自动化立体仓库拣选作业优化研究

Study on Optimization of Sorting Activities in Automatic Storage and Retrieval Systems

为提高自动化立体仓库运行效率,对固定货架系统中拣选作业优化问题进行研究分析。建立自动化立体仓库拣选作业的数学模型,将优化问题归结为经典TSP模型,采用一种改进遗传算法进行求解。该算法对初始种群进行优化处理,并针对遗传算法局部寻优能力不足的缺陷,引入一种"进化逆转算子"。实验结果表明改进遗传算法从拣选路径和优化速度两方面提高了拣选效率,且拣选货位点数越大,优化效果越明显。

In this paper, in order to improve the operational efficiency of the automatic storage and retrieval systems, we analyzed the optimization of the sorting activities relating to the fixed rack system, built the mathematic model of the sorting activities in the ASRS, proved that the model was a classic TSP model and adopted an improved genetic algorithm to solve it. At the end, through an experiment, we verified that the improved genetic algorithm could improve the sorting efficiency on the aspects of sorting path and speed.