Logistics distribution management method and device, equipment and medium

Abstract

The invention relates to a logistics distribution management method and device, equipment and a medium, and the method comprises the steps: extracting an initial weight feature in customer ordering information, carrying out the matching of a corresponding first optimal distribution path based on an established intelligent matching model, and generating a visual path corresponding to the optimal distribution path; extracting identity features in the order placing information of the customer, customizing and automatically printing an initial delivery label, and updating a current delivery point location on a visual path in real time; dynamic weight features are obtained in real time in the user front-end application, a second optimal delivery path is matched according to the dynamic weight features, or automatic printing of a delivery optimization label is executed on a delivery point location next to the current delivery point location in the first optimal delivery path, and an optimal delivery path is automatically matched through an intelligent matching model. The distribution efficiency is improved, and the distribution plan is adjusted by extracting the dynamic weight features. It is possible to ensure smooth delivery even when an external environment changes.

Description

Technical Field

[0001] The present invention relates to the technical field of logistics distribution management, and in particular to a logistics distribution management method, device, equipment and medium. Background Art

[0002] At present, in the jewelry industry, logistics management is the key link to ensure the efficient and accurate flow of goods from suppliers to customers. The jewelry industry has particularly high requirements for logistics, because jewelry products are usually of high value and have strict requirements on the accuracy and safety of distribution. However, traditional logistics management methods generally have problems such as low distribution efficiency, high error rate, and opaque logistics progress of customer orders, which makes it difficult to meet the jewelry industry's needs for efficient, safe and accurate distribution. These problems not only affect the quality of logistics distribution, but also lead to information asymmetry and delivery delays in the supply chain, increase operating costs, and affect customer satisfaction; In order to address these pain points, the jewelry industry urgently needs an efficient and intelligent logistics management system to improve delivery efficiency, reduce error rates and enhance customer experience. Traditional logistics management methods lack intelligent route planning and flexible delivery solutions, and cannot track and adjust delivery routes in real time, resulting in the inability to fully utilize existing resources in a complex logistics environment. In addition, under the traditional model, logistics progress often lacks transparency, and customers cannot understand logistics information in real time, causing unnecessary anxiety and dissatisfaction. Summary of the invention

[0003] In order to solve the problems of low delivery efficiency, high error rate and opaque logistics progress of customer orders commonly existing in traditional logistics management methods, the present application provides a logistics delivery management method, device, equipment and medium.

[0004] The above-mentioned invention objective of the present application is achieved through the following technical solutions: A logistics distribution management method, the logistics distribution management method comprising: Obtain customer order information and match the corresponding outbound goods in the established inbound warehouse management system; Extract the initial weight features in the customer order information, and based on the established intelligent matching model, match the corresponding first optimal delivery path according to the initial weight features, where the first optimal delivery path at least includes a first mailing path and a first self-pickup path, and generate a visual path corresponding to the optimal delivery path in the user front-end application; Extracting identity features from the customer order information, and customizing and automatically printing an initial delivery label based on the identity features and the initial weight features, wherein the initial delivery label is used to be affixed to the outbound goods; Tracking the transfer information of the initial delivery label in real time, and updating the current delivery point on the visualized path in real time according to the transfer information; Dynamic weight features are acquired in real time in the user front-end application, and a second optimal delivery path is matched according to the dynamic weight features, or automatic printing of a delivery optimization label is performed at the next delivery point of the current delivery point in the first optimal delivery path, wherein the second optimal delivery path includes at least a second mailing path and a second self-pickup path.

[0005] By adopting the above technical solutions, by obtaining customer order information and matching the corresponding outbound goods in combination with the warehouse management system, the need for manual operation is reduced, and the outbound process can be accurately automated. Through the intelligent matching model, the system can automatically match the optimal delivery path according to the initial weight characteristics (such as order urgency, customer demand, logistics resources, etc.). This intelligent delivery path planning can fully consider the adaptability of different delivery methods, thereby greatly improving the delivery efficiency and effectively reducing the probability of human errors; this problem is solved by generating a visual path corresponding to the optimal delivery path in the user front-end application. Customers can view the logistics status in real time and track the progress of delivery at any time. This transparency not only improves the customer experience, but also provides more data support for logistics management, which can timely identify and correct any potential delivery deviations; in the traditional logistics process, path planning is often static and difficult to cope with changes in the delivery process, such as traffic congestion, sudden weather changes or other unforeseen factors. By extracting dynamic weight features (for example, traffic conditions, order changes, customer feedback, etc.), the delivery path is updated in real time according to these changes, and the delivery optimization label can be automatically printed to further adjust the delivery plan. By acquiring these dynamic features in real time and adjusting the delivery plan accordingly, it is possible to ensure that delivery can proceed smoothly even when the external environment changes, thus avoiding delays and delivery errors that are common in traditional models.

