基于遗传算法的自动化立体仓库货位优化研究

Research on Slotting Optimization of Automatic Storage and Retrieval System Based on Genetic Algorithm

文章针对单元货格式自动化立体仓库最为核心的货位优化问题,提出以出入库效率、货架稳定性以及工作量均衡为目标的优化模型,对建立的多目标数学模型,利用权重法转化为单目标优化问题,再用遗传算法对该问题进行求解,并以某食品生产企业M公司所建立体仓库的真实数据为例,最后在Matlab中使用遗传算法进行仿真验证。结果表明该模型对于自动化立体仓库的优化效果明显,并且在解决巷道工作量均衡问题方面对于不同类型的立体仓库具有一定的普适性。

Aiming at the core slotting optimization problem of the automated three-dimensional warehouse of unit cargo format,this research proposes an optimization model aiming at in-out and outbound efficiency,shelf stability and workload balance.The established multi-objective mathematical model is transformed into a single goal optimization problem,and then use genetic algorithm to solve the problem,and take the real data of the warehouse established by a food production enterprise M company as an example,and finally use the genetic algorithm to simulate and verify in Matlab.The results show that the model has obvious optimization effect on automated three-dimensional warehouses,and has certain universality for different types of three-dimensional warehouses in solving the problem of roadway workload balance.