Vehicle routing problem for reverse logistics of End-of-Life Vehicles (ELVs).

Reverse logistics management of End-of-Life Vehicles (ELVs) is increasingly focusing on practical solutions for getting additional value from products at the end of their life. As automotive is one of the fastest-growing sectors, the number of ELVs to be collected and recycled has been steadily increasing due to more stringent regulations. On the other hand, the operational cost (transportation) of collecting ELVs might exceed half of the purchased price.

A two-stage stochastic optimization model for reverse logistics network design under dynamic suppliers' locations.

This paper presents a two-stage stochastic programming model for reverse logistics network design (RLND) under uncertainty with dynamic supply sources' locations. The primary objective of the optimization model is to maximize the expected profit generated by selling recycled materials to the secondary markets and to make the landfilling option less attractive. In comparison with the state-of-the-art stochastic optimization models in this area, which mainly focus on the expected optimal value, this paper emphasizes the role of source separation of recyclable materials to increase the productivity level at the collection centers (CC).