[0006] In a preferred example, the present application may be further configured as follows: the step of matching the corresponding first optimal delivery path according to the initial weight feature based on the established intelligent matching model includes: Classifying the initial weight features to generate corresponding classification packages; Based on the established intelligent matching model, assigning values ​​to each of the classification packages to obtain a first weight value of each of the classification packages; According to the classification package, a corresponding current delivery path is matched, and a path load rate of the current delivery path is determined in real time; Determining a corresponding weight load rate according to a sum of the first weight values ​​of each of the classification packets; According to the comparison result of the path load rate and the weight load rate, a corresponding first optimal delivery path is determined.

[0007] By adopting the above technical solution, it is possible to effectively match customer needs with the characteristics of the delivery path by classifying the initial weight features and assigning weight values ​​to each classification package. The creation and assignment process of the classification package ensures that the selection of the delivery path can be dynamically adjusted according to the priority needs of different customers (such as urgent orders, special requirements, etc.). By calculating the weight value of each classification package and merging it, the load conditions of each path can be evaluated in real time to ensure that the load capacity of the logistics network matches customer needs and avoid delivery delays or errors caused by excessive load. By comparing the path load rate and the weight load rate, the system can optimize the path selection and ultimately determine the first optimal delivery path, thereby improving delivery efficiency, ensuring that order delivery is completed on time and accurately, and improving resource utilization and the overall scheduling capability of the system.

[0008] In a preferred example, the present application may be further configured as follows: the step of matching the corresponding current delivery path according to the classification package and determining the path load rate of the current delivery path in real time includes: According to the classification package, matching the corresponding project identification; According to the project identifier, the corresponding current delivery path is selected; Determine each path item in the current delivery path and the item load rate of each path item, wherein the path items include a primary sorting item, a printing item, a secondary sorting item and a verification item, wherein the primary sorting item includes at least a sorting mail pick-up item; The item load rates of the various path items are weighted averaged to generate a corresponding path load rate.

[0009] By adopting the above technical solution, the corresponding current distribution path can be accurately matched according to the item identification in the classification package, and the distribution path related to the item identification can be further screened out. Each distribution path consists of multiple path items, such as primary sorting, word printing, secondary sorting and verification, etc. These path items involve different logistics operation links and resource allocations. By conducting a detailed evaluation of the project load rate of each path item, the load status of each link can be monitored in real time, thereby reflecting the carrying capacity of the overall distribution path. The primary sorting project, word printing project, secondary sorting project and verification project are assigned different load values ​​according to their respective workloads and required resources. Finally, by weighted averaging the load rates of these projects, the system can comprehensively consider the load conditions of each link and generate an accurate path load rate. The calculation result of this load rate helps the system dynamically adjust the distribution path to ensure that each path is within the optimal load range, thereby improving distribution efficiency, avoiding excessive congestion or waste of resources, and ensuring the smoothness of the logistics distribution process.

[0010] In a preferred example, the present application may be further configured as follows: the step of customizing the initial delivery label according to the identity feature and the initial weight feature includes: Scan and verify the product barcodes pre-attached to the outbound goods; If the scanning verification is successful, the barcode information corresponding to the product barcode in the established warehousing management system is removed from the shelf; Determine the unique code for order transfer based on the identity characteristics; Customize and automatically print the initial delivery label according to the initial weight feature and the order transfer unique code; A corresponding label attaching operation is performed, wherein the label attaching operation is used to attach the initial delivery label to the outbound goods.

[0011] By adopting the above technical solution, in the process of customizing the initial delivery label, the barcode of the goods on the outbound goods can be scanned and verified to ensure the consistency between the barcode and the goods, thereby reducing the occurrence of human errors. If the scan verification is successful, the system will automatically remove the inventory information corresponding to the barcode to ensure the real-time update of the inventory data. Then, based on the customer's identity characteristics and initial weight characteristics, the system can generate a unique order flow unique code for each order, thereby ensuring that each piece of goods can be uniquely identified and tracked in the system. By combining the order flow unique code and the initial weight characteristics, the system can customize the initial delivery label to ensure that the label content is accurate and meets the logistics requirements. Finally, the system automatically prints and executes the label application operation, accurately applies the initial delivery label to the outbound goods, and ensures the correct identification and tracking of each package during the delivery process. The automated design of this process improves work efficiency, reduces the error rate of manual intervention, and ensures the information flow and transparency of the entire logistics distribution process.

