27 results about "Delivery cost" patented technology

The invention relates to a multi-store distribution vehicle management method and system, a terminal and a medium, and relates to the field of logistics distribution, and the method comprises the steps: obtaining real-time data, the real-time data comprises store data, vehicle data and traffic data, the store data comprises order demands, inventory states and distribution customer priority information of all stores, and the vehicle data comprises the order demands, the inventory states and the distribution customer priority information of all the stores; the vehicle data comprises vehicle load and volume parameters, and the traffic data comprises road traffic conditions; constructing a data model based on the real-time data; based on the data model, a dispatching algorithm is adopted to generate a distribution plan, and the distribution plan comprises vehicle distribution and distribution paths; and pushing the distribution path to the distribution vehicle. The method has the advantages that the fresh goods can be delivered on time in a fresh-keeping manner, the use efficiency of the vehicle is improved, and the delivery cost is reduced.

The application provides a multi-objective robust optimization method, system, storage medium and electronic equipment for production task planning of a multi-agent collaborative platform, and relates to the technical field of production task planning of a multi-agent collaborative platform. First, according to the production task planning resources of the multi-agent collaborative platform and a single-batch overseas order, a production task planning model with a manufacturing enterprise agent as the core is constructed under the premise of determining the sea transportation time. Then, an infinity norm ball uncertain set is designed for the sea transportation time of a large ship, a robust quadratic multi-objective model for cross-regional multi-agent production task planning is constructed, and the total delivery time deviation and total delivery cost multi-objective of the single-batch overseas order are optimized. The model considers the sea transportation plan prepared in advance by a shipping company agent and the long and uncertain sea transportation time. In addition, the model is converted into an equivalent model, a two-stage hybrid heuristic algorithm is designed for solving, and a reasonable and feasible production task planning suggestion is given for the single-batch overseas order.

The invention relates to the technical field of unmanned logistics, and discloses an unmanned aerial vehicle and vehicle collaborative distribution method, system and device and a medium. The method comprises the following steps: obtaining to-be-delivered order data, unmanned aerial vehicle transport capacity data, vehicle transport capacity data and geographic space data of a delivery area, and constructing a unified collaborative management system comprising an order pool, a transport capacity pool and a connection network; based on a unified collaborative management system, a multi-vehicle and multi-unmanned aerial vehicle collaborative distribution problem considering distribution task completion mode selection and collaborative distribution feasibility constraints is converted into a global collaborative optimization model with the lowest total distribution cost; and solving the global collaborative optimization model to obtain an initial collaborative distribution strategy, and performing real-time adjustment on the initial collaborative distribution strategy based on a real-time operation state and dynamic event feedback in a collaborative distribution process to obtain a target collaborative distribution strategy. According to the invention, through unified collaborative management, global optimization and dynamic adjustment, efficient and low-cost collaborative distribution of the unmanned aerial vehicle and the vehicle is realized.

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.

Method and system of electric vehicle route planning for multi-service delivery and on-route energy replenishment is disclosed. Last mile delivery is a critical component of supply chains that impacts both customer experience and delivery cost. User request is received by a depot of a delivery environment. The user request comprising a current location of the user, one or more required services, and a time window rendered between each of the required services is processed and a graph is generated for the user request. Further, trained learning agent generates a route map indicating a plurality of waypoint locations for the electric vehicle to visit each node in accordance with minimized trip cost of fleet and time duration where each node has a state action pair for the electric vehicle. The learning agent learns continuously during the interaction with delivery environment and obtains feedback for every associated action.

