Abstract
An automated vehicle storage and retrieval system (AVS/RS) is a widespread automated warehouse solution that hosts hundreds of stock-keeping units (SKU) and counts thousands of incoming and outgoing unit loads corresponding to a sequence of time-dependent storage and retrieval transactions. AVS/RS ensures high storage density, reduced cycle time, and high productivity. This study introduces and applies an original data-driven comparative and competitive multi-scenario methodology to measure and control the performance of a multi-deep tier-captive AVS/RS. This original methodology measures and controls the impact of lane depth (1), assignment strategy (2), opening strategy (3), and dispatching strategy (4) on the storage capacity, system throughput, and space efficiency in the design and configuration of an AVS/RS. The proposed methodology was applied to a real case study, demonstrating that the combination of the four leverages significantly affects system performance.
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