229 results about "Delivery efficiency" patented technology

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 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 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 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 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 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.

The invention discloses an intelligent logistics order scheduling method and system, and the method comprises the steps: obtaining a parameter set, the parameter set comprises solid state parameters and dynamic parameters, the solid state parameters are inherent attribute parameters of each order in a to-be-scheduled order queue, and the dynamic parameters are parameters determined according to the dynamic changes of the order queue and an external environment; obtaining a plurality of weight coefficients, wherein the weight coefficient is an importance degree value preset for each parameter; according to the parameter set and the weight coefficient of each parameter, calculating a scheduling priority weight value corresponding to each order through a preset weighting algorithm; ordering the orders in the order queue to be scheduled according to the calculated scheduling priority weight value; and allocating appropriate deliverymen to the orders according to the sequenced order and generating a scheduling instruction. According to the invention, the problems of single logistics order scheduling strategy and difficulty in adapting to real-time dynamic change scenes in the prior art are solved. The distribution efficiency and the resource utilization rate can be improved.

The invention discloses a marketing mobile terminal safety monitoring and dynamic response method and system, belongs to the technical field of information monitoring response, and aims to solve the problems of audience positioning fuzziness, data fragmentation, delivery strategy rigidity, safety risk control difficulty and the like in traditional information touch. The method comprises the steps that potential audience features are positioned, a target population feature system is constructed, and a terminal label is matched to delimit a delivery range; collecting terminal user behavior data in a delivery range, extracting features, dividing information categories, and constructing a multi-dimensional target information database; clustering features to generate a differentiated putting strategy, updating data and re-classifying, and dividing and subdividing a scene to construct a behavior baseline; removing abnormal terminals based on baseline recognition, constructing a category transfer path map, evaluating a strategy effect and judging whether putting is terminated or not according to a standard; according to the invention, the precision, safety and dynamic adaptation of information touch delivery are realized, and the delivery efficiency and effect are remarkably improved.

To improve delivery efficiency.SOLUTION: An information processing apparatus 20 includes: a communication unit 23 for performing communication with a terminal device 30 of delivery staff; and a control unit 21 for acquiring nameplate information concerning a delivery destination and sending the acquired nameplate information to the terminal device 30 via the communication unit 23.SELECTED DRAWING: Figure 1

The invention belongs to the field of intelligent traffic systems and green logistics energy management, and provides a method for optimizing an energy path of an electric vehicle logistics fleet under dynamic traffic, which comprises the following steps of: defining an energy path optimization problem of the electric vehicle logistics fleet under a dynamic traffic environment, the coupling influence of multiple factors such as traffic jam, energy consumption and charging is considered, and a corresponding mathematical model is constructed. And then, designing an optimization framework based on simulation DeepSeek style reasoning, and combining various advanced reasoning mechanisms, such as thinking tree, self-consistency and multi-agent dialogue, to realize dynamic collaborative optimization of charging and paths in the motorcade. And finally, a closed-loop optimization method is provided, and optimal allocation of energy and time is realized by simulating DeepSeek energy decision and later optimization refinement. According to the method, the energy consumption of the motorcade under dynamic traffic can be effectively reduced, and the distribution efficiency is improved.

The invention relates to the field of logistics transportation management, and particularly discloses a visual TMS logistics transportation management system and method, which takes deliverymen, clients and delivery points as transportation network nodes, constructs a dynamic topology based on predicted driving time among the nodes, and provides a visual TMS logistics transportation management system. Deep context association perception is carried out on attribute information such as geographic coordinates and time windows of all transportation network nodes by using a graph convolutional neural network, so that the optimal path connection probability between every two nodes is predicted on the basis, and an adjacent probability matrix between the nodes is generated; and based on a maximum adjacency probability selection principle and an access logic verification mechanism of first delivery and second delivery, determining a transportation route planning result according with business logic, and performing visual display. According to the method, rigid constraints of actual business rules and operation processes can be met, effective delivery decision support is provided for managers and deliverymen, and the intelligent level and delivery efficiency of logistics transportation are remarkably improved.

The invention relates to the technical field of bearing sales, in particular to an MES-based bearing sales management system, which comprises a sales management module, a warehouse management module, a stock management module, a statistical report module and a building and repairing cooperation module, and is characterized in that a real-time linkage mechanism is established, and the delivery efficiency is improved; the core problem of order and inventory disjunction is solved, on-demand, accurate and automatic stock-up instruction generation is realized, the repair and manufacturing precision of bearing overhaul and the product consistency are effectively improved, and the operation safety of client key components is guaranteed.

