565 results about "Delivery efficiency" patented technology

The invention relates to the field of supply chain management and optimization, in particular to a crude oil supply chain management method and system, and the method comprises the steps: constructing a supply chain dynamic model through multi-modal data fusion and causal analysis; real-time data and prediction data are generated based on a digital twinning technology, and cross-node association scenes and extreme climate conditions are simulated; a transportation path, an inventory allocation strategy and a delivery sequence are dynamically optimized through a multi-objective optimization algorithm and a flexible emergency adjustment module; an optimization scheme is automatically executed by using an intelligent contract system, feedback adjustment data and improved scheme data are generated based on real-time feedback, and closed-loop optimization is realized. The dynamic adaptive capacity of the crude oil supply chain in a complex environment is effectively improved, the cost, the inventory turnover rate and the delivery efficiency are optimized, and meanwhile the robustness and the emergency response capacity of the system are enhanced.

The invention relates to the technical field of mine warehouse management, in particular to a self-service warehouse-out system and method, and the system comprises a sensing and interaction module, a data processing and storage module, an automatic carrying and storage module, and a safety and monitoring module. The sensing and interaction module realizes functions such as cargo identification and identification; the data processing and storage module manages inventory, user and task data and analyzes and processes the data; equipment of the automatic carrying and storage module carries goods according to instructions, and the intelligent goods shelf can be automatically adjusted; and the safety and monitoring module ensures accurate cargo quantity, monitors the warehouse and controls personnel to enter and exit. The method comprises the steps that a user initiates an ex-warehouse request, a system checks an inventory and calculates an equipment scheduling priority, then cargo carrying and ex-warehouse operation including equipment scheduling, path planning, carrying detail determination and the like is carried out, and meanwhile weight monitoring, image monitoring and the like are carried out. The warehouse-out efficiency, the inventory management accuracy and the cargo handling safety are improved, and the intelligent level of warehouse management is improved.

The invention provides a railway engineering completion delivery data information extraction method based on digital twinning. Relates to the technical field of engineering data processing. The technical key point of the invention lies in how to construct a dynamic digital twinborn model by integrating various technologies, such as BIM, Internet of Things, big data, AI and the like, and in combination with technologies, such as real-time data monitoring, intelligent analysis, data sharing and the like, the quality control, operation optimization, decision support and completion delivery efficiency of a railway construction project is improved.

The invention relates to the technical field of logistics order delivery management, in particular to a cross-border e-commerce logistics order management system based on big data, which comprises a data acquisition processing unit, an order clustering delivery unit and a delivery execution feedback unit, the data acquisition and processing unit collects orders, geographic information and real-time traffic data from a cross-border e-commerce platform and performs cleaning preprocessing, repeated orders are removed by using a Hash algorithm, the order clustering and delivery unit clusters the orders by using a density peak clustering algorithm, and the clustering effect is optimized by combining the order emergency degree and the customer loyalty, so that the service quality of the cross-border e-commerce platform is improved. A genetic algorithm is adopted to optimize the delivery sequence, the crossover and mutation probability is dynamically adjusted, a fitness function is calculated by considering the delivery distance, time cost and regional limitation penalty factors, a delivery execution feedback unit sends an optimized route to a delivery vehicle, client feedback evaluation data is collected, a delivery strategy is dynamically adjusted by means of an upper confidence bound algorithm, and the delivery efficiency is improved. And the delivery efficiency and the customer satisfaction are improved.

The invention relates to the field of order delivery, in particular to a delivery order intelligent management method and system. The method comprises the following steps: collecting a fresh food delivery order stream, and carrying out effective delivery time window calculation to obtain a dynamic effective time window of each order; identifying available deliverymen in the region, performing real-time delivery load evaluation, and generating a real-time delivery load index; performing intelligent order allocation according to the dynamic effective time window and the real-time delivery load index to obtain newly added order information; performing order priority dynamic evaluation based on the newly added order information to obtain an order delivery priority; and carrying out distribution sequence and path re-planning according to the order distribution priority, and generating a latest distribution planning scheme. The fresh food order delivery efficiency is improved, and the customer purchase experience is optimized.