[0012] In a preferred example, the present application may be further configured as follows: the step of real-time tracking of the transit information of the initial delivery label includes: Obtaining scan information of the initial delivery label; Determine a scanning node corresponding to the scanning information, where the scanning node is a sensor device corresponding to one of the path items of the first optimal delivery path; Corresponding transfer information is generated according to the scanning node and the scanning information.

[0013] By adopting the above technical solution, in the process of real-time tracking of the transfer information of the initial delivery label, the corresponding scanning information can be obtained by scanning the initial delivery label, ensuring that the tracking data of each piece of goods is transmitted to the system in real time and accurately. Based on the scanning information, the system identifies the corresponding scanning node, which corresponds to the sensor equipment of a specific link in the distribution path, such as the logistics center, sorting station or sensor on the transport vehicle. By processing these scanning nodes and scanning information, the system can automatically generate detailed transfer information and update it to the distribution path in a timely manner, ensuring that the transfer status of each step of the goods can be fed back to the system in real time. This not only improves the transparency of logistics information, but also provides accurate data support for subsequent path optimization and customer inquiries, thereby improving the management efficiency and accuracy of the entire logistics distribution process.

[0014] In a preferred example, the present application can be further configured as follows: the step of acquiring the dynamic weight feature in real time in the user front-end application, matching the second optimal delivery path according to the dynamic weight feature, or automatically printing the delivery optimization label at the next delivery point of the current delivery point in the first optimal delivery path includes: Calling corresponding order influencing factors in the user front-end application, wherein the order influencing factors include expedited requests, traffic conditions, weather changes, and order changes; Assigning weights to each of the order influencing factors to generate a second weight value, and adding the second weight values ​​to generate a corresponding dynamic weight feature; Determine whether the characteristic value corresponding to the dynamic weight characteristic exceeds the determined change threshold, and if not, continue to determine; If it exceeds, it is determined whether the second optimal delivery path can be determined according to the path load rate of the first optimal delivery path. If the second optimal delivery path is determined, a first interactive window for selecting whether to select the second optimal delivery path is pushed. If the second optimal delivery path is not determined, a second interactive window for selecting whether to automatically print the delivery optimization label at the next delivery point of the current delivery point in the first optimal delivery path is pushed.

[0015] By adopting the above technical solution, dynamic weight features can be obtained and analyzed in real time in the user front-end application to ensure that the delivery path can flexibly adapt to changes in order demand. The system first evaluates the impact of order influencing factors (such as expedited requests, traffic conditions, weather changes, and order changes) on the delivery path in real time by calling these factors. Then, each order influencing factor is weighted to generate a second weight value, and all weight values ​​are added to obtain the final dynamic weight feature. In this way, the system can dynamically adjust the delivery path based on real-time order changes. When the change of the dynamic weight feature exceeds the preset change threshold, the system will determine whether it is necessary to determine the second optimal delivery path based on the path load rate of the first optimal delivery path. If the second optimal path can be determined, the system will push an interactive window for the user to choose whether to adopt this path; if the second optimal path cannot be determined, the system will push an interactive window to prompt the user whether to choose to perform automatic printing of the delivery optimization label at the next delivery point of the current delivery path. This flexible adjustment mechanism can effectively respond to changes in external factors, improve the flexibility and timeliness of the delivery process, and enhance customer experience.

[0016] The second object of the invention is achieved by the following technical solutions: A logistics distribution management device, the logistics distribution management device comprising: The first acquisition module is used to obtain customer order information and match the corresponding outbound goods in the established inbound warehouse management system; A first extraction module is used to extract the initial weight features in the customer order information, and based on the established intelligent matching model, match the corresponding first optimal delivery path according to the initial weight features, wherein the first optimal delivery path at least includes a first mailing path and a first self-pickup path, and generate a visual path corresponding to the optimal delivery path in the user front-end application; A second extraction module is used to extract the identity features in the customer order information, customize and automatically print the initial delivery label according to the identity features and the initial weight features, and the initial delivery label is used to be attached to the outbound goods; An updating module, used for tracking the transfer information of the initial delivery label in real time, and updating the current delivery point on the visualized path in real time according to the transfer information; The second acquisition module is used to acquire the dynamic weight characteristics in real time in the user front-end application, match the second optimal delivery path according to the dynamic weight characteristics, or automatically print the delivery optimization label at the next delivery point of the current delivery point in the first optimal delivery path, and the second optimal delivery path includes at least a second mailing path and a second self-pickup path.

[0017] The third objective of the present application is achieved through the following technical solutions: A computer device comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above-mentioned logistics distribution management method when executing the computer program.