The invention discloses an application version release time consumption prediction method and apparatus, a device and a storage medium. The method comprises the steps of obtaining version information of a target application version; for each release link, determining a plurality of time consumption influence factors based on a target time consumption prediction model corresponding to the release link; based on the version information, determining factor values respectively corresponding to the plurality of time consumption influence factors; through a target time consumption prediction model, the release time consumption is predicted based on the factor value, and the release time consumption represents the manual time consumption for releasing the application version; the target time consumption prediction model is obtained based on the historical version release time consumption of the plurality of application versions in the release link and the plurality of time consumption influence factors through fitting. According to the embodiment of the invention, quantitative traceability of time consumption influence corresponding to a plurality of links can be realized, the accuracy of predicting release time consumption is improved, the actual optimization of an application version release process is guided, the delivery quality and the delivery efficiency of the application version are improved, and the optimal control of the operation cost is realized.

The application provides a reservation type belt warehouse system, which comprises a warehouse device for storing a cargo carrier, a warehousing device for conveying and hanging the cargo carrier into the warehouse device, a delivery device for outputting the cargo carrier stored in the warehouse device, and a warehouse adjusting device for transferring and adjusting the cargo carrier stored in the warehouse device; the warehouse device has a storage type warehouse device and a reservation type warehouse device, the warehouse adjusting device has a cross-warehouse adjusting device for transporting the cargo carrier between the storage type warehouse device and the reservation type warehouse device, and the delivery device is arranged on the reservation type warehouse device. According to the reservation type belt warehouse system, the user can transfer and adjust the recently needed cargo from the storage type warehouse device to the reservation type warehouse device in advance through the warehouse adjusting device, so that the cargo is close to the delivery device, and the delivery efficiency is greatly improved.

Disclosed in the present application are a group-buy data processing method and apparatus, and an electronic device. The group-buy data processing method comprises: displaying group-buy objects having selectable delivery modes; in response to a first user initiating a target group buy for a target object among the group-buy objects, requesting stock keeping unit information of the target object from a service terminal, displaying the selectable delivery modes of the target object, and determining data of an order to be placed of the first user; in response to a target delivery mode among the selectable delivery modes being selected, updating, on the basis of the target delivery mode, a stock keeping unit of the data of the order to be placed; and in response to an order confirmation instruction for the data of the order to be placed, triggering the generation, based on the updated stock keeping unit, of an order of the first user as a first order of the target group buy, the first order comprising information of the target delivery mode. The method solves the problem of how to improve the delivery efficiency of existing group-buy solutions.

The invention discloses a method and a system for publishing and distributing information service, which realize full-process automatic management of application from developer submission and auditing to access party online through unified application uploading, mirror image construction, isolation environment auditing and multi-dimensional automatic verification. The system supports multi-tenant isolated deployment, and a built-in review rule engine completes compatibility, safety and functional verification; realizing cross-environment adaptation based on the standardized container mirror image and the reusable application assets; and dynamic resource scheduling and alarm rollback are supported through a multi-level elastic capacity expansion and contraction and abnormal instance processing mechanism. According to the method and the system, application version multiplexing and operation state visual monitoring can be realized, the delivery efficiency is improved, the operation and maintenance cost is reduced, and the cluster resource utilization rate and the system stability are improved.

The invention provides a request processing method and device, and the method comprises the steps: responding to a received current code merging request associated with a target branch, and obtaining the states of a plurality of code merging entrance guards associated with the current code merging request; on the basis of the weight and the state corresponding to each code merging entrance guard, determining a merging readiness score of the current code merging request; in response to the fact that the merging readiness score is smaller than a set score threshold value, determining a target access control with the maximum weight from at least one unpassed code merging access control; according to the access control failure log associated with the target access control and the first incremental code difference between the source branch and the target branch associated with the current code merging request, merging blocking information is generated and visually displayed, and therefore the automation and intelligence level of the code merging process is improved, and the code merging efficiency is improved. And the problem repairing period is shortened, so that the stability and delivery efficiency of the target branch are improved.

The application discloses a kind of risk data management systems for cross-border supply chain, belong to risk data management technical field, including raw material procurement management module, product warehousing management module, international logistics transportation management module, domestic warehousing management module, domestic distribution management module, comprehensive data management module.The multiple management modules of the present application are set, the information in cross-border supply chain can be managed in a hierarchical comprehensive, the security of information is guaranteed;And by presetting frequency identification graphics on the outer packaging of product, the product's shipment priority level information can be obtained through subsequent identification, and a more reasonable cargo cell unit is determined according to the product's shipment priority level information to store the product, which greatly reduces the delivery time when delivering, improves the delivery efficiency, to some extent, also reduces the warehousing cost, and also improves the user experience.

