Supporting 3PL Decisions in the Automotive Industry by Generating Diverse Solutions to a Large-Scale Location-Routing Problem

摘要

For the distribution of spare parts to car dealers, many automotive companies use a transport network of intermediate hubs or transport platforms, operated by a set of third-party logistics (3PL) partners. The optimization of this network, particularly the selection of 3PL providers and corresponding transport platforms, is a complex decision that needs to be supported by appropriate software tools. In this paper, we develop such a tool, implement it, and show its results on a real-life case study provided by Toyota. The tool is currently in active use at Toyota to study and improve the distribution of spare parts in Germany. Using a tabu search metaheuristic, the developed tool essentially solves a large location-routing problem, but has several innovative features to increase its usefulness. First, the tool generates a set of high-quality but structurally different solutions, rather than a single one. This increases Toyota's negotiating power, increases its ability to analyze its current transport network against possible alternatives, and allows it to quickly switch between different transport networks if unexpected events occur. Second, a commercial vehicle-routing solver is integrated into the tool, to allow for a far more realistic modeling of the vehicle-routing decision. [PUBLICATION ABSTRACT]