Abstract
This paper aimed to introduce multiple-rack strategies in miniload automated storage and retrieval systems (AS/RSs), which included first fit (FF) and best fit (BF) assignment methods based on a matrix real-coded genetic algorithm (MRCGA) in the storage and retrieval process. We validated the probability occurrence of item sizes as a contributory factor in multiple-rack strategies, and compared their capacities, utilization of units and space by equal probabilities or the 80/20 law. According to the analytical methods, BF showed a reduction of more than 11.2% than FF on travel distance, and Type B-FF, Type B-BF and Type C-BF were better able to meet high-density requirements. These strategies provide diversified storage and retrieval solutions for the manufacturing and express delivery industry.
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