Study On Optimization Of Takeout O2O Orders Allocation With Meal Time

In recent years,the take-out O2 O industry has achieved rapid development with the rapid development of the Internet economy and the encouragement and support of national policies.With the increase in per capita disposable income and changes in user eating habits,takeaway has become a very important part of people's daily diet.However,in the environment where market demand is increasingly strong,there has been a contradiction between the realistic distribution capability of take-away and the high demands and high expectations of customers for delivery services.With the end of the platform subsidy war,users' main focus has shifted from price to time and food quality.Distribution timeliness is one of the important indicators to measure whether the demand is met.If any take-out platform can improve the quality of distribution services and reduce distribution costs while continuously improving the user experience,it will be in an advantageous position in the future competition.The issue of take-out order allocation is one of the key links in the take-out scheduling process,which plays an important role in improving the efficiency of take-away distribution and reducing the distribution cost.At the same time,the issue of take-out order allocation is also a hot research area.This paper mainly studies the issue of the distribution of take-out orders.The main research work is as follows:(1)The issue of take-out order allocation is a very complicated issue.Not only is it affected by certainty factors,it is also affected by many uncertainties.As a matter of uncertainty,meal time has a great influence on the accuracy and rationality of order distribution.It is a key factor affecting the timeliness of delivery and the quality of service.When the delivery person arrives at the merchant,if the delivery has not been completed,it will take a while.This will result in wasted capacity and will affect the delivery of other orders.Especially at peak times,it will affect the overall capacity allocation.If the merchant has already eaten and the delivery staff has not arrived,the taste may have changed when the food is delivered to the customer,which may lead to a decrease in customer satisfaction.Therefore,this article fully considers the factor of meal time when making order allocation.Since the meal time is random,it cannot be determined and cannot be directly calculated.Therefore,this paper analyzes the factors affecting the meal time from multiple dimensions,and constructs a predictive model to predict it,thus providing a basis for subsequent decision-making.(2)In the real-life scenario,most platforms only consider the attributes of a single order when placing orders,and pay less attention to the correlation between multiple orders.The distribution mode of a single order,the amount of delivery per unit time is low,and the distance of the entire distribution process increases,resulting in low distribution efficiency and increased distribution costs.To solve this problem,when assigning orders,this paper firstly merges similar orders according to spatial similarity and time similarity to form a distribution task package,which is then distributed to the same delivery staff.The allocation method of order consolidation can effectively improve the overall distribution efficiency and make rational use of resources compared to the single order allocation method.Thereby increasing the amount of delivery per unit time and reducing the distribution cost.(3)The issue of take-out order allocation has a strong complexity,with dynamic,time window constraints,delivery order constraints,and strict matching of merchant customers.Aiming at this problem,this paper combines the actual business process of take-out with the minimization of distribution cost as the optimization goal,and transforms the actual problem into an optimized model with time window constraint and delivery matching.Due to the manyto-many phenomenon between the merchant and the customer in the actual scenario,this paper turns the many-to-many problem into a one-to-one problem by setting up a virtual point.Simplify the originally complicated problems and facilitate subsequent solutions.(4)The complexity of the issue of the order of the take-out order also increases the difficulty of solving the problem.Based on the existing literature research and actual investigation,this paper designs a two-stage solving algorithm.A rolling time domain mechanism is introduced for the dynamics of the order allocation problem.The entire delivery time domain is divided into several equal-length time windows to achieve dynamic solution.On this basis,the X-means algorithm is first used to merge similar orders,and then the genetic algorithm is used to achieve the optimal match between the order and the delivery staff.Finally,an example is designed to verify the model and algorithm constructed in this paper.The experimental results prove that the mathematical model and two-stage algorithm for solving the take-out order allocation problem proposed in this paper are effective.In this paper,in the research of the distribution problem of the order for sale,the optimization model with time window constraint and order matching of each point is constructed.According to the characteristics of the problem studied in this article,a two-stage algorithm of X-means algorithm and genetic algorithm is designed to solve the problem.The research in this paper has certain reference and reference value for the research of order allocation in the O2 O industry.Can provide some auxiliary functions for the operation decision of the Takeout platform.