| With the development of the logistics and warehousing industry,the traditional way of storage can not meet the demands of production and circulation of materials.Beside,most of the traditional management of warehouse operations rely on experience to arrange the location,making the warehouse run for a period of time will find unreasonable distribution of goods,resulting in Warehouse operation efficiency is reduced,operating costs increase.To this end,Generating applications forcargooptimization.A good strategy of cargo location optimization can greatly improve the efficiency of warehousing and storage and reduce the cost of warehousing system.Therefore,the research on this issue has high practical significance and theoretical value.This paper proposes the goods allocation model based on cluster analysis,that is,to calculate the correlation between goods by combining the receipt frequency of goods in historical order,cluster the goods according to the correlation size,and then distribute the goods location reasonably according to the average output frequency of goods in each category,so as to improve the efficiency of picking.The location-allocation model is analyzed and verified by matrix&laboratory(MATLAB),and the location-allocation scheme of 8 kinds of goods is simulated,and the reasonable location-allocation scheme is obtained.However,when the amount of data is increased,the operation efficiency of the algorithm will be too low.Therefore,the genetic algorithm is used to optimize the location-allocation model,and the optimized algorithm is simulated in MATLAB environment.the results of experiments show that the optimized model algorithm has a significant improvement in operational efficiency.Then,the location-allocation model is further studied,and the location-allocation idea is compared with the location-allocation idea based on association rules,using MATLAB simulation simulation,the results clearly show the superiority of this location-allocation idea. |
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