چكيده لاتين
Optimal warehouse management, as a cornerstone of the supply chain, plays a decisive role in enhancing operational efficiency, reducing costs, and improving customer satisfaction. In complex industries such as the steel industry, which face high production volumes, a wide variety of items, and spatial constraints, designing an optimal layout and storage location assignment becomes a multifaceted challenge. This research focuses on the consumable parts warehouse of the Mobarakeh Steel Complex in Isfahan. The warehouse, with an area of 2508 square meters and 894 stock-keeping items (including bolts, nuts, washers, and tools), faced limitations in its previous design, such as narrow aisles and lack of forklift access to some racks. This study presents a two-stage mathematical model to optimize the layout and item assignment.
The primary objective of this research is to reduce the total distance traveled in the order picking process, which leads to improved workflow and reduced handling costs. Historical data, including monthly consumption, number of orders, physical dimensions, and calculated volume for the 894 items, were collected from the Mobarakeh Steel information system, existing documents, and interviews with warehouse managers. The items were first divided into two main groups (bolts-nuts-washers and tools) and then, using K-Means and Gaussian Mixture Model (GMM) clustering algorithms based on criteria such as monthly consumption, number of orders, dimensions, and volume, were categorized into twelve distinct clusters. The volume of each item was calculated using its dimensions and assigned to one of three Stock-Keeping Unit (SKU) types: pallet, large bin, or medium bin.
The proposed two-stage model consists of: first, assigning item clusters to aisles and bays to minimize inter-aisle travel distances; second, assigning items within each cluster to specific bays and cells while respecting the assignment sequence, SKU type, and spatial constraints. This model was implemented using GAMS software. By considering the objective of distance minimization, it provides an optimal assignment that, while adhering to constraints such as cell capacity, minimum allocation of one cell per item, and maintaining proximity of related items, guarantees faster access to high-consumption items.
This approach identifies consumption and demand patterns and, through layout optimization, significantly reduces the distance traveled for order picking. The results of this research not only improve warehouse space utilization but also reduce operational costs and picking time by minimizing unnecessary movements, enhance operational safety, and improve customer satisfaction.
It is noteworthy that the warehouse currently utilizes 100% of its bays. However, the optimal solution from this research has resulted in the freeing up of 19% of the warehouseʹs bays. This model, generalizable to other industrial warehouses with similar challenges, provides a scientific and practical solution for optimal warehouse management and can serve as a foundation for future research in warehouse space management.
