Research On The Storage Of Artificial Picking Warehouse Based On Intelligent Optimization Algorithm

With the rapid development of the logistics industry,warehousing is required to process orders quickly to meet customer needs.The increase ofthe complexity of warehouse operation and the improvement of customer demand diversity,how to realize the fast pick has become the key to enterprise development.The optimization of the layout and the optimization of the storage path can improve the external processing efficiency and internal treatment efficiency,and improve the overall efficiency of warehousing operations,reduce operating costs,improve customer satisfaction.In FAW International Logistics Co.,Ltd,the worker select the picking route according to experience,it leads to the problem of slow picking rate and the dailiao.First of all,this paper summarizes and divides the warehouse operation,optimize the layout of warehouse operation units with the SLP method,thatoptimizes the warehouse logistics and improves the external processing speedof order.Secondly,this paper researchs the intelligent algorithm on pick routeproblem,especially on ant colony algorithm and genetic algorithm.For the current status that the ant colony algorithm is sensitive to parameter and the lack of guidance on parameter setting,this paper uses genetic algorithm to optimize the ant colony algorithm and that improves the performance of ant colony algorithm.Taking the typical path optimization model for example,proved the effectiveness of parameter optimization.Thirdly,this paper designs a new genetic algorithm based on the double area warehouse,which is used to segmentationthe order thatorders for large quantities of goods.a multi-objective dynamic ant colony genetic algorithm is designedto solve the optimization problem of pick route.The performance of the algorithm is compared with the typical path optimization problem,andthe superiority of dynamic ant colony genetic algorithm is proved.Two kinds of route optimization system are developed by using MATLAB R2009 a,and the validity of the developed system is proved by the simulation analysis of the actual order.