The embodiment of the invention provides an advertisement putting early warning method and device, equipment and a storage medium, and the method comprises the steps: obtaining putting content information, an expected putting channel, an initial putting budget and an expected conversion amount of a to-be-put advertisement, determining at least one matched target historical delivery plan from a plurality of historical delivery plans according to the delivery content information and the expected delivery channel; according to the expected conversion amount, the historical conversion amount of the at least one target historical delivery plan and the historical delivery statistical amount, determining a predicted delivery statistical amount, and according to the historical delivery cost of the at least one target historical delivery plan, the historical delivery statistical amount and the predicted delivery statistical amount, calculating to obtain a predicted delivery cost; and judging whether the initial delivery budget and the predicted delivery cost meet set early warning conditions or not, and outputting early warning information under the condition that the early warning conditions are met. According to the scheme, early warning can be carried out on the initial delivery budget, and large budget deviation in the actual application process is avoided.

The invention discloses an activity delivery budget updating method and device, equipment and a storage medium. The method comprises the steps of obtaining user active data of candidate users, screening a target user from the candidate users according to the user active data, and determining an activity putting budget based on the target user; putting activity data to the target user, and when callback information corresponding to the activity data is received, determining the putting cost of the activity data based on the callback information; and obtaining a plurality of activity subjects corresponding to the activity data, determining an apportionment proportion corresponding to each activity subject, and updating an activity delivery budget of each activity subject according to the delivery cost and the apportionment proportion. According to the scheme, by introducing a data screening and dynamic callback cost feedback mechanism based on the user activeness, refined management and real-time updating of the activity putting budget are realized.

The application provides an advertisement delivery method and device, electronic equipment and storage medium, wherein the delivery cost and the number of click events of each media in the historical round are obtained; the remaining allocation number and the delivery cost of each media are used to determine the cost to be consumed; the relationship between the remaining cost of the advertisement delivery and the cost to be consumed is used as a constraint, the total amount of the remaining allocation number of each media is used as a target, and the remaining allocation number of each media is determined; the advertisement delivery in the current round is performed according to the remaining allocation number of each media, the current round is taken as the historical round, the delivery cost and the number of click events of each media are updated, and the advertisement delivery in the next round is performed. The method, device, electronic equipment and storage medium provided by the application accumulate the real advertisement delivery data of each media by performing the advertisement delivery on each media in multiple rounds, so that the advertisement delivery effect is gradually optimized with the iteration of rounds, and the advertisement delivery on each media can be more accurately predicted.

The utility model provides a device capable of sensing commodity state changes. The device comprises a device body, a sensing switch and a circuit board. An inductive switch and a circuit board are arranged on the device main body, and the inductive switch is electrically connected with the circuit board; an area, corresponding to the inductive switch, in the device body is provided with an interface used for sleeving a commodity, so that when the interface is sleeved with the commodity, the inductive switch is closed. When the interface is separated from the commodity, the inductive switch is switched off; and a signal transmission module is arranged in the circuit board. According to the application, automatic monitoring of commodity distribution and use is realized through the inductive switch and the circuit board with the built-in signal transmission module. Through the state change of the inductive switch, the circuit board can detect the installation and removal of the device, and the related information is reported to the server through the signal transmission module, so that the server confirms the delivery and use state of the commodity, and automatically generates a new delivery order, thereby improving the commodity management efficiency, reducing the delivery cost, reducing the manual intervention, and improving the user experience. And user experience is improved.

The application discloses an intelligent manufacturing scheduling method and device, electronic equipment and medium. Through the application of the technical solution, the total cost including product processing cost, overtime cost of employees, product delay delivery cost, and product inventory cost is taken as the optimization target. And combined with the deep reinforcement learning algorithm, the scheduling plan corresponding to the order information is output at the lowest cost. Thus, on the one hand, the production manufacturer can automatically give a scheduling scheme within a period of time in real time. On the other hand, the scheduling scheme is not accurate due to the problem that the employee production cost in the production process is not considered in the related art.