The invention provides a take-out order scheduling method and system, a storage medium and a program product, and relates to the field of personnel or project management, and the method comprises the steps: generating a path network according to the coordinates of a pickup point and a delivery point of a new order; determining a group of geographic grid indexes covering the path network based on a preset grid cell size to obtain a new order path index set; calculating an intersection index set of the new order path index set and the future path index total set of the candidate rider; and when the number of the unique identifiers of the geographic grid indexes in the intersection index set exceeds a preset path matching threshold value, adding the new order into the order sequence of the target candidate rider with the highest comprehensive score, and adjusting the planned path corresponding to the target candidate rider to complete the scheduling of the new order. By implementing the method, the problem of misjudgment of the smoothness caused by path simplification can be relieved, and the matching accuracy of the order and the rider is improved, so that the overall delivery efficiency is improved.

The invention discloses a causal evaluation method for advertisement putting. The method comprises the following steps: acquiring a plurality of data sets of advertisements put on a take-out platform by merchants operating on the take-out platform; inputting the plurality of data sets into a causal graph mining model set to obtain a first candidate causal graph set; filtering the first candidate causal graph set based on an expert knowledge base to obtain a second candidate causal graph set; obtaining the weight of the path according to the relationship between the node and the path of each second candidate causal graph in the second candidate causal graph set, and aggregating the plurality of second candidate causal graphs based on the weight of the path to obtain a causal assessment large graph; and based on the causal evaluation large graph, evaluating the causal relationship between the advertising parameters and the effect indexes of the merchant advertising. According to the method, the accuracy of advertisement effect evaluation can be improved through accurate causal relationship analysis, the advertisement putting efficiency can be improved, and the putting strategy can be optimized.

The invention discloses a system for quantitatively and automatically distributing screws and gaskets according to process requirements. The system comprises a plurality of sets of tray groups; the on-line caching station is a starting station and is used for placing and conveying an empty tray group; the tray disassembling station is used for sequentially disassembling the empty tray group into single trays; the automatic distribution station is used for distributing gaskets and screws to the trays according to the read two-dimensional code information on the trays; the tray stacking station is used for sequentially stacking the distributed single trays into a tray group; the offline temporary storage station is used for conveying the tray group completing the distribution task; and the main controller is electrically connected with the stations and is used for inputting distribution task information and controlling execution of distribution tasks. The tray is adopted to distribute the screws and the gaskets, the screws and the gaskets can be quantitatively and automatically distributed to the matrix sequence round holes of the tray according to process requirements, and the distribution efficiency and accuracy are greatly improved. The invention further discloses a method for quantitatively and automatically distributing the screws and the gaskets according to the process requirements.

The invention relates to the field of logistics, and discloses a logistics order dispatch monitoring method, device and equipment and a storage medium, and the method is used for carrying out dispatch monitoring on a logistics order to improve logistics dispatch efficiency and satisfaction. The method comprises the following steps: acquiring basic information, dynamic signing data and external environment data of a logistics order, and converting the basic information, the dynamic signing data and the external environment data into structured data; calculating the contribution degree score of each feature in the structured data to delay prediction, and screening out the features with the top 80% of the contribution degree scores as prediction features; inputting the prediction features into a pre-trained delay rate prediction model, calculating the delay rate of the logistics order, and matching the early warning level of the logistics order according to the delay rate; a receiver demand is obtained, and a processing scheme is generated in combination with the receiver demand, the early warning level and the structured data; and generating a visual early warning prompt according to the processing scheme, and synchronizing the visual early warning prompt to the logistics management platform, the courier mobile terminal and the receiver applet.