The invention discloses an industrial ERP dynamic scheduling optimization method based on deep reinforcement learning, and the method comprises the following steps: S1, obtaining to-be-scheduled industrial ERP data, and carrying out the preprocessing of the to-be-scheduled industrial ERP data; s2, constructing a heterogeneous graph structure, and setting node types and edge weight parameters in the graph; s3, performing multi-layer graph feature extraction on the initial scheduling state graph based on a graph attention mechanism to generate a node feature vector; s4, constructing a distributed reinforcement learning environment, and setting an independent strategy sub-network for each type of scheduling sub-tasks; s5, performing joint decision-making on the scheduling action to generate a scheduling scheme as a current round scheduling result; s6, calculating a reward value and feeding back the reward value to the corresponding strategy sub-network; and S7, repeatedly executing the steps S1 to S6, and generating a new scheduling action by using the updated strategy sub-network. According to the method, adaptive optimization of industrial ERP scheduling under multi-source heterogeneous data is realized, and the resource utilization rate and the order delivery efficiency are remarkably improved.

The invention discloses a predictive order dispatching system based on digital twinning, and relates to the technical field of intelligent order dispatching, the predictive order dispatching system comprises four core modules: an urban transport capacity digital twinning construction module integrates order dispatching platform historical orders, real-time traffic flow and urban GIS data, constructs and updates a twinning model, and divides standard grid units; a short-term order demand prediction module obtains grid order, traffic and environment feature sequences based on the model, and predicts order quantity and thermodynamic diagrams in 15-30 minutes in the future; a transport capacity supply and demand gap early warning module analyzes the gap and generates early warning; the active intervention and optimization module generates an instruction according to a preset strategy, dispatches transport capacity through order pre-dispatching and the like, and then evaluates and optimizes the strategy according to feedback. The system realizes order pre-judgment, accurate transport capacity allocation, reduction of supply and demand imbalance, shortening of user waiting time, reduction of operation cost, and improvement of delivery efficiency and service quality.

The invention discloses an urban unmanned aerial vehicle cargo distribution route planning method and system and an unmanned aerial vehicle. The method comprises the following steps: acquiring flight information of an urban area; analyzing the flight information to obtain a planned route; setting a landing site in the urban area according to the planned route; and transferring the carried goods at the landing site according to the planned route, so that the goods are conveyed from the ground to a destination within a preset mileage. According to the method, the unmanned aerial vehicle route is formulated, the stations are set in the route, and the unmanned aerial vehicle delivers goods in the planned unmanned aerial vehicle route, so that the delivery efficiency is improved.

The invention relates to a cold-chain food distribution analysis method and system based on big data, and the method comprises the steps: carrying out the dynamic feature extraction of multi-source monitoring data of a cold-chain food distribution vehicle, and obtaining and generating transportation state parameters; carrying out correlation matching on the transportation state parameters and real-time environment data of the cold-chain food distribution vehicle to obtain an environment influence evaluation result; carrying out distribution efficiency analysis on the vehicle path transportation data of the cold-chain food distribution vehicle based on the environmental influence evaluation result to form initial distribution efficiency data; road condition diagnosis is carried out on the route transportation data, route pre-judgment is carried out in combination with the environmental influence evaluation result, and a route prediction result is generated; and performing cross analysis on the initial delivery efficiency data and the path prediction result, and formulating a global delivery scheme of the cold-chain food delivery vehicle. According to the invention, logistics resource configuration can be optimized, and the overall operation efficiency of cold-chain logistics is improved.

The invention discloses a near space unmanned aerial vehicle launch trajectory optimization method, device and equipment and a storage medium, and the method comprises the steps: determining a take-off point and a target launch point of an unmanned aerial vehicle according to a launch task when the launch task is received; constructing a motion model of the unmanned aerial vehicle, and constructing a target function corresponding to the launching trajectory of the unmanned aerial vehicle and a plurality of constraint conditions based on the motion model of the unmanned aerial vehicle; constructing a putting trajectory planning problem model based on the objective function and a plurality of constraint conditions; based on the take-off point, the target delivery point and the delivery trajectory planning problem model, performing optimization solution on the delivery trajectory to obtain an optimal delivery trajectory; the unmanned aerial vehicle is controlled to be launched in the near space according to the optimal launch trajectory, and the optimal launch trajectory is optimized and solved under the target function corresponding to the launch trajectory of the unmanned aerial vehicle and multiple constraint conditions, so that efficient trajectory optimization of the unmanned aerial vehicle in the near space under the multiple constraint conditions is realized; and the launching efficiency of the unmanned aerial vehicle and the task execution success rate can be improved.

