A computational software system to design order picking warehouses

• Published in: Computers & operations research 2021-08, Vol.132, p.105311, Article 105311
• Main Authors: Ozden, S.G., Smith, A.E., Gue, K.R.
• Format: Article
• Language: English
• Subjects: Algorithms; Aspect ratio; Computational tool; Design optimization; Design parameters; Floorplans; Heuristic methods; Layouts; Open source; Operations research; Optimization; Order picking; Software; Source code; Warehouse design; Warehouses; Websites
• ISSN: 0305-0548; 1873-765X; 0305-0548
• DOI: 10.1016/j.cor.2021.105311

•An open source solver for the Warehouse Layout Optimization Problem is introduced.•A wide variety of traditional and innovative designs are evaluated.•An exact formulation that can handle many constraints is presented.•A heuristic optimization and a new encoding for the problem are described.•Computational results on example problems are provided. Even though order picking is the most costly operation in a warehouse, current design practices have used the same principles (straight rows with parallel pick aisles and perpendicular cross aisles) to reduce travel distances between pick locations for more than sixty years. We present an open-source computational software system for facilitating the design of warehouse layouts to near-optimality considering average walking distance of the picker as the objective function. This software is particularly novel because a wide variety of traditional and innovative designs are automatically generated and evaluated. For the warehouse design parameters we consider the rectangular aspect ratio of the floor plan, the number and location of cross aisles, the number and location of pick aisles, and the location of a single input/output location. The main components of the design system are importing pick list profile data, creating the warehouse layout design as a network, product allocation (slotting) of SKUs through the warehouse, routing of pickers on a sample of orders using an exact routing algorithm, and design optimization using a meta-heuristic. We provide both mathematical and computational descriptions of the algorithms used by the software system, describe the types of problems that can be solved, and summarize our computational experience. This software is open source available on a GitHub website under an MIT license.