Research On The Front Warehouse Location Of A Fresh E-commerce Company

The arrival of COVID-19,while disrupting the pace of people’s lives,also brings huge development opportunities to fresh food e-commerce.As people’s demand for fresh food continues to increase,higher requirements are placed on the timeliness of fresh food e-commerce services and product quality.However,current traditional fresh food e-commerce and supermarkets cannot meet all the needs of consumers.In this context,fresh food e-commerce companies with the pre-warehouse model have emerged.Company A is a national fresh food e-commerce company that adopts the prewarehouse model.The cost has risen sharply due to the lack of scientific location planning.How to avoid re-opening stores under the premise of covering all needs,thereby reducing costs,is a problem that A company currently needs to solve.In response to this problem,this article has done the following research:First,introduce the background of the research in this article.By comparing the models of fresh food e-commerce,it is concluded that A company belongs to the "front warehouse+home" model.At the same time,it analyzed the relevant theories of the front warehouse,including its functions,characteristics and user characteristics,and sorted out the factors considered when selecting the location of the fresh food ecommerce related facilities to lay the foundation for the construction of the model.Then,according to the two problems of high cost and low coverage in the location of the front warehouse of A company,combined with the company’s location goals and principles,the construction includes the fixed cost of opening the front warehouse,transportation cost,rider delivery cost and users Self-imposed penalty cost is a cost minimization model,and the problem that all requirements are covered is considered in the constraints.Then,the hierarchical clustering method is used to cluster the demand points in the target area,and the demand points and the location options of the front warehouse are obtained.On this basis,Baidu API is called to calculate the riding distance between the demand point and the candidate point to restore the real situation of the business to the greatest extent.Use the multiple linear regression method to obtain the forecast model of the demand at the demand point,and distinguish the selfpickup order quantity and the distribution order quantity,and lay the foundation for the model solution.Finally,the method of using LINGO software,a tool for solving the model,is briefly introduced.In this paper,a company A will conduct business in Xicheng District,Beijing as an example,collect relevant data,and solve the constructed model.According to the results,A company can choose to open a different number of front-end warehouses according to its own operating strategy,so that the cost is the lowest under the premise that the demand points in the whole region are covered.This method provides a reference for A company in the location planning of the front warehouse,and also provides a reference for the location selection decisions of other fresh food e-commerce companies.