The invention relates to the technical field of distribution scheduling, in particular to a multi-mode fusion take-out distribution scheduling system and method, and the system comprises a real-time data collection module, a scheduling algorithm optimization module, an autonomy enhancement module, an adaptation module, a rider behavior analysis module, a distribution dynamic division module, an emergency response module, and a performance optimization module. The real-time data acquisition module is used for data acquisition and data verification; according to the multi-mode fusion take-out delivery scheduling system and method, multi-channel data acquisition, algorithm optimization, autonomy enhancement, environment adaptation, behavior analysis, regional management, customer service support and performance optimization are fused; according to the system and the method, the problems of data singleness, algorithm stiffness, lack of flexibility and poor environmental adaptability in a traditional intelligent delivery process are effectively solved, the intelligent level of take-out delivery is improved, the delivery efficiency and the customer experience are improved, and powerful support is provided for sustainable development of the take-out industry.

The invention discloses a resource creation method, device and equipment for model service and a medium, and relates to the technical field of computers, and the method comprises the steps: converting a model service deployment demand input by a user into a standardized service template; analyzing the standardized service template to obtain a model service resource scheduling instruction, the model service resource scheduling instruction being used for indicating a target resource pool; and determining a target driver corresponding to a target resource pool indicated by the model service resource scheduling instruction, so as to create cloud resources of the model service in the target resource pool by using the target driver, thereby realizing automatic resource creation of the model service, greatly shortening the deployment period through full-process automatic operation, reducing the labor cost, and improving the deployment efficiency. The heterogeneous resource management process is effectively integrated, the delivery efficiency is remarkably improved, and an enterprise can flexibly and efficiently deploy various AI model services on a private cloud platform and deal with quickly changing business requirements leisurely.

The invention relates to the technical field of content analysis, and particularly discloses a delivery analysis method and system based on content characteristics and propagation effects, and the method comprises the steps: obtaining a plurality of delivery contents based on a target keyword; multi-dimensional putting effect analysis is carried out, and a putting effect comprehensive score is generated; performing content characteristic analysis on the plurality of delivery contents to generate a content quality score; acquiring propagation data of a plurality of delivery contents, constructing a propagation network based on the propagation data, inputting the propagation network into a pagerank model, and outputting a propagation effect score; and generating a delivery analysis report according to the delivery effect comprehensive score, the content quality score and the propagation effect score. Through analysis of multi-dimensional indexes such as the delivery amount, the category, the time interval distribution and the re-delivery proportion, a delivery effect comprehensive score is generated based on standardization and a weight distribution mechanism, the overall performance of a delivery strategy can be evaluated, delivery effect feedback can be provided, systematic decision support is provided, and the delivery efficiency and the return rate are improved.

The invention discloses a control system and method of an intelligent express cabinet, and relates to the technical field of express logistics. In order to solve the problems that in the delivery process of an existing express cabinet, a courier still needs to manually input parcel information and select proper cabinet cells for delivery, operation is complex, efficiency is low, and errors are prone to occurring. The control system of the intelligent express delivery cabinet comprises the intelligent control cabinet, code scanning, identification and delivery processes of packages can be rapidly and accurately completed through the automatic intelligent express delivery cabinet, the express delivery processing efficiency and convenience are greatly improved, a courier does not need to manually input package information, human errors are reduced, meanwhile, the package input time is shortened, and the express delivery efficiency is improved. According to the express delivery cabinet, accurate delivery control ensures that a user can easily and quickly find and take out own parcels, the requirement of manual intervention is reduced, the human resource cost is reduced, the turnover rate of the express delivery cabinet is also improved, each cabinet grid can be fully utilized, and the operation cost is further reduced.

The invention discloses a short-distance order selection and real-time delivery response method and system, and the system comprises an order receiving module, an order optimization module, a delivery path planning module, a deliveryman distribution module, a state monitoring and feedback module and an exception handling module, the order receiving module is used for receiving a delivery order submitted by a user through a mobile terminal or a webpage terminal, carrying out the preprocessing of order information, and transmitting the preprocessed order information to a server; the order optimization module is used for ordering and selecting orders through an optimization algorithm on the basis of geographic positions, delivery time requirements and commodity characteristics of the orders, the delivery path planning module is used for generating an optimal delivery path according to the selected orders and adjusting the delivery path in real time by utilizing a dynamic path optimization algorithm, and the deliveryman distribution module is used for distributing the deliveryman. According to the current state, the distance and the workload condition of the deliveryman, the order is allocated to the optimal deliveryman, so that the order selection and delivery efficiency is improved through an intelligent means, the delivery path is optimized, and the abnormal condition in the delivery process is responded in time.

