Abstract: To make better use of storage space and pursue efficient receiving and retrieving operations, an automated storage and retrieval system (AS/RS) model was established with the goal of minimizing handling time for an automatic high rack cigarette warehouse. In addition, a two-stage bacterial foraging algorithm was developed to integrate and optimize storage location allocation and job scheduling during the operation of the AS/RS model, and to generate a receiving/retrieving strategy for a one-day cycle. Taking the daily cigarette receiving and retrieving orders of the finished cigarette warehouse of Inner Mongolia Kunming Cigarette Limited Corporation as an example, the bacterial foraging algorithm, particle swarm optimization algorithm, simulated annealing algorithm, and genetic algorithm were used to solve the model, respectively, and then compared with the initial storage strategy, under which each row of shelves are limited to receive the cigarettes of the same brand, in terms of operation time in one single day and storage space utilization. The results showed that the four algorithms were all superior to the initial one. Among them, the bacterial foraging algorithm showed the best performance and good stability when no more than 20 storage locations were occupied before that test initiated. Moreover, the frequently received/retrieved goods were allocated to the storage locations near the shipment end, it resulted in a 12% reduction in the average travel time and a 23% increase in the average receiving/retrieving efficiency. This method supports the promotion of operational efficiency and the reduction of labor costs in finished cigarette warehouses.