Risk explicit interval linear programming model for long-term planning of vehicle recycling in the EU legislative context under uncertainty

摘要: Abstract With the number of vehicles expected to increase 1.85 billion by 2030 and scrap generated from end-of-life (ELVs) be 3.71 tonnes, there is a strong motivation properly process flow these materials. The EU Directive on (EU ELV Directive) aims recovery recycling rates ELVs in order reduce waste improve environmental performances. Long-term optimization planning vehicle increasingly important. However, lack research uncertainties system, none previous studies analyzed linkage trade-offs between decision risk system performances, no was reported interval-based programming for problem. In meet imposed eco-efficiency quotas, maximize profit minimize risk, at same time fill identified gaps, explicit interval linear model optimal long-term factories developed. It can create plans procuring hulks, sorting material fractions, allocation sorted flows metals desired value aspiration level. A numerical study demonstrated potentials applicability proposed model. Vehicle aim reaching highest possible level quantity quality metal flows. future quotas will not endanger their business. success final phase implementation jeopardized, because even were reached all created test problems. Quantity land-filled wastes radically reduced after January 1, 2015. results would valuable supporting creating production strategies reducing uncertain situations.