Abstract: To improve the military AS/RS delivery speed and running stability, this paper proposes a design that the stacker carries on a class-based L-shaped zone oriented optimization at leisure. According to user’s choice, it generates class-based L-shaped zone information. Each goods’ coupled destination location is sought for when shortest stackers total run time and lowest center of gravity are treated as the target by building corresponding mathematical model. Genetic Algorithm based on hybrid preference is adopted for the multi-objective optimization problem. The results have shown that this method can greatly improve output efficiency of certain goods in a specific environment and reduce the center of gravity. Meanwhile, the study also has a certain value on the general sense of storage location reassignment.

Key words: class-based L-shaped zone, Genetic Algorithm（GA）, multi-objective optimization, storage location reassignment

摘要： 为提高军队自动化立体仓库出货速度和运行稳定性，提出了在堆垛机闲时对货位进行以分类存储L形分区为导向的再分配优化设计。根据用户需求，生成分类存储的L形分类存储目标货位分区信息，以堆垛机总运行时间最短和货架重心最低为目标，研究货品新的目标耦合货位并建立了相应数学模型，利用基于混合偏好的遗传算法对该多目标优化问题进行了求解。结果显示，该方法能较大提高自动化立体仓库某类货品在特定环境下的出库效率并降低货架重心。同时，该研究对一般意义的货位再分配也具有一定价值。

关键词: 分类存储L形分区, 遗传算法, 多目标优化, 货位再分配