Localized package shipment with partial outsourcing: An exact optimization approach for Chinese courier companies

This work is concerned with the daily package shipment problem that aims to find low-cost paths for a large volume of packages and transportation vehicles over a network of transshipment centers (TCs). For Chinese courier companies, this typically involves tens of thousands of origin–destination (OD) pairs and has to be solved in a limited time window every early morning. Inspired by their industry practices, where most vehicles (99.8% for our industry partner STO) only unload packages after departing from the origin and the shipment volumes can be split, we propose a novel Localized Package Shipment with Partial Outsourcing (LPSPO) model for each TC to individually decide their daily shipment profiles, which aligns with their current operations. Though the number of OD pairs in our localized model is considerably reduced, it is strongly NP-hard and we exploit the model structure to design a column generation-based algorithm, which iteratively identifies profitable paths for the restricted master problem. Then, we develop problem-specific cutting planes and variable bound tightening techniques to accelerate our algorithm. An extensive numerical study validates that our algorithm significantly outperforms CPLEX in solving the LPSPO model. Finally, experiments on realistic instances from a leading Chinese courier company illustrate that the LPSPO model may reduce its transportation costs by up to 10 million USD annually.