Vehicle scheduling and routing at a cross docking center for food supply chains

- This research adopts cross-docking center for distribution of perishable food products.
- The model is formulated as a mixed integer program with the objective of minimizing the earliness, tardiness, inventory holding, and transportation cost.
- The proposed model with customer zones and hard time windows has relatively short computational time.

Cross-docking is increasingly used to reduce inventory holding and the time products spend in the supply chain. It is especially suitable for fresh produce distribution with a short shelf-life. This research studies cross docking operations to ensure food can be delivered just in time and with minimum cost of delivery, including inventory holding and transportation costs, and the penalty costs of early or tardy deliveries. The research focuses on the integration of vehicle scheduling and routing in one comprehensive model, which have traditionally been modeled separately. The integrated model also considers product consolidation at the warehouse and respects delivery time windows specified by the customer. The VRSP system is modeled as a mixed-integer linear program in CPLEX. Experiments reveal that it can be solved in a reasonable amount of time only for small sized problems. To reduce the size of the solution space, the concept of customer zones is introduced and hard instead of soft time windows are applied (VRSP-CZHTW). Extensive experiments are conducted with different size problems. The VRSP-CZHTW problem can still be modeled using CPLEX but can now be solved in a short time even for real-life size problems. The research is the first to include all the operations performed at a cross-dock warehouse in a single comprehensive model, and incorporates practical constraints for customer delivery zones and delivery time-windows. The novelty is in modeling food distribution efficiency, and in supporting food distributors in providing better delivery service for the time sensitive items at lowest logistics cost.