Research On Optimization Of Storage Capacity Of Fast-moving Consumer Goods Based On Order Prediction

With the improvement of China's economic strength and the rapid development of mobile Internet,China's e-commerce has developed rapidly.As a virtual transaction method,e-commerce requires the cooperation of many social service links to improve convenience for consumers.It not only represents a new consumer experience,but also represents a new format for the development of retail and its supporting services..Regarding logistics,in order to obtain an effective and convenient shopping experience,this needs to improve the efficiency of logistics distribution.As a result,the new concept of "front warehouse" was proposed.For the e-commerce front warehouse,it is necessary to accurately predict the volume of goods.Therefore,accurate prediction of the e-commerce order volume is of great significance for optimizing the e-commerce front warehouse storage volume and improving service quality.This article takes the order volume of FMCG front warehouse as the research object to optimize the storage volume of front warehouse.First of all,this article summarizes the current research status of order forecasting,the research status of front storage,and the research status and future development trends of warehouse forecasting.It introduces the concept of e-commerce front storage and its differences from ordinary storage.The significance of researching the optimization of the front warehouse storage volume of e-commerce is summarized.Then,a time series prediction model of multidimensional Taylor's network is established,and the e-commerce order quantity of different varieties of milk from the three major milk brands(Yili,Mengniu,and New Hope)in Baoding is forecasted.Then,by reading domestic and foreign literature on enterprise storage,the four major influencing factors of the e-commerce front warehouse FMCG storage volume are summarized-order forecast volume,safety stock volume,transportation cost,and storage cost.And based on the forecast amount of the order,an e-commerce front warehouse FMCG storage volume optimization model is constructed.Finally,an example analysis is made to apply the immune genetic algorithm to optimize the milk storage capacity of the front warehouse in Baoding City.The purpose of this article is to establish a reasonable forecast model for e-commerce FMCG orders and obtain a more accurate forecast.The milk storage capacity of the warehouse is optimized.Through the research of this subject,it has a certain reference to the online sales proportion that guides the service optimization,cost saving,and increase sales of FMCG mobile e-commerce enterprises.