A multi-stage interval-stochastic programming model for planning end-of-life vehicles allocation. (1st March 2016)

• Record Type: Journal Article
• Authors: Simic, Vladimir
• Is Part Of: Journal of cleaner production. Volume 115(2016:Mar.)
• Page Start: 366
• Page End: 381
• Publication Date: 2016-03-01
• Subjects: End-of-life vehicle -- Management -- Multi-stage -- Stochastic -- Interval programming -- Uncertainty; Factory and trade waste -- Management -- Periodicals; Manufactures -- Environmental aspects -- Periodicals; Déchets industriels -- Gestion -- Périodiques; Usines -- Aspect de l'environnement -- Périodiques; 628.5
• DOI: 10.1016/j.jclepro.2015.11.102
• Languages: English
• ISSNs: 0959-6526

Abstract

Abstract: The amount of material entering end-of-life vehicles (ELVs) management systems all over the EU has been reduced due to increased export of used vehicles to non-EU countries. According to the latest data, only 6.23 million ELVs were processed in 2012 (e.g., 8.37 million ELVs were processed in 2009). Considering that currently 342 active vehicle recycling factories exist in the EU, as well as that in the last ten years the total processing capacity has been increased several times, it is clear that there is a serious conflict. This paper proposes a multi-stage interval-stochastic programming model for planning end-of-life vehicles allocation. The developed model is able to reflect dynamics in terms of decisions for ELV allocation from a multi-region waste management system to multiple vehicle recycling factories within a multi-period context. It is capable of incorporating multiple policies within the optimization framework. Uncertainties expressed as probability distributions and discrete intervals are effectively handled, based on a multi-layered scenario tree with a finite set of scenarios. A semi-hypothetical case study is conducted in order to demonstrate the potentials and applicability of the proposed model. Influences of parameter uncertainty on model solutions are thoroughly examined. Comprehensive analyses of various policy situations, associated with different levels of economic penalties and system failure risks, are presented. The proposed model is effective for solving difficult ELV allocation problems with uncertainties included as part of the formulation. It can help quantify the relationships between ELV management system profit and disruption risk of the vehicle recycling factories, and thus provide optimal ELV allocation schemes. Highlights: MSISP model for planning end-of-life vehicles allocation is developed. It has advantages in dynamic analysis, uncertainty reflection and policy analysis. A case study demonstrated the potentials and applicability of the proposed model. The model can serve as the support for vehicle recycling managers. The developed model can be extended to other environmental engineering problems.