Research On The Optimization Of The Ratio Of Two Types Of Delivery Personnel On O2O Takeaway Instant Delivery Platform

In the post-pandemic era,the O2 O food delivery market is growing,but due to the surge in orders,the user dissatisfaction and complaint rate of overtime has increased,resulting in a decline in customer satisfaction.In order to solve this problem,the O2 O takeaway instant delivery platform has adopted the method of increasing the number of delivery personnel,but this has also led to an increase in delivery costs.Therefore,the platform needs to balance the relationship between distribution costs and customer satisfaction.In order to reduce delivery costs and improve customer satisfaction,the O2 O takeaway instant delivery platform considers the optimal ratio of two types of delivery personnel in the two scenarios of order adaptation mode and joint delivery mode.(1)In the order adaptation mode,the impact of the two types of delivery personnel on distribution cost and customer satisfaction is analyzed by changing the ratio,and a mathematical model is constructed with the lowest unit satisfaction cost.According to the actual distribution process,the rolling time domain on-demand proximity matching algorithm is designed,and the optimal ratio of the two types of delivery personnel under different order volumes and order proportions is obtained through numerical simulation experiments.The results show that: When the total number of orders is certain and the proportion of special delivery orders is less than or equal to 70%,the optimal proportion of special delivery delivery personnel is 26%,and crowdsourced delivery personnel are74%.When this value is greater,the optimal proportion of dedicated delivery workers is 32%,and crowdsourced delivery people are 68%.Through the sensitivity analysis of parameters such as order volume,time window length and vehicle capacity,it is shown that the change of order window length and vehicle capacity will not affect the optimal composition ratio of the two types of delivery personnel.The increase in the total number of orders has the most significant impact on the optimal ratio of the two types of delivery people.(2)In the common distribution model,consider the impact of changes in the composition ratio of the two types of delivery personnel on distribution costs,and introduce the concept of minimum customer satisfaction to ensure cost reduction while maintaining stable customer satisfaction.An optimal matching model with the goal of minimizing the total cost of platform distribution is constructed,and an undifferentiated delivery algorithm for rolling time-domain orders is designed.Through simulation experiments,the optimal ratio of two types of delivery personnel under different order volumes is solved.The results show that: When the order volume is fixed,with the increase of the proportion of special delivery personnel,the total delivery cost and customer satisfaction show an overall upward trend.The optimal composition ratio of the two types of delivery workers is 48%-56% of dedicated delivery workers and 44%-52% of crowdsourced delivery workers.By changing the order size,time window length,vehicle capacity and other parameters,it is found that the total cost of distribution increases with the increase of time window length and order volume.The order volume has the most significant impact on the target value.The above conclusions further expand the research in this field.The results of this thesis can provide multi-angle solutions for O2 O takeaway instant delivery platforms to solve problems related to reducing delivery costs and improving customer satisfaction.By optimizing the composition ratio of private delivery and crowdsourcing delivery personnel,it will promote the further development of the O2 O takeaway instant delivery platform.