Research On Location Optimization Of Retail Network Terminal Of S Pharmaceutical Chain Enterprises

Pharmaceutical retail network terminal is one of the important institutions for people to obtain pharmaceutical services,and plays an important role in ensuring people's physical and mental health.In recent years,the continuous implementation of the new deal of medical reform has made the pharmaceutical chain enterprises usher in greater development space.Under the encouragement of policies,various pharmaceutical chain enterprises focus on opening up a large number of retail network terminals and blindly enter the market,resulting in a series of business problems.On the other hand,due to the disadvantages of manual investigation of network terminal location,it is difficult to cover the new area in time.Therefore,for pharmaceutical chain enterprises,optimizing the scale and structure of retail network terminals and seizing the pharmaceutical market without wasting operating costs is an urgent problem to be solved.Pharmaceutical chain enterprises retain a large amount of data in the operation process,and can also obtain a large amount of supporting data from the Internet.Using these data combined with machine learning algorithm to study the location and optimization of pharmaceutical online retail terminals is helpful to realize the scientific location and retail network layout optimization of pharmaceutical chain enterprises and reduce the operation cost of enterprises,Enhance the competitiveness of enterprises.Taking s,a large chain pharmaceutical retail enterprise in Jinan,as the research object,this paper uses machine learning and big data analysis technology to study the location and optimization of s enterprise's pharmaceutical retail terminal by analyzing the relationship between s enterprise's pharmaceutical retail terminal and urban interest points.In the aspect of location selection of pharmaceutical retail terminals,nine characteristic variables are analyzed and determined from four aspects: population factors,competition factors,traffic factors and geographical factors;Then,the crawler technology is used to collect the information of interest points of various influencing factors,and the grid method of Arc GIS is used to divide the research area of Jinan into grids with appropriate size,count the number of various service outlets in the grid,and get the sample data;Then,the random forest,support vector machine,logistic regression and xgboost model of machine learning are used to learn the sample data set,establish a series of machine learning models for the location of pharmaceutical retail terminals,evaluate the model with evaluation indexes,and select the machine learning model with the best prediction result;Finally,the application research of Licheng District is carried out to formulate an appropriate site selection and expansion scheme.In the aspect of pharmaceutical retail terminal optimization,integrate and analyze the existing business data and urban interest point data of s enterprise,analyze and select characteristic variables from four aspects: management factors,geographical factors,demographic factors and service factors,build a multi classification machine learning model,and compare the model experimental results to find the optimal pharmaceutical retail terminal optimization model,Finally,optimize and analyze the pharmaceutical retail network terminals in Licheng District,put forward suggestions on the development and scale adjustment of existing terminals according to the classification results.The location optimization model obtained by using machine learning method in this study can not only provide decision-making basis for s enterprise's reasonable planning in Jinan,but also provide reference for the location optimization construction of retail terminals in other cities and other chain pharmacies.