı: JOURNAL OF CLEANER PRODUCTION
  • Sayfa Sayıları: ss.1036-1051

Özet

Recycling aims at preventing rapid depletion of natural resources while transforming produced waste into value for economy. However, this process becomes a major challenge in automotive industry, which requires cooperative engagement of multiple players within a complex supply chain. In line with the essence of the topic, government agencies around the world issue directives drawing regulatory frameworks for designing recycling operations comprising various activities such as collection of end-of life vehicles (ELVs), recovery of reusable components, shredding ELV's body, recycling valuable materials and disposal of the hazardous waste. In general, the amount of returned product in a reverse logistics network is highly uncertain, and the ELV market in Turkey is no exception to this. For that purpose, this study aims developing a fuzzy mixed integer location-allocation model for reverse logistic network of ELVs conforming to the existing directives in Turkey. Accordingly, this study uses a novel approach and assumes that ELV supply in the network is uncertain. The merit of the proposed mathematical model is proved on a real world scenario addressing the reverse logistics design problem for ELVs generated in metropolitan area of Istanbul. The network generated specifies that recycling process is not profitable under the existing circumstances with the given level of supplied ELV and the returned product records per capita in Istanbul are far beyond the EU averages. Consequently, sensitivity analyses question the reliability of the obtained results. (C) 2019 Elsevier Ltd. All rights reserved.