Research On Dynamic Scheduling Of Unmanned Delivery Vehicles For Instant Retail

Under the influence of the continuous expansion of the instant retail market and the transformation of consumer consumption patterns,people’s requirements for the timeliness of the delivery of instant retail goods are getting higher and higher,and the high distribution cost in the distribution process and the frequent safety accidents of delivery personnel restrict the further development of instant retail enterprises.With the continuous maturity of unmanned distribution vehicle production and application technology,unmanned delivery vehicles have entered daily life.In this context,the scheduling research of unmanned delivery vehicles under instant retail has become a new problem to be solved.Based on this,in view of the characteristics of dispersion,randomness,dynamism and timeliness of instant retail orders,combined with the requirements of unmanned vehicle delivery for load and driving speed,the scheduling of unmanned delivery vehicles under the background of instant retail is considered.According to the business scale of instant retail enterprises,it can be divided into two scenarios of single-vehicle situation and multi-vehicle situation for research,respectively,the dynamic scheduling model of unmanned distribution vehicles under the single-vehicle situation and the dynamic scheduling model of unmanned distribution vehicles in the multi-vehicle situation are established,and intelligent algorithms are designed to solve them,and a large number of numerical simulation studies are carried out for comparative analysis,and finally the research conclusion is drawn.The specific research content and main research conclusions are as follows:(1)Research on the dynamic scheduling of unmanned distribution vehicles in the case of bicycles.Taking the minimum total distribution cost as the objective function,a dynamic scheduling model of unmanned delivery vehicles is established,two order processing methods are adopted,the advance processing strategy and non-advance processing strategy are adopted,and the rolling time domain optimization algorithm is designed to solve the problem,and the effectiveness and applicability of the strategy are verified through a large number of simulation experiments.The main results show that:(1)The distribution range has the most significant influence on the objective function.(2)The rolling time domain duration and time window interval under the advance processing strategy have a greater impact on the objective function,while the rolling time domain duration and time window interval under the non-advance processing strategy have less impact on the objective function.(3)In the case of bicycles,the total distribution cost of the non-pre-processing strategy is lower than that of the pre-processing strategy.(2)The dynamic scheduling problem of unmanned delivery vehicles in the multi vehicle situation is studied.Due to the different sizes and distribution ranges of instant retail enterprises,a single unmanned vehicle is difficult to meet the distribution needs of different enterprises.In the case of multiple vehicles,the allocation results of orders and vehicles,as well as the selection of vehicle travel paths,affect the timeliness of order delivery.In the case of multiple vehicles,the distribution range is expanded and the number of orders increases.Based on the characteristics of order dynamics,with the minimum total distribution cost as the objective function,a dynamic scheduling model for unmanned delivery vehicles is established.Two order processing methods,namely,advance processing strategy and non advance processing strategy,are adopted.Based on the complexity of the problem in the case of multiple vehicles,an improved genetic algorithm is designed to solve the problem,improving the quality of solution and shortening the solution time,A large number of simulation experiments have been conducted to verify the effectiveness and applicability of the strategy.The main research results show that:(1)The distribution range has the most significant impact on the objective function.(2)The rolling time domain duration and time window interval have the same impact on the objective function under the two strategies.The rolling time domain duration has a smaller impact on the objective function,while the time window interval has a larger impact on the objective function.As the number of vehicles increases,the total distribution cost under the two strategies decreases significantly.(3)In the case of multiple vehicles,the total delivery cost of the advance processing strategy is lower than that of the non-advance processing strategy.The research conclusion will expand the research results of vehicle dynamic scheduling issues in the field of unmanned distribution under instant retail,provide a theoretical reference for instant retail enterprises to further promote the unmanned vehicle distribution model,achieve cost reduction and efficiency increase,and promote the development and application of intelligent logistics.