Vehicle routing problem for reverse logistics of End-of-Life Vehicles (ELVs). (1st February 2021) - Chaabane, Amin
Highlights: Decision support system of Vehicle Routing Problem for Reverse logistics of ELVs. Efficiency in vehicle routing problem within reverse logistics context. This paper presents its scientific contributions based on a real word case. Sensitivity analyses confirmed the reliability of generated solutions. Analytical tool for application in waste collection vehicle routing planning. Abstract: 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. Furthermore, parameters that influence the solution of the routing problem for the collection of ELVs tend to change due to the dynamic customers' locations and variations in vehicle type and the condition of the vehicules at the end of their life. This research proposes a new reverse logistics routing problem for the collection of end-of-life vehicles. It combines the classical Vehicle Routing Problem (VRP) with the pick-up problem and additional constraints such as loading pick-up sequences, time-windows, multi-trips, heterogeneous internal fleet, and external carriers. We also developed an efficient heuristic to construct routes and assign dealers to truck routes for solving large and real-size instances in a reasonable time. In collaboration with a significant player in North America for ELVs recycling, we performed a sensitivity analysis to compare the industry's current practices and the proposed method. The validation process with different instances demonstrates results consistency and provides useful managerial insights. Finally, sensitivity analysis shows potential changes in the solution performance regarding the penalty cost of unused internal fleet, the extra broker cost, the size of ELVs collected, and the number of the internal carriers' truck fleet.