[0018] The fourth objective of the present application is achieved through the following technical solutions: A computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the above-mentioned logistics distribution management method are implemented.

[0019] In summary, the present application includes at least one of the following beneficial technical effects: 1. By obtaining customer order information and matching the corresponding outbound goods with the inbound management system, the need for manual operations is reduced and the outbound process can be accurately automated. Through the intelligent matching model, the system can automatically match the optimal delivery path based on the initial weight characteristics (such as order urgency, customer demand, logistics resources, etc.). This intelligent delivery path planning can fully consider the adaptability of different delivery methods, thereby greatly improving delivery efficiency and effectively reducing the probability of human errors; 2. This problem is solved by generating a visual path corresponding to the optimal delivery path in the user front-end application. Customers can view the logistics status in real time and track the progress of delivery at any time. This transparency not only improves the customer experience, but also provides more data support for logistics management, enabling timely identification and correction of any potential delivery deviations; 3. In traditional logistics processes, route planning is often static and difficult to cope with changes that occur during delivery, such as traffic congestion, sudden weather changes, or other unforeseen factors. By extracting dynamic weight features (e.g., traffic conditions, order changes, customer feedback, etc.), the delivery route is updated in real time according to these changes, and delivery optimization labels can be automatically printed to further adjust the delivery plan. By obtaining these dynamic features in real time and adjusting the delivery plan accordingly, it can ensure that delivery can continue smoothly even when the external environment changes, thus avoiding delays and delivery errors that are common in traditional models. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 It is a flow chart of a logistics distribution management method in one embodiment of the present application.

[0021] Figure 2 This is a flowchart for implementing step S20 in a logistics distribution management method in one embodiment of the present application; Figure 3 This is a flowchart for implementing step S203 in a logistics distribution management method in one embodiment of the present application; Figure 4 This is a flowchart for implementing step S30 in a logistics distribution management method in one embodiment of the present application; Figure 5 This is a flowchart for implementing step S40 in a logistics distribution management method in one embodiment of the present application; Figure 6 It is a flow chart for implementing step S50 in a logistics distribution management method in one embodiment of the present application; Figure 7 This is a principle block diagram of a logistics distribution management device in one embodiment of the present application; Figure 8 It is a schematic diagram of a device in an embodiment of the present application. DETAILED DESCRIPTION

[0022] The present application is further described in detail below in conjunction with the accompanying drawings.

[0023] In one embodiment, if Figure 1 As shown, the present application discloses a logistics distribution management method, which specifically includes the following steps: S10, obtain customer order information, and match the corresponding outbound goods in the established inbound storage management system; in this embodiment, obtaining customer order information means that the system extracts detailed information related to the order after the customer submits the order through the e-commerce platform. This information includes the type, quantity, delivery address, customer needs, etc. of the goods. By matching the corresponding outbound goods from the inbound storage management system, the system can automatically select suitable goods in the inventory according to the specific requirements in the customer's order. The technical effect of this step is to improve the efficiency and accuracy of order processing through automated matching, reduce manual intervention, and ensure the accurate outbound delivery of goods, avoiding incorrect delivery due to poor inventory management. For example, if a customer places an order to buy jewelry earrings, the system will automatically select the corresponding style and quantity of earrings from the warehouse according to the order information, and prepare them for delivery.

[0024] S20, extracting the initial weight features in the customer's order information, matching the corresponding first optimal delivery path based on the established intelligent matching model according to the initial weight features, the first optimal delivery path at least includes the first mailing path and the first self-pickup path, and generating a visual path corresponding to the optimal delivery path in the user's front-end application; in this embodiment, extracting the initial weight features in the customer's order information means that the system extracts important parameters that can reflect the delivery requirements from the customer's order information. The initial weight features may include the urgency of the order, the customer's loyalty, the volume or weight of the goods, the timeliness requirements, etc. Based on these initial weight features, the intelligent matching model will calculate the priority of a delivery path and generate the first optimal delivery path. This path includes at least a mailing path and a self-pickup path. According to the customer's choice, the system can flexibly provide customers with optional paths for two delivery methods. The system will generate and display the visual path corresponding to the first optimal delivery path in real time in the user's front-end application, so that customers can intuitively understand the progress of their order delivery. Specifically, if the order requirement is more urgent, the system may automatically select the fastest delivery method and display the path on the customer's application so that the customer can view the expected delivery time and route in real time.

