Abstract:

With the rise of new retail in the community， grid warehouse， as a transfer station linking online platforms and off line stores， is particularly important. However， online purchase demands of community customers are seriously affected by the changeable distribution environment of grid warehouses and the difficulty of delivery time. The decisions of grid warehouse operators are inevitably affected by the change of online demand distribution in communities， which brings high sorting and transportation costs and difficulties in profits making. Firstly， based on the analysis of interaction mechanism between the changes of community demand and the decision of grid bin distribution， a “community demand prediction and grid bin distribution decision making” iterative optimization framework is proposed in order to solve these problems. Secondly， a model of demand prediction based on support vector regression algorithm is constructed to predict the demand of community orders. Thirdly， an optimization model about distribution path of grid warehouse is constructed with the goal of profit maximization， using the adaptive large neighborhood search algorithm to solve it. Finally， an example with 35 communities is given to verify the effectiveness of the framework we proposed with the models and algorithms. Additionally， the changing rules of profit variation in different conditions is deeply explored based on the actual situation. It is shown that： （1） Using the iterative optimization framework considering different demands can increase total profit by about 50%. （2） In the stage of grid warehouse distribution decision， compared with the solution by Cplex solver， the Adaptive Large Neighborhood Search algorithm can Increase efficiency more than tenfold. （3） In the same region， the expansion of scale does not always lead to an increase in profits. As the number of pick-up points increases， the total profit shows a trend of “first increase and then decrease”. （4） For grid warehouse operators， it is recommended to use minivans and light trucks responsible for distribution tasks. The research achievement of this paper will provide a theoretical basis for the operation decision optimization of grid warehouse in the new retail environment.

Key words: new retail in community, grid warehouse, demand prediction, distribution decision, iterative optimization