基于遗传算法的密集型自动化立体仓库货位分配优化研究

Research on Optimization of Location Distribution of Intensive Automated Warehouse Based on Genetic Algorithm

密集型自动化立体仓库是由在货架轨道上行走的穿梭板与堆垛机配合作业。而影响其系统效率的主要因素是堆垛机要搬运穿梭板。文章研究了仓库中货物订单的最优货位分配与出入库作业次序。在研究基础上建立数学模型,运用遗传算法以及MATLAB软件对模型求解并得出数据。用FLEXSIM仿真软件建立某企业仓库1:1实体模型,先得出优化前数据,然后对模型优化得出优化后数据。将优化前数据与求解数据和优化后数据进行对比,发现堆垛机搬运穿梭板的次数减少了30%,运行效率提高了10.4%,且求解数据和优化后数据结果误差较小。

The intensive automated three-dimensional warehouse is operated by a shuttle plate that runs on the shelf rail in cooperation with the stacker.The main factor affecting the efficiency of the system is that the stacker has to transport the shuttle.This paper studies the optimal location allocation and order of goods entering and leaving the goods in the warehouse.Based on the research,the mathematical model is established,and the genetic algorithm and MATLAB software are used to solve the model and obtain the data.FLEXSIM simulation software is used to build a 1:1 entity model of an enterprise warehouse.First,the data before optimization is obtained,and then the optimized data is obtained by optimizing the model.Comparing the pre-optimization data with the solution data and the optimized data,it is found that the number of times the stacker transports the shuttle plate is reduced by 30%,the operation efficiency is improved by 10.4%,and the error of the solution data and the optimized data result is small.