The invention discloses an intelligent construction digital delivery method and system based on master-slave multiple chains, and relates to the technical field of engineering construction management, and the method comprises the steps: carrying out the unique identification code coding of an engineering construction file, generating a file identifier, and constructing a multi-participant co-construction platform; performing sharing and encryption management on file data among participants based on a master-slave multi-chain consensus mechanism; and managing business process data through the cooperative work of the main chain and the side chain, and automatically judging the authority of the access request of the user. According to the intelligent construction digital delivery method based on the master-slave multiple chains, the identification and management efficiency of the file is enhanced by generating the unique engineering construction file identification code, the file sharing efficiency is improved through point-to-point butt joint and data sharing of the engineering file among multiple parties, and the intelligent construction digital delivery efficiency is improved through a master-slave multiple chain intelligent contract mechanism. The safety and the management efficiency of the project file are improved, and better effects are achieved in the aspects of the management efficiency, the safety and the sharing efficiency.

The invention provides an intelligent cooking supervision optimization system based on digital twinning and a construction method, and solves the problems of insufficient whole-process supervision of a traditional kitchen, lagging of real-time early warning and difficulty in operation standardization. The system constructs a virtual model through high-precision modeling (geometry, physics, behaviors and rules); the whole stir-frying link is uniformly coded by using an industrial internet identification analysis technology, so that data tracking and tracing are realized; a real-time data acquisition, transmission and analysis mechanism is established, and seamless virtual-real mapping between physical equipment and a digital platform is realized; and a visual control interface is constructed to support ordering and remote control. A scheduling rehearsal mechanism based on an improved ant colony algorithm is innovatively proposed, multi-task multi-pot dish distribution scheduling is optimized, trial and error cost is reduced, and meal delivery efficiency and system stability are improved. The system provides support for digital and intelligent transformation of the catering industry, and improves food safety supervision and kitchen operation efficiency.

The invention belongs to the technical field of unmanned aerial vehicle control, and discloses an unmanned aerial vehicle delivery method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining the delivery task information of an unmanned aerial vehicle, controlling the unmanned aerial vehicle to fly to an air area to obtain the position information of a target identifier, and recognizing the motion state of the target identifier based on the position information, and when the target identifier is in a moving state, calculating to obtain a predicted moving track of the target identifier through a dynamic target prediction model, generating flight path information according to the environment information in combination with the position information or the predicted moving track, controlling the unmanned aerial vehicle to fly to a delivery position corresponding to the flight path information, and performing wind speed compensation based on the wind speed compensation information. Controlling the unmanned aerial vehicle to deliver the target material to a receiving area corresponding to the target identifier; and based on the environment information and the position information or the delivery position corresponding to the flight path information generated by the predicted movement track, the unmanned aerial vehicle is controlled to deliver, and the delivery efficiency of the unmanned aerial vehicle is improved.

The invention provides an operation control method and device for a road-occupying unloading carrying vehicle, a medium and equipment, and belongs to the technical field of transportation control. According to the method and the device, for the vehicles which occupy the road for unloading on the one-way road, when the vehicles enter the unloading preparation stage, the affected vehicles which are affected by the road-occupying unloading of the vehicles and cause the distribution influence are identified, and the saving duration and the avoiding duration which are generated when the affected vehicles are avoided are simulated and calculated; the method comprises the following steps: calculating an avoidance profit value corresponding to a simulation avoidance situation on the basis of the simulation avoidance situation, determining an avoidance strategy from various simulation avoidance situations according to the avoidance profit value, and performing avoidance on one or more influenced vehicles according to the avoidance strategy. Thus, although the delivery duration of the target vehicle is longer than the pre-estimated duration, the delivery duration of one or more affected vehicles can be saved, and the delivery efficiency of the whole delivery control system can be improved.

