Abstract
A network queuing approach is used to estimate performance measures for Autonomous Vehicle Storage and Retrieval (AVS/R) Systems using opportunistic interleaving. The model exploits the distribution of cycle types and random storage assumptions to estimate the proportion of single and dual command cycles in a system. Comparable in accuracy and computational efficiency to procedures based on standard queuing models, the proposed technique provides the additional advantage of flexibility for modeling the interfaces between a storage system and the overall material flow system in a facility. The procedure is demonstrated for a range of problem scenarios.
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