[0025] S30, extracting the identity features in the customer's order information, and customizing and automatically printing the initial delivery label based on the identity features and the initial weight features. The initial delivery label is used to be affixed to the outbound goods; in this embodiment, extracting the identity features in the customer's order information means that the system confirms the customer's identity by identifying the customer's unique identifier (such as customer ID, account number, etc.). The identity feature is not only a code for identifying the customer, but may also involve information such as the customer's historical purchase record and loyalty level. Based on the customer's identity features and initial weight features, the system will customize and automatically print the initial delivery label for the order. The initial delivery label will contain key information such as product information, customer information, delivery route and estimated arrival time, and will be affixed to the outbound goods. The technical effect of this step is to automatically generate and attach delivery labels, which not only improves operational efficiency, but also ensures that each package in the logistics process can be accurately tracked and identified, avoiding delivery problems caused by incorrect or missing labels. For example, if the customer is a VIP customer, the system may give its order a higher delivery priority based on the customer's identity features, and generate a special delivery label for the order.

[0026] S40, real-time tracking of the transit information of the initial delivery label, and updating the current delivery point on the visual path in real time according to the transit information; in this embodiment, real-time tracking of the transit information of the initial delivery label refers to real-time tracking of the transportation process of the goods by scanning the initial delivery label (such as a barcode or RFID tag). Whenever the goods pass through a key transit node, the system obtains the transit information through the sensor device of the scanning node (such as an RFID reader, a barcode scanner, etc.), and feeds this information back to the system in a timely manner. The system updates the current delivery point on the visual path through the transit information to ensure that the user can see the latest location and estimated arrival time of the goods in real time. The technical effect of this step is to provide real-time logistics tracking, increase the transparency of the delivery process, and allow customers to keep abreast of the progress of the order at any time. For example, assuming that the order is passing through multiple sorting centers and distribution sites, the system will dynamically update each site that the goods pass through in the user's application until it is finally delivered to the customer.

[0027] S50, real-time acquisition of dynamic weight features in the user front-end application, matching the second optimal delivery path according to the dynamic weight features, or automatically printing the delivery optimization label at the next delivery point of the current delivery point in the first optimal delivery path, the second optimal delivery path includes at least a second mailing path and a second self-pickup path. In this embodiment, real-time acquisition of dynamic weight features in the user front-end application means that the system can dynamically update the delivery requirements of customer orders according to real-time data (such as traffic conditions, weather changes, customer expedited requests, etc.) during the delivery process. These dynamic weight features will be reflected in the selection of the delivery path according to actual conditions. The system matches the second optimal delivery path according to these real-time changes, or in the first optimal delivery path, automatically prints the delivery optimization label according to the next delivery point of the current delivery point. The second optimal delivery path includes a second mailing path and a second self-pickup path, which are mainly used to deal with unforeseen situations, such as traffic congestion, weather changes, etc., to ensure that the order can be delivered on time. The technical effect of this step is to flexibly deal with unexpected situations in the delivery process and adjust the delivery path in real time to ensure the shortest delivery time and the most efficient route. For example, in certain emergencies (such as bad weather or traffic accidents), the system will automatically calculate the second best route and notify the customer of the latest delivery information or choose whether to continue optimizing the route to avoid delays or wrong deliveries.

[0028] In summary, by obtaining customer order information and matching the corresponding outbound goods with the inbound management system, the need for manual operation is reduced and the outbound process can be accurately automated. Through the intelligent matching model, the system can automatically match the optimal delivery path based on the initial weight features (such as order urgency, customer demand, logistics resources, etc.). This intelligent delivery path planning can fully consider the adaptability of different delivery methods, thereby greatly improving delivery efficiency and effectively reducing the probability of human errors; this problem is solved by generating a visual path corresponding to the optimal delivery path in the user front-end application. Customers can view the logistics status in real time and track the progress of delivery at any time. This transparency not only improves the customer experience, but also provides more data support for logistics management, which can timely identify and correct any potential delivery deviations; in traditional logistics processes, path planning is often static and difficult to cope with changes in the delivery process, such as traffic congestion, sudden weather changes or other unforeseen factors. By extracting dynamic weight features (for example, traffic conditions, order changes, customer feedback, etc.), the delivery path is updated in real time according to these changes, and delivery optimization labels can be automatically printed to further adjust the delivery plan. By acquiring these dynamic features in real time and adjusting the delivery plan accordingly, it is possible to ensure that delivery can proceed smoothly even when the external environment changes, thus avoiding delays and delivery errors that are common in traditional models.

