Research On Demand Forecast And Resource Scheduling Of Chain Retail Outlets In O2O Model

In recent years, under the impact of the rapid development of e-commerce, the overall performance of the traditional consumer market is weak, and traditional retail companies have to try O2 O model in order to promote their own transformation and upgrading. At the heart of the O2 O is the interacting and integrating of online and offline sources, and O2 O pays great attention to user experience. If missing offline experience, O2 O will be incomplete, and even cause the failure of the entire pattern. Therefore, as the first step of offline experience, to ensure the availability of the products becomes particularly important.To ensure the availability of products is simply about the content of the two aspects of demand and supply: For the side of demand, in order to grasp the demand situation of each retail outlets in advance, we need to predict the demand for each outlet. However, Due to the complexity of O2 O mode environment, the demand of each network is affected by many uncertain random factors both of online and offline. What’s more, the coverage of each retail outlet is very limited, and the random factors have large effect to the demand. Because the traditional forecasting method cannot take the influence of random factors into consideration, this paper uses the probability sorting model for demand forecasting research. For the side of supply, in order to meet the demand as well as saving the cost of scheduling, we need to develop resource scheduling research on the basis of the demand forecast to find the optimal scheduling scheme. In the study of probability sorting problem, we just know the order of the probability of each nature state and do not know the specific number, so we can’t accurately calculate the expected value, but only to find the expected value of the maximum and minimum values. That’s to say, demand forecasting result is an interval concept, and on this foundation, we consider using interval programming model to solve the resource scheduling problem.Based on this, the mainly research works of this article are as follows:(1) In-depth analysis the operating process of chain retail enterprises under O2 O model, and discuss resource scheduling process of chain retail enterprise in O2 O and the influencing factors of retail outlets demand;(2) Giving full consideration to the impact of possible random factors in the future on the demand forecasting of the retail outlets, set up the demand forecasting model based on probability sorting;(3) Based on the demand forecast research, set up the resource scheduling interval programming model, and solve it by transforming it into a deterministic programming problem;(4)A case is given to present the calculation process of demand forecasting and resource scheduling.This paper concentrates on the retail outlets, and from the perspective of both demand and supply, through the establishment of the demand forecasting model based on probability sorting and resource scheduling interval programming model, gives the program to effectively guarantee product availability so as to improve customer experience. This research fits the specific problems in O2 O practice and has very strong reality reference significance.