In logistics, many transportation company consolidate several small shipping orders into a larger shipping order to reduce cost. This strategy is called shipment consolidation. In addition to cost reduction, shipment consolidation can reduce CO₂ emissions.
Previous studies on shipment consolidation assume that all customers are willing to wait during shipment consolidation cycle and all orders would be met. However, in real life, customer defection may happen when delivery time increases. Increased delivery time caused by shipment consolidation may lead to customer defection. Thus, customer defections should be considered as a factor to examine the optimal shipment consolidation decision.
I consider a single-item inventory system where shipments are consolidated to reduce the transportation cost and environmental cost(such as CO₂ emissions) using quantity-based and time-based consolidation policies. With consideration of customer defection, I develop mathematical models for quantity-based shipment consolidation and time-based shipment consolidation policies respectively which can minimize transportation cost and environmental cost such as CO₂ emission and obtain optimality properties for the models. Using the mathematical model, simple and efficient algorithms are developed to compute the optimal solution for ordering and shipment integrated decisions.
To compare the performances between the quantity-based policy and the time-based policy, extensive numerical experiments are conducted, and the decision variables and the total cost are compared. Numerical results show that the performance of time-based consolidation policy is better than that of quantity-based policy when the order cancellation rate increases. In addition, meaningful insights are extracted from the results of the numerical experiments, which can support decision making of logistics service provider.