This study is motivated by the optimal shipment problem of B-yol, an international 3PL company that specializes in cross-border ecommerce (CBeC) logistics outsourcing services. Traditional third-party logistics (3PL) cannot keep up with rapid development and requirements of CBeC. B-yol collects outbound shipments from shippers and consolidates shipments in its cargo terminals. The consolidated shipments are subsequently shipped to international warehouses of e-retailers, for subsequent delivery throughout Europe. In the volatile ecommerce markets, the 3PL has to adjust its traditional freight consolidation strategies to simultaneously meet service commitments and minimize transportation cost. Stochastic arrival times of shipment orders makes the situation even more challenging. Therefore, in this study we develop a model to optimize total cost for the company, which consolidates loads from various cross-border ecommerce shippers at its facility. The model’s output is the optimal timing of the shipment, namely how long should shipment orders be held and how much should be consolidated before a shipment is sent. Shipment orders stochastically arrive and wait to be served, incurring a discount cost for waiting. We model this problem as a discrete-time Markov Decision Process, defined over a finite horizon. Using the monotonic properties of the optimal cost function, we developed a simulation algorithm to determine optimal consolidation strategies for the batch service of CBeC customers. Finally, we conducted numerical experiments to observe the results of the proposed approach under various parameter value scenarios.
Cross-border ecommerce (CBeC), consolidation, optimization, dynamic programming, simulation.