The invention discloses an intelligent bidding method and device based on an Apple advertisement marketing interface, and relates to the technical field of advertisement putting, and the method comprises the steps: constructing a double-branch machine learning model comprising a long and short-term memory time sequence branch and a gradient boosting tree feature branch; training the model by using historical delivery data to obtain a target prediction model; collecting real-time delivery data through an Apple advertisement marketing interface, and generating a plurality of candidate bidding strategies according to a preset business rule; inputting the real-time data and the candidate strategy into a target prediction model to obtain a conversion probability prediction value and a cost distribution prediction value of the candidate bidding strategy; based on the predicted value, calculating a strategy score value through a score function, and screening out a high-score strategy combination; and integrating keywords, audiences, time periods and region adjustment parameters of the strategy combination, and generating an optimal bidding strategy package. According to the application, the Apple Ads advertisement bidding strategy can be efficiently and automatically optimized so as to improve the putting efficiency and the cost control.

The present invention provides an intelligent path planning method and system for logistics drones, which relates to the field of data processing technology, including: reading multiple RFID tag information of multiple packages to be delivered; obtaining the standard logistics performance of M idle drones of the same model; performing joint optimization of logistics task allocation to obtain M delivery allocation strategies and M logistics delivery paths; fitting to the delivery verification map to locate M verification tag sequences; during the loading process, performing loading deviation verification through an onboard scanner; during the execution of package delivery, performing path execution deviation verification through M verification tag sequences. The present invention solves the technical problem that the path planning method of the prior art is usually based on fixed maps or preset rules, and it is difficult to dynamically adapt to multiple packages, complex paths and real-time delivery needs, resulting in insufficient efficiency and reliability of logistics delivery.

The embodiment of the invention discloses a code test case generation method and system, equipment and a storage medium. According to the technical scheme provided by the embodiment of the invention, the difference code between the new branch code and the reference branch code is determined by obtaining the new branch code; querying a pre-constructed code call chain relationship library based on the difference code, determining matched call chain relationship information as a target call chain relationship, querying a pre-constructed code case association library based on the difference code, and determining matched case information as a target case; and constructing a test case of the difference code based on the target call chain relationship and the target case, so as to perform code testing of the difference code based on the test case. By adopting the technical means, accurate and efficient construction of the difference code test case can be realized, and the generation efficiency of the test case is improved while the accuracy of the test case is guaranteed. Tedious processes of manual use case creation and maintenance are avoided, so that the software quality and the delivery efficiency are improved.

The embodiment of the invention discloses a data space and a data interaction method. The data space comprises a plurality of modules, and an efficient intelligent data circulation system is constructed. The data market platform stores data resource description, and the data resource library is responsible for storing data governance information. And the AIAgent module converts query of a data demander into a structured request through a natural language processing technology, and performs data matching. And a matching result generates a data use protocol through the contract management module, so that the data use compliance is ensured. And the user interaction module is used for displaying and confirming protocol content and ensuring consensus of a data provider and a data demander. Once confirmed by the protocol, the data resource description will be delivered to the data demander through the AIAgent delivery engine. According to the invention, the data interaction and delivery efficiency is greatly improved, manual intervention is reduced, intelligent scheduling, development and utilization of data resources are realized, and data transaction circulation is effectively promoted.

The invention discloses a DevOps-based multi-choice component convenient deployment method, which comprises the following steps: interactively acquiring cluster configuration items from a user, including basic parameter configuration of a cluster and starting parameter configuration of cluster selectable components, to generate a main configuration file, analyzing the main configuration file to obtain an installation file for cluster deployment, executing the installation file, and executing the installation file for cluster deployment. A cluster environment and optional components are integrally and conveniently deployed; the method comprises the following steps of: configuring a trigger mechanism for a code warehouse, pushing an update code to the code warehouse by the developer, triggering an assembly line task of an automatic tool, performing automatic code compiling and mirror image construction on a selectable component code, and automatically pushing a mirror image to a mirror image warehouse by the developer; according to the method, mirror image updating of the selectable components is executed through an automatic tool to complete automatic deployment of the selectable components, so that the efficiency of cluster management and component updating deployment is improved, and the delivery efficiency and quality of a software system are improved.

The invention discloses an intelligent delivery targeted penetration decision-making method for precision marketing, particularly relates to the technical field of intelligent delivery targeted penetration decision-making, and comprehensively identifies potential anomalies through unified processing of a standardized index set and dynamic association construction of multi-level thresholds; by means of the constraint of a delivery strategy oscillation index on a delivery behavior, dynamic bidding, material optimization and flow distribution can be smoothly adjusted in a fluctuating environment, the controllability of budget consumption and the continuity of a delivery effect are ensured, and a multi-dimensional penetration strategy of competition, scenes, crowds and materials is combined, so that the delivery efficiency is improved. According to the method, high-value user groups are more accurately reached, the material matching degree is improved, the return on investment and the conversion rate are stably kept increased, oscillation and resource waste in the putting process are reduced, and the cross-platform collaborative optimization capability and the risk prevention and control level are improved.

