Research On Distribution And Path Optimization Of Takeaway Orders Under Crowdsourcing

Since the Internet has gradually become a part of people's daily life,the rapid development of technology has enabled the Internet to integrate with many traditional industries,resulting in many new industries.This new industry's online and offline cooperation model is called the O2 O model.As a logistics terminal distribution industry that has developed rapidly in recent years,take-out has become a much-needed service favored by customers.In the context of the "Internet+" era,the rise of Meituan takeout and hungry delivery platforms have closely linked the traditional catering industry and the Internet.The vigorous development of the take-out industry has also provided an environment for the emergence of the crowdsourcing distribution model.Crowdsourcing distribution provides a new way of thinking about takeaway delivery by integrating the free resources of the public,effectively easing the pressure of takeout delivery.However,the crowdsourcing delivery model also faces many problems in delivery order delivery.Delivering delivery to customers within a specified time is an important factor that affects customer satisfaction,but a large influx of delivery orders during the peak time period is at the current stage.Crowdsourcing delivery capabilities have brought huge challenges,which shows that the weak takeout order processing capacity in the crowdsourcing mode and the inability of orders to be delivered to customers in time have become an urgent problem to be solved by major takeout crowdsourcing distribution platforms.The first reason for these problems is that the order distribution model of the crowdsourcing distribution platform lacks scientific and unified guidance,and is only distributed based on experience.The takeout distribution model is mainly divided into merchant self-delivery and full-time delivery platform delivery(Hummingbird special delivery,Meituan special delivery)Delivery,Baidu Knight)and crowdsourcing distribution platform distribution(Hummingbird crowdsourcing,Meituan express,Jingdong crowdsourcing,Dada).The order distribution mode of take-out includes the mode of grabbing orders,the mode of dispatching orders,and the mode of combining dispatching orders.However,the current mode of order allocation for crowdsourcing distribution platforms is the mode of grabbing orders based on the immediate processing of orders,that is,the orders placed by customers from the takeaway platform immediately Sending to the order-bill distribution pool,the total delivery person grabs the order or assigns it to the delivery person,lacking the idea of similar order concentration and order optimization,resulting in the phenomenon that orders that are far away and orders that are close are assigned to the same delivery person.The distribution distance per person has increased greatly,resulting in a waste of resources.Secondly,due to the low entry threshold of the takeout crowdsourcing distribution platform,and the takeout delivery staff is a part-time delivery,without professional training,when facing the distribution of multiple orders in the process of order delivery,you can only use orders for orders from different locations The sequential delivery may lead to an unreasonable order distribution order,resulting in some orders cannot be delivered to customers within the specified time.In this paper,the research work on the optimization of the distribution path of takeout orders under the crowdsourcing distribution model is as follows:(1)First collect the relevant research and data to get the concept,research background and theoretical basic knowledge about crowdsourcing mode,order allocation and path optimization,and then combine the business processes of D crowdsourcing delivery platform to find out the takeout order under crowdsourcing mode The unresolved delivery problems are mainly due to unreasonable order allocation and crowdsourcing delivery staff who cannot select the optimal delivery path when facing many orders during peak periods,resulting in order delivery overtime and affecting customer satisfaction.(2)For the problem of distribution of takeaway orders,use a clustering algorithm to cluster the orders and assign them to the corresponding crowdsourcing delivery staff.In this paper,according to the distribution of order demand points of a business during the peak period of a day,clustering demand points based on the clustering algorithm based on AP and K-Means,after obtaining the clustering result,assign a certain order to the crowdsourcing delivery staff.(3)To solve the problem of delivery route optimization for take-out orders,first establish a vehicle route optimization model with a hard time window,which minimizes the delivery cost as the objective function.The delivery cost includes vehicle transportation costs and penalty costs due to overtime,considering the customer's time window and Constrain the maximum load of the vehicle,and use the improved genetic algorithm to solve the model.(4)Take the merchant A of Xuhui District,Shanghai as an example to conduct an empirical analysis to verify the effectiveness of the method used in solving the problem of distribution of delivery orders and path optimization.