The impact of inventory stored at different stages of the supply chain is significant. Determining the minimum and maximum inventory levels as well as the amount of orders to be placed constitute major challenges for decision-makers. An ordering policy (s, S) specifies these decision variables by placing an order when the stock level is less than s units, and specifying the order amount by the difference between the maximum stock level (S) and the current stock position. Since determining optimal values ​​of (s,S) is computationally expensive, simulation-based optimization is a potential tool to analyze alternatives and find these optimal values. Infinitesimal disturbance analysis (IPA) is used by (Gavirneni, 2001) in a capacitive supply chain. In addition to calculating the appropriate order level, they also measured the benefit of sharing the retailer's order policy inventory parameters and demand data with the supplier, which reduced the supplier's cost by 1 at 35%. Simulated annealing and ranking and selection procedure can be combined to find an optimal value...