The invention belongs to the field of medicine logistics transportation, and particularly relates to a logistics transportation service intelligent decision-making method, which comprises the steps of S1, acquiring industry constraint information of a to-be-delivered medicine order; s2, dynamically determining a decision strategy suitable for the current order based on the industry constraint information, the decision strategy defining a quantitative trade-off relationship among cost, service quality compliance and operation risk; s3, performing multi-target comprehensive evaluation on a plurality of candidate logistics service providers according to the decision strategy, and generating a comprehensive evaluation result fusing predicted distribution cost and historical compliance risk performance of the logistics service providers; s4, according to the comprehensive evaluation result, selecting a logistics service provider to execute order delivery; and S5, based on actual delivery result data fed back after the selected logistics service provider executes the order, performing optimization iteration on the decision strategy determination logic in the step S2.

This disclosure provides a method, apparatus, electronic device, and storage medium for configuring an item warehouse. The method includes: determining the item warehouse configuration target and constraints during the item warehouse configuration process; determining the target item categories involved in the item warehouse configuration process; determining the target item delivery cost corresponding to the target item categories during the item warehouse configuration process; and determining item warehouse configuration information based on the item warehouse configuration target, the item warehouse configuration constraints, and the target item delivery cost. This application's technical solution enables item warehouse deployment optimization at the item level within a multimodal item warehouse network structure.

This invention relates to the field of intelligent manufacturing logistics technology, specifically a dynamic periodic material delivery scheduling system based on an automotive assembly line. The system includes: a data acquisition module that acquires real-time information on material consumption and warehouse inventory status at production workstations; a demand forecasting module that predicts the material demand sequence for each workstation within a future cycle, including precise demand time windows; a constraint management module that integrates constraints such as vehicle capacity, material attributes, and channel rules; and an optimization modeling module that constructs a multi-objective optimization model based on the demand sequence and constraints, aiming to minimize the total travel distance and satisfy all time windows. A scheduling generation module solves this model to generate a dynamic delivery plan including vehicle departure time, loading list, delivery route, and estimated arrival time. This invention achieves accurate dynamic forecasting of material demand and multi-objective collaborative optimization of delivery cost and timeliness.

The invention provides a cloud computing scene-oriented software product delivery method and device and electronic equipment, and relates to the technical field of computers, in particular to the technical fields of cloud computing, software delivery and the like. The specific implementation scheme comprises the steps of obtaining a product delivery list; wherein the product delivery list is used for indicating a target software product to be delivered; generating a function white list of the target software product; wherein the function white list is used for indicating to-be-delivered functions of the target software product; generating a product delivery instruction based on the product delivery list and the function white list; sending the product delivery indication to a product server; wherein the product server is used for delivering the target software product based on the product delivery instruction. By adopting the method, the delivery cost of software products can be reduced, and meanwhile, the flexibility, the automation level and the efficiency of the delivery process are improved.

A system and method for optimizing delivery of data over hybrid networks by generating delivery plans derived from a delivery schedule and optimizing delivery timing, delivery method, and network selection based on data priority, caching availability, delivery cost, and destination reach.

This invention discloses an integrated intelligent warehousing and distribution logistics management system, comprising: an intelligent warehousing module, a warehousing collaboration module, an intelligent distribution management module, a data analysis module, a decision support module, and a system management module. The intelligent warehousing collaboration module generates picking tasks based on orders and dynamically schedules AGVs to complete goods handling. The collaboration module maps the status of goods, equipment locations, and operational processes within the physical warehouse in real time. This invention has the following advantages: dynamic location allocation improves warehouse space utilization, shortens AGV task response time, predictive maintenance reduces equipment failure rates, unmanned delivery reduces last-mile delivery costs, knowledge graphs and AI algorithms automate routine problem handling, digital twins and large-screen visualization systems provide transparent management throughout the entire process, intelligent warehousing management enables rapid storage and retrieval of goods and accurate picking, and intelligent distribution management optimizes vehicle scheduling and route planning.

