Inventory optimization with (S, s) policy and backlog under stochastic discrete demand and lead time

This paper presents the simulation sheet and python code for optimizing the total cost with real data of demand and information factors of product. Python code has been used as a tool to automate the simulation sheet reduced unnecessary time if do it manually. The way that used to optimized are cyclic coordinate search in three ways, horizontal, vertical, and diagonal, because the result shows that the optimal cost will shows in the diagonal line. The findings of this study will help to determine inventory levels and annual costs in warehouse environments, allowing for more complicated and realistic investigations in warehouse systems.