The invention discloses a content delivery method and device, and the method comprises the steps: responding to an account creation request sent by a terminal web page, and creating an account based on the configuration information indicated by the request; a task creation request sent by a terminal web page is obtained, a delivery task is generated based on creation information indicated by the request, the terminal web page presents a task creation component, and after the task creation component is triggered, a task creation configuration page is presented, and task configuration information is received; a task creating request is generated based on the task configuration information, and the task configuration information comprises selected account number information selected from created account numbers, to-be-released content information and release recovery information. Through the configuration mode, one-key batch delivery of different media platform accounts is realized, and the defects of poor delivery efficiency and low delivery precision in related technologies are overcome.

The invention discloses an advertisement putting control method, an advertisement putting system, a storage medium and a program product, and the advertisement putting method comprises the steps: receiving a business district image uploaded by a user based on a user terminal node, and then determining a group portrait corresponding to the business district according to the business district image; and then one or more advertisements most adaptive to the group portrait are selected from the advertisement library according to the group portrait as target advertisements, and target advertisement putting device nodes in the business district are controlled to play the target advertisements, so that the purpose of accurately putting the advertisements is realized, and a plurality of decentralization processes are realized. In this way, the advertisement putting income in unit time is effectively improved, and advertisement putting is more accurate. Moreover, by implementing the above scheme based on the block chain, the purpose of decentration is better achieved, and the problem of low advertisement putting efficiency caused by artificial interference is effectively avoided.

The embodiment of the invention provides an article delivery system, method and device, computer equipment, a storage medium and a computer program product, and relates to the technical field of Internet of Things. The system comprises a main control module, an information acquisition module and an intelligent delivery module, the main control module, the information acquisition module and the intelligent delivery module communicate with one another through a wireless communication technology; wherein the information acquisition module is used for acquiring article delivery information of a target article and sending the article delivery information to the main control module; the main control module is used for acquiring delivery path information of the target article according to the article delivery information and sending the delivery path information to the intelligent delivery module; and the intelligent delivery module is used for delivering the target article to the delivery destination of the target article according to the delivery path information. According to the system, the article delivery efficiency is remarkably improved, the manual operation requirement is greatly reduced, the cost is effectively reduced, and the article delivery efficiency, safety and accuracy are improved.

The invention provides a multi-access linkage method and system based on take-out waybills and a storage medium. The method comprises the following steps: selecting to create temporary access permission two-dimensional code information while creating a take-out order based on a resident; an associated door lock management platform access address is obtained according to the resident delivery address, and a temporary request is sent to the door lock management platform access address; the door lock management platform creates temporary access permission two-dimensional code information according to the temporary request; according to the temporary access permission two-dimensional code information, determining that the current two-dimensional code type is a take-out access control type; generating a verification message; and the door lock management platform performs verification according to the verification message and feeds back the verification message to the access control management platform to determine whether to open the current access control. Compared with the prior art, when the resident carries out take-out transaction, the temporary access authority is automatically generated and provided for a take-out worker, the authorization problem of delivery access control in the final link of take-out is solved, and the take-out delivery efficiency is improved.

The invention discloses a public transportation auxiliary unmanned aerial vehicle cooperative distribution method considering client point dynamic demands, introduces a public transportation auxiliary unmanned aerial vehicle with large service range coverage to carry out express distribution, and aims to reduce the terminal logistics distribution cost and improve the distribution timeliness. The method comprises the following steps: constructing a generation model which simulates a dynamic customer demand and considers a time window in combination with an actual scene, and establishing a bus auxiliary unmanned aerial vehicle cooperative distribution optimization model which considers the customer point dynamic demand based on a customer point generation mechanism and a bus unmanned aerial vehicle cooperative operation mechanism in the generation model; and aiming at the established model, designing a dynamic information processing strategy based on bus departure time, and fusing the dynamic information processing strategy into an adaptive large neighborhood search framework for solving, thereby obtaining a heuristic algorithm suitable for solving a bus-assisted unmanned aerial vehicle cooperative distribution problem considering the dynamic demand of a client point. The distribution path can be dynamically planned according to the demand points generated at any time, the logistics delivery efficiency is improved, and the distribution cost is reduced.