A stochastic optimization model for reverse logistics network design of end of life vehicles: case study of İstanbul

Abstract

Waste management is gaining crucial importance as recycling aims at transforming produced waste into value for economy in recent years.As automotive is one of the fastest growing industries worldwide, recycling of end‐of‐life vehicles (ELV) gains importance day by day. Due to legislations and new regulations, multiple players like users, producers, treatment facilities, municipalities, etc. require cooperative engagement and they are being conferred new responsibilities in recycling process. Participations of multiple actors in the recycling process of ELV bring various uncertainties to the case. Additionally, parameters of the recycling process, like number of vehicles withdrawn per year, cost items, percentages of material types in the vehicles are tended to change due to technological, social and economic developments. Automotive industry has a crucial importance in Turkish economy which is highly effected by socio‐political and economic developments. Furthermore, Istanbul is a metropolitan area which has maximum rate of vehicle ownership in Turkey. For that purpose, this paper aims to propose a scenario‐based real‐life stochastic optimization model for management of supply chain network of the ELVs’ recycling process in Istanbul. Consequently, sensitivity analysis and scenario analysis are applied to question the consistency of the study and to review the results with different scenarios.