To provide a product sales method that can reduce product delivery costs and product prices, and a system for achieving the product sales method.SOLUTION: This sales method includes: (1) receiving, from a user terminal of a user using at least one facility, an order / payment signal for ordering products placed in a storage unit at a server connected in communication with a storage unit placed in a space set up within the at least one facility where security against intrusion by unspecified persons is ensured; (2) after receiving the order / payment signal, transmitting an authentication code for unlocking the storage unit from the server to the user terminal; and (3) reading the authentication code with a reader provided in the storage unit or a reader connected in communication with the storage unit.SELECTED DRAWING: Figure 3

This invention provides a route optimization method for truck-drone collaborative delivery in rural areas. It relates to the field of route planning technology. The method includes: constructing a delivery network comprising delivery centers, ground delivery points, and flight delivery points; dividing customer nodes into multiple delivery clusters; selecting a cluster center for each cluster as the truck's stopping point and the drone's take-off and landing starting point; establishing an integer programming model with the objective of minimizing delivery costs and waiting time costs; solving the integer programming model using a two-layer interactive optimization algorithm; dynamically determining the optimal connection point between the truck's next stopping point and the drone's current path using the golden section method, minimizing the time difference between the truck and the drone reaching that point; and outputting the optimal collaborative delivery route for the truck and drone, including the truck's driving path, the drone's flight path, and the location information of each dynamically connected point.

Embodiments of the present application provide a software deployment management method and device, computer equipment and a storage medium, wherein the method comprises: sending a management authorization request to a second device to request the second device to authorize a first device to use a management service to manage distributed deployment of a software tool package; wherein the management authorization request is generated according to hardware information of the first device; receiving authorization credential information returned by the second device, the authorization credential information being generated by the second device after verifying that the first device has the qualification to use the management service according to the management authorization request; initializing the management service based on the authorization credential information, and after successfully initializing the management service, in response to a registration request sent by any node device that intends to use the software tool package, calling the management service to manage deployment of the software tool package for the corresponding node device; the efficiency of deployment management for the software tool package can be improved, and the delivery cost can be reduced.

This invention discloses a method and system for scheduling urban last-mile delivery based on multi-agent reinforcement learning, belonging to the field of intelligent logistics technology. The method acquires delivery orders and global state information, generates a global state vector through a global state perception module, generates policy parameters for each delivery agent through a multi-agent policy generation module based on a dynamic value decomposition network, allocates orders and schedules resources based on a Nash equilibrium mechanism through a competitive and cooperative scheduling module, and after executing the delivery task, feeds back the reward value to the policy generation module through an execution feedback optimization module using a Nash social welfare-based reward allocation mechanism to form a closed-loop optimization. This invention achieves coordinated scheduling and complementary advantages of three types of delivery resources: drones, delivery personnel, and smart parcel lockers, significantly improving delivery efficiency and customer satisfaction while reducing delivery costs.

To provide a product sales method that can reduce product delivery costs and product prices, and a system for achieving the product sales method.SOLUTION: This sales method includes: (1) receiving, from a user terminal of a user using at least one facility, an order / payment signal for ordering products placed in a storage unit at a server connected in communication with a storage unit placed in a space set up within the at least one facility where security against intrusion by unspecified persons is ensured; (2) after receiving the order / payment signal, transmitting an authentication code for unlocking the storage unit from the server to the user terminal; and (3) reading the authentication code with a reader provided in the storage unit or a reader connected in communication with the storage unit.SELECTED DRAWING: Figure 3

The invention relates to the technical field of building design, and discloses a delivery method and equipment of an air conditioning system, a medium and a program product. The method comprises the steps that all air conditioning equipment object instances and relation instances among all the air conditioning equipment object instances are obtained; obtaining each first target cold source equipment object instance in each air conditioning equipment object instance, and searching each associated equipment object instance in each air conditioning equipment object instance based on a preset delivery rule according to each first target cold source equipment object instance and a relation instance between the air conditioning equipment object instances; and according to the first target cold source equipment object instances and the associated equipment object instances, central air conditioner cooling whole system object instances are generated. The automatic digital delivery of the air conditioning system can be realized, and the delivery quality can be ensured while the delivery efficiency is improved and the delivery cost is reduced.