[0029] In one embodiment, if Figure 2 As shown, in step S20, that is, based on the established intelligent matching model, the step of matching the corresponding first optimal delivery path according to the initial weight features includes: S201. Classify the initial weight features to generate corresponding classification packages; in this embodiment, classifying the initial weight features means that the system classifies the initial weight features extracted from the customer order (for example, the urgency of the customer's needs, the order amount, the type of goods, the delivery time requirements, etc.). These features may involve different dimensions of the order, and the system will divide the orders into different classification packages based on these features. Each classification package represents a class of orders with similar delivery requirements. For example, for urgent orders, regular orders, and scheduled orders, the system will put them into different classification packages respectively. The technical effect of this step is that a clear feature model can be established for each order, thereby providing data support for subsequent path matching and optimization. Through such classification processing, the system can more efficiently identify and process orders with different needs, and improve the overall logistics responsiveness and accuracy.

[0030] S202. Based on the established intelligent matching model, each classification package is assigned a value to obtain a first weight value for each classification package; in this embodiment, based on the established intelligent matching model, each classification package is assigned a first weight value for each classification package using an intelligent matching model (such as a machine learning model, a rule engine, etc.) according to the characteristics of each classification package. The weight value reflects the priority and delivery requirements of the classification package in the overall delivery path. The intelligent matching model will calculate according to the actual business rules, historical data and the dynamic needs of the current order to generate a weight value suitable for the current classification package. Specifically, if an order belongs to the emergency delivery category, the system will assign a higher weight value to the classification package to ensure that the order can be delivered first. The technical effect of this step is that by assigning weights, the delivery priority of each classification package can be reasonably allocated, thereby providing a scientific basis for the optimal path selection.

[0031] Specifically, when assigning values ​​to each classification package based on the intelligent matching model, the first thing to consider is the specific characteristics of the delivery demand represented by each classification package. The intelligent matching model will assign values ​​based on these demands to determine the weight value of each classification package. This assignment process is based on a data-driven approach, which combines algorithms and rules to handle the priority, timeliness and special requirements of orders. Specifically, the intelligent matching model will first analyze the characteristics of each classification package, which may include the urgency of the order, the value of the goods, the customer's requirements (such as whether it is expedited), the distance to the destination, the choice of delivery time, etc. Each feature will be assigned a specific value based on the preset business rules and historical data. These values ​​reflect the degree of influence of each feature on the delivery path; for example, if an order belongs to the expedited delivery category, the system will assign a higher weight value to the classification package to ensure that its delivery path can be processed first. On the other hand, for orders for regular delivery, the weight value is relatively low, and the system may choose a more standard delivery path. In addition, the intelligent matching model will also take into account the volume and weight of the order. If the order is for bulk commodities, the system will allocate more distribution resources or give priority to the appropriate mode of transportation to ensure that the distribution is not limited by the physical properties of the goods; the calculation of the first weight value not only relies on static data, but also dynamically adjusts it in combination with real-time data. For example, during peak hours, the choice of delivery route may be affected by traffic conditions. The intelligent matching model will obtain traffic information in real time and dynamically adjust the weight value according to the current traffic conditions. The dynamic assignment of this weight value can ensure that the order can choose the most appropriate delivery route in different situations, thereby optimizing delivery timeliness and resource utilization; once the weight value of each classification package is assigned, the system can perform subsequent delivery route optimization and matching based on these weight values, thereby realizing intelligent and efficient logistics management.

[0032] S203, according to the classification package, matching the corresponding current distribution path, and determining the path load rate of the current distribution path in real time; in this embodiment, according to the classification package, matching the corresponding current distribution path means that the system uses the classification package information with assigned weight values ​​to match the most suitable distribution path. The characteristics of each classification package determine the suitable distribution path. For example, urgent orders may require a faster express delivery method, while regular orders can choose a standard distribution path. The system will select the most suitable distribution path for each classification package in combination with the path resources and distribution requirements in the current distribution network. In addition, determining the path load rate of the current distribution path in real time means that the system will monitor and calculate the load of each distribution path in real time. The path load rate reflects the use of transportation resources on the current path, such as whether there are high-density distribution tasks or whether there are sufficient resources to handle new distribution requirements. The technical effect of this step is that by monitoring the path load in real time, the system can dynamically adjust the distribution path according to the actual situation of the resources to avoid delays or distribution errors caused by path overload.

[0033] Specifically, the process of determining the path load rate of the current distribution path in real time is mainly to monitor and analyze the resource usage of each link on the distribution path, so as to evaluate the path carrying capacity and the utilization rate of transportation resources. Specifically, the path load rate is calculated based on the dynamic data in the actual transportation process, involving multiple factors such as transportation capacity, current number of tasks, delivery time window, traffic conditions, etc. The system collects this data in real time to continuously adjust the evaluation of the path load to ensure the effectiveness of the path and the rational allocation of resources.

