New Warehouse Designs: Angled Aisles and Their Effects on Travel Distance

In supply chain and logistics systems, warehouses and third-party logistics centers have become the backbone of distribution networks that store and deliver goods. However, these facilities are still built to look much as they have been for the past fifty years (Gue and Meller, 2009). This dissertation builds on some recent research that challenges traditional ways of organizing picking aisles and cross aisles in unitload warehouses. The designs in this dissertation, and the models that produced them, offer to the research and practicing communities a new and fundamentally different way to extract cost and improve the performance of industrial warehouses. For warehouses with one, two and three cross aisles, we develop closed form, single-command travel distance functions in a continuous warehouse space. We use these functions to minimize expected travel distance in a unit-load warehouse with a centrally located pickup and deposit (P&D) point under randomized storage. We propose three optimal unit-load warehouses with respect to the inserted cross aisles, the Chevron, the Leaf and the Butter y. In order to provide a more accurate model and to analyze the wasted space for angled aisle designs, we build a discrete model of aisles and pallet locations that better represents warehouse designs. We develop a general warehouse design tool that models aisles, pallet locations and dock doors as discrete objects. The tool implements a network representation of the warehouse, a shortest path algorithm to determine travel distances, and a particle swarm meta-heuristic to search for the best arrangement of aisles. To illustrate the use of model, we define five design problems that are differentiated by the locations of multiple P&D points. We propose improved non-traditional aisle designs for each design problem with one and two inserted cross aisles.;Last, we introduce the idea of robustness in non-traditional aisle designs with respect to a varying number of P&D points. For two commonly found flow patterns in industry, we use our models to determine optimal designs for an increasingly large block of P&D points to find the point at which the structure "breaks." The results suggest that the Chevron design, in particular, is robust over a wide range of P&D points.