This application provides a collaborative scheduling method and related equipment for bus-assisted drone logistics, belonging to the fields of low-altitude economy and smart logistics technology. The method includes: acquiring delivery task information, bus route information, and bus speed adjustment pricing information; constructing an optimization model with the objective of minimizing total delivery cost, and jointly optimizing the bus's operating speed between stations with the drone delivery plan; controlling the bus to operate at the optimal speed based on the optimization results and guiding the drone to perform delivery tasks. The total delivery cost includes drone energy consumption cost, bus speed adjustment cost, and customer waiting time cost. This application achieves deep collaboration between the public transportation system and the logistics delivery system, significantly reducing drone waiting time, lowering total delivery cost, and improving the efficiency of public resource utilization, possessing extremely high practical application value.

The application discloses a single-quantity balancing dispatching method in a crowd-sourced instant logistics scene. When a new order is generated, a nearby delivery personnel set is first screened according to the spatial position of the order, then the delivery cost of each delivery personnel in the set for delivering the order is calculated through path inference of the new order and the delivery personnel set, then K delivery personnel with the minimum delivery cost are selected for pre-dispatching, the delivery balancing score of the K delivery personnel is calculated and sorted, the first order in the pre-dispatching list of the delivery personnel with the highest score is selected for dispatching decision, and the pre-dispatching list of other delivery personnel including the order is updated until the distribution of all new orders is completed. The method guarantees the system efficiency and service quality to a certain extent, alleviates the contradiction between the single quantity and the transport capacity resources, realizes the stability and continuity of the order quantity of different delivery personnel individuals and different time periods, and is beneficial to the improvement of the entire platform ecology.

To provide a card seal that maintains security, reduces resource consumption, and lowers delivery costs. [Solution] The card seal 1 comprises a temporary card fixing piece 11 on which the card C is temporarily fixed, a covering piece 12 connected to the temporary card fixing piece 11 via a first fold line L1 and covering the card C, and a first joining portion 20 provided on at least a part of the outer circumference of the first sealing region S1 formed when the temporary card fixing piece 11 and the covering piece 12 face each other, and joining the temporary card fixing piece 11 and the covering piece 12.

An AI-enhanced computerized e-commerce system, optimized for smaller merchants such as florists who often provide seasonal perishable gifts that require local delivery, and who often desire to form cooperative networks with local merchants offering related gift services, as well as other related merchants such as other florists in more distant locations. The web server-based system, further assisted by generative AI systems and methods, allows merchants to easily set up non-static (time variable) websites that automatically provide schedule driven promotions. New products can be quickly uploaded from smartphones, and sophisticated time and location aware algorithms can compute accurate delivery costs and make such costs transparent to customers. The system may also include backend software configured to assist in product production, inventory control, product cost optimization, product delivery optimization, management, and tracking. The generative AI techniques allow for improved customization and response to unexpected contingencies.

The invention discloses a logistics intelligent distribution method and system based on data analysis, and relates to the technical field of logistics distribution. A product distribution area is divided into a grid map; carrying out attribute assignment on each grid in the grid map; based on the vehicle capacity constraint and the product demand time constraint, establishing a target function by taking minimization of the delivery cost as a target; extracting parameters related to the target function from the grid map and mapping the parameters to the target function; a population is initialized, each particle in the population represents a distribution scheme, and a corresponding distribution path is recorded in the distribution scheme; the distribution cost is used as a fitness value, and the fitness value of each particle is calculated; iteratively updating the speed and the position of each particle, and recalculating the fitness value of each particle after iteration updating; and when an iteration stop condition is met, taking the distribution scheme corresponding to the particle with the lowest fitness value as a final distribution scheme. According to the invention, the distribution of a large number of distribution point products can be completed in time with low distribution cost.