In last decade, global competition has forced manufacturers to optimize logistics. An innovative containerization method (CM) provides a new perspective for optimizing logistics cost saving, where collapsible containers are used to reduce the frequency of return freight. However, the optimization of logistic cost is complicated due to the trade-offs with many factors, such as custom demand, inventory, production throughput and uncertainty. Therefore, the appropriate model and accurate estimation of the total cost and system performance are of great importance for decision-making. Based on this estimation, an effective control method can be selected for improving the optimization.
This research develops a mathematical model of the container dynamic flow system by using the collapsible containers. A continuous time, discrete space Markov process is used for stochastic scenario. The model determines the total cost savings, based on the collapsible rate, the number of collapsible containers, the performance of the factory and the supplier and the transportation environment. The presented mathematical formulation enables the evaluation of the system performance. A case study of collapsible container supply chain system demonstrates the advantages of this methodology. In addition, a simulation model of this stochastic system is presented to verify the mathematical model. Simulation tests are conducted to demonstrate the potential logistics cost savings in the closed-loop supply chain system.