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Performance evaluation of In-Deep Class Storage for Flow-Rack AS/RS

2012; Taylor & Francis; Volume: 50; Issue: 23 Linguagem: Inglês

10.1080/00207543.2011.624561

1366-588X

Olivier Cardin, Pierre Castagna, Zaki Sari, Nihad Meghelli,

Optimization and Packing Problems

Abstract This article presents a new storage-retrieval method called In-Deep Class Storage, designed for Flow-Rack AS/RS. Class-based storage is a well-known method that has an extensive literature; our method is based on the fact that it is more efficient to dedicate the front layers of each bin to the class of the most popular items rather than dedicating whole bins close to the drop-off station. Clearly, this idea is not trivial to implement due to the dynamic behaviour of such racks. Thus, two separate algorithms have been defined, one for storage and one for retrieval, enabling dynamic use of our approach, with the only hypothesis of a Pareto distribution of item demand. This article presents a simulation study designed to compare the performance of random storage and retrieval with the use of the algorithms. This study shows a significant improvement of the expected retrieval delay, the main performance indicator selected for the study. Keywords: flow-rack automated storage and retrieval systems (flow-rack AS/RS)storage and retrieval heuristicclass-based storagesimulation with discrete eventsperformance assessmentin-deep class storage Acknowledgement This work was partially funded by the EGIDE organisation via the TASSILI 11 MDU831 program (reference 24323VD).