Incorporating vertical travel into non-traditional cross aisles for unit-load warehouse designs

Abstract

This article proposes modifications to the travel-time models for non-traditional warehouse aisle layouts, Flying-V and Fishbone, by incorporating a vertical travel dimension. The resulting non-linear optimization models incorporate Chebychev travel within the picking aisles. The obtained shape of the aisle and the percent improvement for a traditional warehouse are compared with the results found in previous research that ignores vertical travel. It is shown that the percent improvement diminishes as the height of the rack increases, with Fishbone maintaining a higher percent improvement over Flying-V. It is also shown that while the shape of Flying-V can be considerably altered by considering vertical travel, the Fishbone layout often maintains its recommended shape regardless of the height of the rack. The article concludes with recommendations for effective implementation of these two designs.

Storage allocation in a warehouse based on the forklifts fleet availability

“…Warehousing the products will not add any value to it (except specific products such as wine), and shipping/storing the products is a costly activity that the company operates to create the opportunity of making benefit by selling the product in the future. 1 Frazelle 2 believes that the warehousing systems determine the final efficiency or inefficiency of a whole supply chain. Warehousing is commonly used to achieve some of the most important goals of a company 3 :…”

Integration of single and dual command operations in non-traditional warehouse design

“…Furthermore, Öztürkoğlu et al [24] introduced three new NTW layouts characterised by an increasing number of cross-aisles, optimising the warehouse size, while Mesa [25] proposed a new diamond layout using random and class-based storage assignment under single command operations. Considering multiple P&D points, several contributions [26][27][28][29][30][31][32] upgraded previous design models, while Clark and Meller [33] investigated the impact of the vertical travel distances to reach the bays. Bortolini et al [19], Accorsi et al [34] and Bortolini et al [35] introduced the aforementioned diagonal cross-aisle layout.…”

Formulating and solving the integrated batching, routing, and picker scheduling problem in a real-life spare parts warehouse

“…This is only true in case of a linear distance approximation function (e.g., rectilinear distance metric), which is the case for low-level storage systems. In case of high-level storage systems, the Chebychev distance metric includes vertical travel as follows: the travel time between two vertices equals the maximum of the horizontal travel time and lifting time (Clark and Meller, 2013). Consequently, the number of arcs increases tremendously compared to the general Steiner TSP formulation as all vertices within a pick aisle need to be connected by arcs, making the MIP model too hard to solve even for very small instances.…”