A dynamic ordering policy for a three echelon supply chain with backordering for perishable goods

Inventory management considering back-ordering policy is becoming a more effective strategy for balancing limited supply with unpredictable demand. Back-logging of inventory is widespread in numerous businesses, including manufacturing, airline, spare part service, and retail industries. This paper develops a control-theoretical method, Smith predictor, for continuous review inventory systems for perishable items with backordering and multi-supplier supply chain. The proposed model aims to respond quickly to market demand changes and generates different orders to smooth and reduce the bullwhip effect in a reasonable time. This modified control theory eases the flow of information in inventory systems. Finally, the block diagram is used to simulate a three-echelon supply chain for perishable products where backorder is allowed. The proposed model is examined and verified using Normal, Exponential, and Gamma distribution demands in MATLAB's Simulink. The results illustrate that the proposed model is consistent with the Exponential distribution.