Determining an optimal order-up to level on (T, S) policy by search methods with multi-item consumer product inventory

This research focuses on optimizing retail inventory for multi-consumer products using the periodic review/order-up-to policy, or (T, S) policy. It incorporates stochastic lead times, with demand estimated based on historical data. Since the inventory handles multiple items, storage space is limited, and shared space allocation is not used. The study aims to determine the optimal order-up-to level (S) for each product to minimize total annual cost (TAC).To find the optimal solution, the grid search method and the golden-section search method are automated through spreadsheet simulations using Macros in Microsoft Excel. Results indicate the optimal order-up-to level (S) and the corresponding nominal total annual cost (TAC) from both methods. The comparison reveals that the grid search method slightly outperforms the golden-section search due to the characteristics of the search technique.