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Received: 20 November 2018 Accepted: 12 January 2019 With the continuous development of the market economy, the tobacco industry is rapidly expanding in China. There are now numerous cigarette retailers across the country, which distribute multiple types of cigarettes to consumers in small batches and multiple times. Against this backdrop, the traditional warehouse storage and retrieval (S/R) approach, an integration of the radiofrequency identification (RFID) and manual sorting, no longer satisfies the market demand. Most cigarette distribution centres now use automated stereo warehouses, which face the com-plex and realistic problem of goods S/R with multiple stackers, multiple carriers and irregular goods locations. After analysing the features of the automated storage and retrieval system (AS/RS), this paper introduces the bacterial foraging optimization (BFO) algorithm to optimize the AS/RS in light of the actual work conditions. Firstly, a model framework was set up based on the production reality and algorithm constraints. Next, the model was solved by the bionic algorithm BFO. Finally, a numerical example was selected to verify the effectiveness of the algorithm. The results show that the BFO can effectively shorten the operation time and improve the S/R efficiency. The research findings provide a scientific and rational plan for automated ware-housing in complex environments.

Development of Optimization Model and Algorithm for Storage and Retrieval in Automated Stereo Warehouses