[0034] First, the system obtains the use of transportation resources for each delivery route in real time, including vehicles, delivery personnel, warehouse capacity, transportation tools, etc. By integrating with other data in the logistics management system, the system can understand the number of resources and loads allocated on each route. For example, if a route has been occupied by multiple orders and there are few remaining available resources, the system will calculate the load of the route based on this information. The higher the load rate, the closer the resource usage of the route is to the upper limit, which may affect the delivery efficiency. Secondly, the system dynamically adjusts the route load rate by analyzing external factors such as real-time traffic data and weather conditions. In the case of traffic congestion or bad weather conditions, the system will increase the weight of these factors on the route load rate because these factors will increase the time and resource consumption of delivery. By analyzing these external data in real time, the system can effectively predict the feasibility and resource requirements of the route, so as to adjust the load rate in time to avoid continuing to allocate more orders when the route load is too high, which will cause delivery delays or waste of resources. In addition, the system will also dynamically monitor the workload of each link in the delivery process, such as the load of sorting, loading, and delivery. These links also play an important role in the calculation of the path load, especially when the path involves multiple distribution projects, such as sorting, printing, packaging, etc. The increase in these workloads will have an impact on the path load. The system updates the path load rate in real time by continuously tracking the progress of these links. For example, if the workload of a sorting node increases sharply, the system will evaluate the load of the node and may dispatch more resources or adjust the path. In the end, all of this data—including transportation resources, traffic and weather impacts, and the workload of each link—will be summarized into the system, and the system will perform a weighted analysis on them to calculate the final path load rate. The value of this load rate can reflect the current resource usage of the path in real time, providing an important basis for subsequent distribution path optimization and resource adjustment. If the load rate of a certain path is too high, the system will prompt the dispatcher or automatically select other paths to avoid excessive concentration of resources, thereby ensuring a smooth and efficient distribution process. In short, the path load rate of the current distribution path is determined in real time by dynamically monitoring the resource usage of each link, the changes in real-time external factors, and the workload of each link in the transportation process. Through this comprehensive analysis, the system can evaluate the path load status in real time, ensure the rational allocation of distribution resources, and avoid delays or waste of resources during the distribution process.

[0035] S204. Determine the corresponding weight load rate according to the sum of the first weight values ​​of each classification package; in this embodiment, determining the corresponding weight load rate according to the sum of the first weight values ​​of each classification package means that the system calculates a total weight load rate according to the weight value of each classification package. This load rate reflects the priority and resource requirements of all classification packages on the distribution path. The weight load rate is obtained by adding up the weight value of each classification package, and can fully reflect the impact of different order requirements on the distribution path. For example, if a distribution path involves multiple high-priority orders (such as urgent orders), the weight load rate of the path is higher, which means that the system will give priority to these orders to ensure the reasonable allocation of resources. The technical effect of this step is that the calculation of the weight load rate provides the system with a basis for evaluating whether different paths are suitable for current order requirements, thereby achieving more accurate path selection.

[0036] S205. Determine the corresponding first optimal delivery path according to the comparison result of the path load rate and the weight load rate. In this embodiment, determining the corresponding first optimal delivery path according to the comparison result of the path load rate and the weight load rate means that the system compares the path load rate and the weight load rate to determine the optimal delivery path. The comparison result of the path load rate and the weight load rate can help the system determine whether the resources of a certain path have reached the upper limit, or whether there is a more suitable alternative path. Through such a comparison, the system can ensure that a path is selected that meets the order priority requirements and can reasonably allocate resources. For example, if the load rate of a path is high, the system may choose another path with a lower load to avoid traffic congestion or delivery delays. The technical effect of this step is that by comparing and optimizing the load conditions of the path, the system can ensure that the distribution resources are optimally utilized, while ensuring that customer orders can be delivered on time and accurately, thereby improving the efficiency and responsiveness of the overall logistics system.

[0037] In one embodiment, if Figure 3 As shown, in step S203, that is, the step of matching the corresponding current delivery path according to the classification package and determining the path load rate of the current delivery path in real time, includes: S2031. Match the corresponding project identifier according to the classification package; in this embodiment, matching the corresponding project identifier according to the classification package means that the system assigns a unique project identifier to each order based on the order characteristics and requirements previously obtained through the classification package. This project identifier is used to distinguish different delivery tasks and routes, and can accurately match the corresponding delivery project. The project identifier can represent each link in the distribution process, such as sorting, packaging, shipping, etc. The task volume, priority and resource requirements of each link can be tracked and managed through the identifier. Specifically, if an order needs to be processed first or contains multiple tasks (such as mailing and self-pickup), the system will assign corresponding identifiers to these orders so that the delivery path can be tracked and adjusted in subsequent steps.

