Enhancing Lateness Management in Cross-docking
Today's marketplace is moving faster than ever, and companies are challenged to distribute their products more quickly, efficiently and cost-effectively. This has led to the rise of cross-docking in the global supply chain to help keep pace with customer demand. Cross-docking refers to the practice of unloading goods or materials from an incoming vehicle (e.g., train car, truck, vessel container) and then loading them directly onto outbound vehicles with no storage in between. A common form of cross-docking operations corresponds to single or multi-item pallets, which are unloaded, sorted based on their destination, and placed directly onto outbound trucks. This strategy allows transportation companies to move towards more proactive, agile and flexible supply chains, with shorter product cycles and easier product customization.
The objectives of the project are to improve the existing software tools that plans the scheduling of the incoming/outgoing vehicles of a crossdocking facility in order to reduce the lateness (tardiness/earliness) of the goods deliveries. In addition, we will explore the integration of machine learning tools in order to enhance those software tools.