OPTIMIZATION OF STOCK KEEPING AND SPACE UTILIZATION POLICY FOR A WAREHOUSE

This study considers the one-dimensional variable-sized bin packing problem (VSBPP) which is an NP-Hard problem. In this study, the objective is to find an efficient solution that minimizes both the total capacity of the bins used and the number of bins required, thereby optimizing the company's storage policy and saving space within the warehouse. Three algorithms are employed to solve a real warehouse’s VSBPP: i) First Fit Decreasing (FFD), ii) Best Fit Decreasing (BFD), and iii) Next Fit Decreasing (NFD). The warehouse dataset includes items of various sizes, and the goal is to allocate these items into bins most efficiently. Experimental results demonstrate that the FFD and BFD algorithms outperform the NFD algorithm. Furthermore, all three algorithms significantly reduce storage space usage and improve space utilization compared to the warehouse's current practices.