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Stochastic reverse logistics network design for waste of electrical and electronic equipment

  • Berk Ayvaz
  • , Bersam Bolat
  • , Nezir Aydin*
  • *Corresponding author for this work
  • Istanbul Ticaret University
  • Yildiz Technical University

Research output: Contribution to journalArticlepeer-review

173 Citations (Scopus)

Abstract

In recent years, Reverse Logistics has received increasing attentions in supply chain management area. The reasons such as political, economic, green image and social responsibility etc. force firms to develop strategies to their current systems. The aim of this study is to propose a generic Reverse Logistics Network Design model under return quantity, sorting ratio (quality), and transportation cost uncertainties. We present a generic multi-echelon, multi-product and capacity constrained two stage stochastic programing model to take into consideration uncertainties in Reverse Logistics Network Design for a third party waste of electrical and electronic equipment recycling companies to maximize profit. We validated developed model by applying to a real world case study for waste of electrical and electronic equipment recycling firm in Turkey. Sample average approximation method was used to solve the model. Results show that the developed two stage stochastic programming model provides acceptable solutions to make efficient decisions under quantity, quality and transportation cost uncertainties.

Original languageEnglish
Pages (from-to)391-404
Number of pages14
JournalResources, Conservation and Recycling
Volume104
DOIs
Publication statusPublished - 1 Nov 2015

Bibliographical note

Publisher Copyright:
© 2015 Published by Elsevier B.V.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 9 - Industry, Innovation, and Infrastructure
    SDG 9 Industry, Innovation, and Infrastructure
  2. SDG 12 - Responsible Consumption and Production
    SDG 12 Responsible Consumption and Production

Keywords

  • Reverse Logistics Network Design
  • Sample average approximation
  • Stochastic programming
  • Uncertainty
  • Waste of electrical and electronic equipment (WEEE)

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