In the last decade, global competition has forced manufacturers to optimize logistics. The implementation of collapsible containers provides a new perspective for logistics cost savings, since using collapsible containers reduces the frequency of shipping freight. However, optimization of logistic cost is complicated due to the interactions in a system, such as market demand, inventory, production throughput, and uncertainty. Therefore, a systematic model and accurate estimation of the total cost and system performance are of great importance for decision making. In this paper, a mathematical model is developed to describe deterministic and stochastic scenarios for a closed-loop container dynamic flow system. The uncertainties in a factory and a supplier are considered in the model. The performance evaluation of the collapsible container system and total cost estimation are provided through model analysis. Furthermore, fuzzy control method is proposed to monitor the processing rate of the supplier and the factory and to adjust the rate of the supplier operation then further reduce the logistic cost. A case study with a matlab simulation is presented to illustrate the accuracy of the mathematical model and the effectiveness of the fuzzy controller.

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