Optimization On Online Supermarket Order Splitting And Order Consolidation And Package Distribution Based On Time-Space Network

The booming online retail industry has produced a number of large online supermarkets with Chinese characteristics.The new e-commerce model of large-scale online supermarkets,its convenient shopping methods and numerous merchandise items have brought great convenience to consumers' lives,but at the same time,its own operation development also faces many challenges.Online supermarkets have the characteristics of large-scale,warehouse operation,multiple products,and diverse customer receipt time.Order fulfillment centers often need to allocate tens of thousands of orders every day.Unreasonable distribution will not only cause high order fulfillment costs,multiple distribution,redundant packaging waste,etc.,will also lead to longer customer receipt cycles and lower satisfaction.Therefore,scientifically and efficiently processing consumer orders,reasonably and effectively shortening the package delivery cycle has become an academic frontier concern in the e-commerce field.Based on this,this thesis takes the large-scale online supermarket as the research background,takes the electronic orders issued by consumers in large online supermarkets as the research object,and shortens the order fulfillment cycle of large online supermarkets as the research goal,splits and consolidates large-scale online supermarket orders and packages.Distribution is a key research issue,with the inherent characteristics of warehouses and orders of large online supermarkets,consumer satisfaction as the starting point,fulfilling"dynamic variability","time benefit" and "space complexity" around online supermarket orders.The internal requirements,using the space-time network flow methodology,genetic algorithm theory,carried out research on the large-scale online supermarket order splitting and consolidation and package distribution.The research in this thesis contains the following two aspects:(1)For the problem of large-scale online supermarket order splitting and order consolidation,by analyzing the basic factors such as warehouse inventory and order demand that affect the problem,from the two dimensions of time and space,study the large-scale online supermarket under the dynamic update of time and space information.The specific plan for order splitting and consolidation.Firstly,aiming at the characteristics of time and geographical location changes in orders and packages during the fulfillment process,we use the space-time network flow method to minimize the package cost,package distribution cost,and minimize time cost.Based on the relationship between single flow,warehouse distribution flow and customer demand,a joint optimization model of online supermarket order splitting and order consolidation based on time-space network is constructed.Then,based on the characteristics of the model,the genetic algorithm is used to solve the model.Finally,the model is proved to be correct.The small-scale and large-scale experiments simulate the model and verify the correctness of the model and the effectiveness of the genetic algorithm.(2)For the large-scale online supermarket package distribution problem,by analyzing the economic cost of vehicle assignment and the benefit of customer receipt time in the distribution process,the large-scale online supermarket under the dynamic update of time and space information is studied from the two dimensions of time and space.Firstly,aiming at the huge amount of parcels generated by the online supermarket at each moment,the urgency of the customer's request for the delivery time,and the economics of the vehicle assignment during the distribution process,the online supermarket package distribution problem is studied based on the time-space network theory in this thesis.Then the distribution problem is described and defined in detail.With the goal of minimizing vehicle assignment cost and minimizing distribution time cost,an online supermarket package distribution model based on time-space network is established.The model objective function and the connection and meaning of each constraint are elaborated.The characteristics of the model are solved by genetic algorithm.Finally,the small-scale experiment and the large-scale experiment are used to simulate the model,and the correctness of the model and the effectiveness of the algorithm are verified.The research work of this thesis provides a new solution for large-scale online supermarket order processing and parcel delivery operations.The obtained online supermarket order splitting and order consolidation model based on time-space network,online supermarket package distribution model based on time-space network,genetic algorithm simulation results are all play important roles in promoting the formation of a more complete large-scale online supermarket order fulfillment theory research system,for large-scale online supermarket operation decision-makers in timely,efficient and scientific processing of large-volume,multi-variety orders.The basis of scientific decision-making has important theoretical significance and application value.