The invention provides an unmanned distribution vehicle with an automatic loading and unloading function, and relates to the technical field of intelligent logistics. The unmanned distribution vehicle comprises an automatic driving vehicle, a fork lifting device, a fork translation device and a cargo cage supporting device, the automatic driving vehicle comprises a vehicle frame and a cargo compartment arranged on the vehicle frame, a compartment opening communicated with the interior is formed in the end face, away from a vehicle head, of the cargo compartment, and the fork lifting device is arranged on the vehicle frame and located below the compartment opening; the pallet fork translation device and the cargo cage supporting device are both arranged in the cargo compartment, the cargo cage supporting device is provided with two cargo cage supporting assemblies which are opposite in the width direction of the cargo compartment and are spaced from each other, and the pallet fork translation device is located between the two cargo cage supporting assemblies; wherein the cargo cage is lifted through the pallet fork lifting device, the cargo cage is moved into / out of the cargo compartment through the pallet fork translation device, and the cargo cage is supported through the two cargo cage supporting assemblies. On the basis, automatic loading and unloading of the cargo cages are achieved, the labor intensity of workers is low, and the distribution efficiency and safety are higher.

The invention discloses a dynamic task priority scheduling method and system for flexible production, and belongs to the technical field of machine learning and intelligent manufacturing. The method comprises the following steps: collecting equipment state and load data in real time; constructing a weight adjustable optimization objective function of the production efficiency, the resource utilization rate and the delivery date satisfaction rate; generating an initial task priority sequence through a clustering algorithm based on the equipment abnormal characteristics, the task urgency degree and the load data; the priority weight is dynamically adjusted by simulating the environment temperature change; when an equipment fault occurs, the task is redistributed to the standby equipment; and calculating a resource scheduling scheme by adopting a particle swarm optimization algorithm and taking a task priority as a particle position. According to the invention, through multi-dimensional dynamic weight adjustment and real-time fault response, the resource utilization rate of the production line, the order delivery efficiency and the flexible response capability are effectively improved.

The application discloses a device information delivery method and device, equipment and storage medium. Based on the current area, the target device type is acquired, the alternative delivery space and the delivery form list are determined according to the target device type; the target delivery space and the target delivery form are determined based on the alternative delivery space and the delivery form list, wherein the target delivery form includes the coordinate delivery form and the non-coordinate delivery form; when the target delivery form is the non-coordinate delivery form, the device information delivery is carried out according to the target delivery form. The target delivery space and form are determined through the alternative delivery space and the delivery form list, different methods are adopted for different user requirements, the user requirements without the requirements for the device style and the accurate position are solved, the delivery is more in line with the actual situation and the requirements, and the efficiency and the quality of the delivery are improved. Through the digital delivery of the device information, the artificial workload is reduced, the on-site delivery efficiency is improved, and the delivery cost is reduced.

The invention discloses a robot material delivery control method and device, electronic equipment and a storage medium, relates to the technical field of robot control, can be applied to financial science and technology and medical health business scenarios, and comprises the following steps: determining key feature parameters and material categories of a target material; according to the key feature parameters, the material types and physical parameters of a robot grabbing device, grabbing action parameters and delivery action parameters matched with the target material are determined; planning a moving path from a material delivery starting point to a target point based on the dynamic environment information of the service scene; and the robot is controlled to execute material delivery operation according to the moving path based on the grabbing action parameters and the delivery action parameters, and in the material delivery operation execution process, the delivery action parameters and the moving path are adjusted based on the material posture and the dynamic environment change of the service scene till delivery of the target material is completed. The delivery efficiency and delivery safety of robot material delivery can be improved.

The application relates to the technical field of intelligent robots, and provides a service type water delivery robot, which comprises a universal chassis and a delivery support, the delivery support is arranged on the universal chassis, one side of the delivery support is provided with a touch screen and a visual identification module; the delivery support is further provided with a top plate and a water storage layer, the top plate is arranged above the delivery support, and the water storage layer is provided with a plurality of placing barrels which are arranged in an inclined mode and face the outer side of the delivery support. Based on this, the problem of jolting of bottled water during delivery can be solved, the delivery efficiency is improved, and the user experience is improved.

The invention relates to the technical field of express delivery signing methods, and discloses a signing optimization method based on multi-dimensional intelligent recommendation. Comprising the following steps: acquiring historical signing record information and real-time data information; extracting address feature information, sign-in place feature information and time feature information, dynamically adjusting the weight according to a scene by adopting a weighted scoring mechanism, predicting an optimal sign-in place by adopting XGBoost, and outputting a recommended sign-in place list and confidence; receiving a sign-in application, automatically matching a receiving address, generating a sign-in address recommendation list if a historical association sign-in address exists in the address, taking the historical association sign-in address as initial recommendation, directly generating a sign-in address candidate list if no historical record exists, and sending the sign-in address candidate list or the sign-in address recommendation list to a user side; receiving sign-in address confirmation information, and completing sign-in; the method has the advantage of improving the express delivery efficiency.