Research On Location Of Pre-warehouse

With the upgrade of consumption,consumers pay more and more attention to the quality of service and the convenience of shopping.The traditional logistics organization has been difficult to meet the needs of customers.All major e-commerce companies and entities have begun to change the end logistics organization model.The model came into being.At present,the research content of the development prospects of the pre-warehouse and the type of the pre-warehouse is becoming more and more perfect,but there are few studies on the location of the front warehouse,which is different from the location problem of the city distribution center.The site belongs to the location of the terminal logistics facility.Therefore,based on the research status and actual needs,this paper proposes a multi-objective model and solution method for the location of the pre-warehouse,mainly doing the following researches:(1)This paper analyzes the factors,steps and principles of the pre-warehouse mode and the location of the pre-warehouse.Through analysis,it is known that the radiation range of the pre-warehouse is limited,the customer demand is scattered,the demand is affected by the factors of population,economy,policy,etc.,and the customer is sensitive to the service time.The factors affecting the location of the pre-warehouse are selected and selected.Site steps.(2)Use the K-means algorithm to cluster customer demand points.In this paper,based on the K-means algorithm,based on the POI data of Gaode map,the scattered and numerous customer demand points are clustered,and the error square sum and the contour coefficient are selected to evaluate the clustering effect,and the clustering effect is selected.k value.After clustering,the problem of location selection of the pre-position is transformed into the general location problem,the difficulty of site selection is greatly reduced,and the efficiency of site selection is improved.(3)This paper comprehensively considers the company and the customer,and establishes a multi-objective model with the smallest total logistics cost and the highest customer satisfaction.The front warehouse is close to the consumer's end warehouse.The product type is mainly fresh,and the end delivery is characterized by a small amount of multi-frequency.If the goods cannot be delivered to the customer in time,the customer's time satisfaction will decrease,resulting in a decrease in customer satisfaction.This further leads to a decline in customer purchases and an impact on the company's earnings.Therefore,customer satisfaction is expressed by the penalty cost based on time satisfaction.At the same time,considering the lowest total cost of the logistics network of the enterprise in the pre-position mode,a multi-target location model is established.(4)Take the company A as an example to carry out model and algorithm verification.Data collection and analysis of demand distribution and demand status of Company A in Xicheng District,Beijing.For the shortest distance between the two points in the pre-position mode,the Baidu map api is solved by Python,which is the shortest distance from the map.The road path distance can maximize the distance between the two points under the actual traffic conditions,and the data accuracy is ensured,which improves the accuracy of the location of the front bin.The multi-objective genetic algorithm NSGA-II is used to solve the model,and the pareto optimal solution set is obtained.The validity and practicability of the model and algorithm are proved.