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A Novel Stochastic Optimization Model for Reverse Logistics Network Design of End-of-Life Vehicles: A Case Study of Istanbul

dc.contributor.authorKaragoz, Selman
dc.contributor.authorAydin, Nezir
dc.contributor.authorSimic, Vladimir
dc.date.accessioned2026-06-27T14:46:47Z
dc.date.issued2022
dc.description.abstractWaste management is gaining crucial importance as recycling aims at transforming produced waste into value for the economy. As the automotive industry is growing fast worldwide, recycling end-of-life vehicles (ELVs) attracts great research attention. Due to the promulgated regulations, multiple players like the last owners, manufacturers, treatment centres, and municipalities require a more cooperative engagement. The participation of multiple actors in the recycling process of ELVs brings various uncertainties. Additionally, parameters of the recycling process, like the number of vehicles withdrawn per year, cost items, and material composition tend to change due to technological, social, and economic developments. The automotive industry has crucial importance in the Turkish economy, which is highly affected by socio-political and economic issues. Furthermore, the Istanbul metropolitan area has the highest rate of vehicle ownership in Turkey. For that purpose, this paper proposes a scenario-based real-life stochastic optimization model to improve ELV supply chain network management in Istanbul. Sensitivity analyses to changes in scenario occurrence probabilities and changes in the amount of collected ELVs are performed to question the consistency of the study. The results of the mathematical model highlight that the operational cost items have the greatest ratio comparing the other cost items in the model. Furthermore, the results of the sensitivity analysis underline that the operational costs and selling prices of the materials from the ELVs have a significant impact on the profitability of ELVs' recycling process. In addition, uncertainty in the number of ELVs has a significant effect on both operational and strategical decision-making processes. This research can be extended in the direction of examining the effectiveness of ELV management in Turkey since Istanbul could represent the whole of Turkey with its economic and cultural characteristics. Further works can also try to implement the novel concept of a socially resilient supply chain in the ELVs' management.en
dc.description.urihttps://doi.org/10.1007/s10666-022-09834-5
dc.identifier.doi10.1007/s10666-022-09834-5
dc.identifier.eissn1573-2967
dc.identifier.endpage619
dc.identifier.issn1420-2026
dc.identifier.issue4
dc.identifier.startpage599
dc.identifier.urihttps://hdl.handle.net/20.500.14981/64663
dc.identifier.volume27
dc.identifier.wos000805534600001
dc.language.isoeng
dc.publisherSPRINGER
dc.relation.ispartofENVIRONMENTAL MODELING & ASSESSMENT
dc.rightsopenAccess
dc.subjectEnd-of-life vehicle
dc.subjectDecision-making
dc.subjectStochastic programming
dc.subjectScenario-based optimization
dc.subjectUncertainty
dc.subjectLOCATION-ALLOCATION PROBLEM
dc.subjectLINEAR-PROGRAMMING MODEL
dc.subjectLOOP SUPPLY CHAIN
dc.subjectEnvironmental Sciences & Ecology
dc.titleA Novel Stochastic Optimization Model for Reverse Logistics Network Design of End-of-Life Vehicles: A Case Study of Istanbul
dc.typeArticle
dspace.entity.typePublication
local.import.sourceWOS

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