Unit load storage systems are pervasive throughout global supply chains. Significant reductions in their automation costs could have significant economic impact. A new alternative to traditional crane-based automation uses flexible autonomous vehicles in storage and retrieval operations. This technology has not significantly penetrated commercial markets for warehouse automation due to a lack of design tools for evaluating its performance. This precludes direct comparisons of autonomous vehicle technology with crane-based technology in the pre-engineering or “design conceptualization” stage of system development where key technology selection decisions are made. To address this problem, this chapter proposes computationally efficient cycle time models for Autonomous Vehicle Storage and Retrieval System that use scalable computational procedures for large-scale design conceptualization. Simulation based validation studies suggest that the models produce high accuracy. The procedure is demonstrated for over 4,000 scenarios corresponding to enumeration of the design spaces for a range of sample problems.
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