自动化立体仓库是一个错综复杂的存储系统，货位优化问题直接影响自动化立体仓库的工作效率。针对自动化立体仓库的货位选择问题，本文提出以出入库效率和货架稳定性为优化因素的货位优化模型，并采取病毒协同遗传算法对优化模型进行仿真。最后对仿真结果及货位优化前，病毒协同遗传算法优化后，传统遗传算法优化后三者的对比结果进行分析，结果说明病毒协同遗传算法（VEGA）能有效实现自动化立体仓库货位优化，是提高货物出入库效率和货架的稳定性的一种有效方法。
Automated warehouse is an intricate system of storage, and slotting optimization problems directly affect the efficiency of the Automated Warehouse. To solve the dilemma of location selection of automatic stereo warehouse, a Slotting Optimization model which take the out of storage efficiency and shelf stability of storage as its optimization factors is proposed, the Multi-objective mathematical model of Slotting Optimization is established. According to the actual conditions of Automated Warehouse, with the help of Strategy Set Transformation, Delphi method and the Analytic Hierarchy Process(AHP) are used to determine the weight. And virus combined with genetic algorithm is taken to simulate the optimization model. In the MATLAB software environment, the Multi-objective genetic algorithm for virus is utilized to calculate the model solution. Finally, the results comparison among the simulation of the data before Slotting Optimization, the data after virus combined with genetic algorithm and the data after traditional genetic algorithm indicates that Virus Cooperative Genetic Algorithm(VEGA) can effectively optimize the automation stereoscopic warehouse slotting. It is also a kind of effective way to improve the efficiency of goods out of storage and stability of shelf.
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