Designing Optimal Layouts for Block Stacking Warehouses

Abstract

Storing pallets of Stock Keeping Units (SKUs) on top of one another on a warehouse floor is known as block stacking. Although this storage system can be inexpensively implemented in any open area, it is challenging in terms of space planning. Designing an optimal layout for this storage system involves determining the optimal numbers of aisles and cross-aisles, bay depths, cross-aisle types, and their locations in the layout. The storage space is wasted in this system by a combination of honeycombing and accessibility aisles. Honeycombing refers to unoccupied pallet positions in a partially occupied lane that are only available to the SKU that has occupied the first pallet position of the lane. The accessibility waste refers to the space devoted to aisles and cross-aisles because they are not used for pallet storage. There is a trade-off between honeycombing and accessibility waste with respect to lane depths. Shallow lanes generate less honeycombing waste but impose more aisles to the layout, whereas the opposite is true for deep lanes. Cross-aisles improve transportation costs within the warehouse, but their devoted space contributes to the wasted space. Hence, both space utilization and transportation costs must be considered to study cross-aisles. This dissertation explores the above trade-offs and relations from three different perspectives: (1) it proposes a closed-form solution model to obtain optimal lane depths for block stacking in diverse manufacturing and non-manufacturing environments; (2) it studies the layout design problem from space utilization perspective, and proposes an optimal model to find space-efficient layouts; and, (3) it investigates the effects of cross-aisles on transportation costs and proposes a multi-objective model to design layouts that optimize both space utilization and transportation costs. The proposed models along with the highlighted future extensions provide proper tools to the companies to design efficient warehouses and implement a comprehensive foundation for further research.