Research On O2O Takeaway Delivery Path Optimization Under Crowdsourcing Mode

In the context of the normalization of the epidemic,O2O food delivery has become one of the mainstream of people’s lifestyles,and this mainstream has also attracted countless delivery staff to engage in the O2O food delivery service industry.However,providing a good delivery service not only means direct benefits to the delivery staff,but also accompanied by the quiet expenditure of delivery costs.Therefore,based on the crowdsourcing model,under the premise of ensuring customer satisfaction and controlling delivery costs,this paper studies the optimization of O2O takeaway delivery routes.In this paper,in the optimization problem of O2O takeaway delivery path under the crowdsourcing mode,according to the order distribution method,crowdsourcing is divided into two modes: order dispatch and order grabbing.In the order dispatch mode,the crowdsourced courier only needs to visit the matched restaurants and customers in each order in an orderly manner;while in the order grab mode,due to the random appearance of order demands and the dynamic position of each crowdsourced courier.The change makes the delivery problem in this mode a dynamic programming problem,so it is analyzed from the two stages of "initial order grabbing plan" and "dynamic scheduling plan".For order types,the concept of order priority is introduced to distinguish orders into VIP orders and basic orders(where there is a penalty cost for VIP orders).For the delivery time,a relatively open soft time window is established.From the perspectives of customer satisfaction and delivery cost,the delivery access process is simplified by setting virtual points,and the order priority is considered,with a soft time window,multiple visits to each node,orderly pairing,pick-up and delivery are constructed.Two kinds of path optimization models,sequential and multi-dispatch center,convert multi-objective into single-objective through the inverse function method,and design for genetic algorithm and iterative local search algorithm respectively according to the different characteristics of crowdsourcing order dispatch and order grab mode and improvements to complete the solution to both models.Finally,through the verification and comparison of numerical examples,it is proved that the optimization model constructed in this paper and the improved genetic algorithm and iterative local search algorithm have a significant optimization effect on the O2O takeaway delivery path in the crowdsourcing mode,and the delivery speed of the crowdsourcing delivery staff is obtained.Before a certain value,the impact on the delivery results is greater,and then the impact tends to be stable,and the maximum cargo weight of the delivery tool has no significant impact on the delivery results.Standards provide reference value.In this paper,through the research on the optimization of O2O takeaway delivery paths in the crowdsourcing mode,a mathematical optimization model is constructed in the two modes of crowdsourcing and order grabbing,and through the design and improvement of the genetic algorithm and iterative local search algorithm,the problem solving.While solving real-life problems,it improves the service level of the O2O takeaway platform,reduces delivery costs,and ensures customer service satisfaction and actual benefits of crowdsourcing delivery staff.