Research On Order Allocation And Path Optimization Of Take-Out System Under O2O Pattern

Since the emergence of online ordering of fast food in 2010,this ordering pattern has become a very popular consumption pattern in the catering industry until 2015.This pattern takes the Internet as the communication carrier and establishes information channels for ordering fast food between customers and restaurants through various application software,relying on numerous deliverers to take charge of offline delivery of food and items.This service pattern is called take-out ordering pattern under O2 O pattern because it integrates Internet(Online)communication and offline delivery process.The pattern is widely used in the market of logistics distribution and take-out.Driven by this pattern,the take-out market has experienced a period of germination,development,expansion and relative maturity.In recent years,on the basis of controlling distribution costs,various take-out companies pay more attention to the satisfaction of customers waiting for take-out,and the take-out market is also about to reach maturity.Intelligent distribution of delivery orders,accurate assignment of deliverers and reasonable scheduling of delivery routes will all have an impact on delivery costs and customer satisfaction in waiting for take-out.In this paper,the take-out delivery problem including order allocation and route scheduling is studied.It provides theoretical basis and reference for the development of take-out delivery industry and the study of related transportation scheduling and management problems.Based on the balance between supply and demand of commodity flow,this paper constructs a spatio-temporal network model of take-out distribution.The collaborative optimization of order distribution and route scheduling under dynamic distribution and the comprehensive optimization of customer satisfaction and delivery cost under accumulation status with static distribution are studied respectively.Aiming at these two kinds of problems,different optimization models and solving algorithms are designed respectively,and the rationality of the models and the feasibility of the algorithms are verified by numerical examples.Firstly,this paper introduces the development background,research significance and relevant research results of take-out delivery in recent years,analyzes the general process of take-out delivery,and makes a comprehensive comparison between the delivery and its essential problem VRP and its derivative problems.Therefore,the take-out delivery problem is determined to have its research significance,feasibility and uniqueness.Secondly,considering the dynamic generation of take-out orders in actual delivery problems,a spatio-temporal network model for collaborative optimization of take-out order allocation and delivery routes is constructed to minimize the cost of delivery.The model accurately represents the corresponding merchants and customers as well as the time window,and also represents the time process and spatial location of take-out delivery.An optimization algorithm with dynamic order allocation as the main algorithm and improved genetic algorithm as the sub-algorithm is designed.The rationality of the model and the feasibility of the algorithm design are verified by a simulation example under the condition of changing road conditions.Thirdly,the delivery problem in the backlogs is studied,and the spatio-temporal network model corresponding to this problem is also constructed to maximize customer satisfaction in waiting for take-out and minimize delivery cost as dual-optimization objectives.An improved dual-objective genetic algorithm is designed.Through the simulation example,the solution of "non-dominated" solution set provides several feasible solutions for take-out delivery.Finally,the paper summarizes the research content,analyzes the application scenarios and fields of the model and the algorithm designed in this paper,as well as the existing shortcomings.On the basis of the research of this paper,prospects are made.