Assignment strategy and lane depth in homogeneous multi-deep shuttle-based S/R systems

An automated vehicle storage and retrieval system (AVS/RS) is a widely used warehouse solution that adopts automated technologies to store and retrieve palletised unit loads. Several factors affect the performance of such shuttle-based systems in terms of productivity and space efficiency. This study focuses on the best achievable performance of nominal storage capacity saturation via assignment strategy selection and lane depth determination. These are the crucial aspects to consider when designing and configuring a homogeneous AVS/RS, where homogeneity means that the generic storage lane hosts unit loads (UL) of the same item. This study aims to introduce and apply an original mixed-integer linear programming model to optimise the space efficiency and storage capacity of a multi-deep tier-captive AVS/RS. A time-splitting methodology is introduced to obtain solutions for real applications. A multi-scenario analysis conducted on a case study demonstrates the effectiveness of the proposed model and solution methods.