[0038] S2032. Filter out the corresponding current delivery path according to the project identification; in this embodiment, filtering out the corresponding current delivery path according to the project identification means that the system determines the delivery path where the order is currently located through the project identification. Each project identification is associated with a specific delivery path, and these paths usually consist of multiple links, such as sorting, transportation, and distribution. By analyzing the project identification, the system can filter out the current delivery path corresponding to it to ensure that each order can be delivered according to the predetermined path. For example, if an order belongs to an urgent delivery task, the system will filter out a fast delivery path suitable for the urgent task; if it is an ordinary order, the system will select a standard delivery path. This step ensures that the system can dynamically match the delivery path that best suits the current order requirements.

[0039] S2033, determine each path item in the current distribution path, and the project load rate of each path item, the path item includes a primary sorting item, a printing item, a secondary sorting item and a verification item, wherein the primary sorting item at least includes a sorting mail pick-up item; in this embodiment, determining each path item in the current distribution path, and the project load rate of each path item means that the system calculates the load rate of each path item by performing a detailed analysis of each link of the current distribution path. Path items include but are not limited to a primary sorting item, a printing item, a secondary sorting item and a verification item, wherein the primary sorting item at least includes a sorting mail pick-up item. Each path item has different workloads and resource requirements, so the system needs to assign a load value to each item according to actual conditions. For example, a primary sorting item may involve a large number of item sorting and packaging operations, and its load rate is relatively high; while the printing item may mainly involve commodity label printing, and the load is relatively low. By accurately evaluating the load rate of each path item, the system can understand the resource usage of each link on the distribution path in real time to ensure that each link in the entire distribution process can obtain reasonable resource allocation.

[0040] Specifically, one sorting project is to distinguish orders that need to be printed, orders that are missing external factory goods, and orders that have complete mailing / self-pickup goods. Among them, after one sorting of orders that need to be printed, the scanning transfer order of the printing project can be printed, and after one sorting of orders that are missing external factory goods, the external factory goods data is exported (the external factory delivers the goods to the platform based on this data). After the external factory returns the goods, the barcode of the goods is scanned to automatically match the order, and the app synchronizes the shipping status (warehousing + distribution), and then exports the distribution delivery order (verifies whether the gram weight and labor cost are consistent with those provided by the manufacturer. This comparison data comes from the data when the goods are created). In addition, when scanning Scan the barcode of the goods to automatically match the order, and the app synchronizes the delivery status (warehousing + distribution) in the steps. It can also be divided into the warehousing and distribution of goods from other factories. The goods are automatically matched with the order and a distribution and warehousing prompt is given. The distribution and warehousing prompt can be: first, the first scan (the goods are the first goods of the external factory in the order); second, it already exists in the area waiting for distribution (in addition to this item, there are other goods from the external factory in the order); third, the order is not complete, but the factory is complete (the goods of the external factory in the order have been fully distributed); fourth, the order is complete (the goods of the order have been fully distributed), and the secondary sorting item can intuitively see whether the order goods have been distributed.

[0041] After exporting the distribution delivery order, you can continue to sort the orders that need to be labeled, the orders that need to be boxed, and the orders that need to be certified in the secondary sorting project. Among them, the first sorting of the orders that distinguish the complete goods for mailing / self-pickup is also directly sent to the secondary sorting project. If it is an order that needs to be labeled, the label number is automatically generated (the data is synchronized with the certificate agency through the interface), and then the transfer order and the product barcode are scanned (check the certificate / label, matching). If it is an order that needs to be boxed, a sorting batch order is generated, and then the transfer order and the product barcode are scanned (check the certificate / label, matching). Matching), if it is an order that needs a certificate for sorting, a batch order will be generated (synchronized with the certificate agency to produce the return goods), and then the forwarding order and the barcode of the goods will be scanned (check the certificate / tag, matching). After scanning the forwarding order and the barcode of the goods (check the certificate / tag, matching), the data will be automatically compared for consistency, and then the mailing / self-pickup order generated after one sorting will be judged. If it is self-pickup, a manual click / self-pickup code will be automatically generated after 6 minutes (synchronized to the customer account). If it is mailed, the express order app will be automatically printed to synchronize the logistics status, and then it will be packaged for door-to-door collection; Among them, all the verifications of weight and labor costs are consistent with those provided by the manufacturer. This comparison data comes from the data when the goods are created, the verification of certificates / tags, and similar supporting steps are all verification items, and the apps mentioned above are all so-called user front-end applications.

[0042] S2034. Weighted average the project load rates of each path project to generate a corresponding path load rate. In this embodiment, weighted average the project load rates of each path project to generate a corresponding path load rate means that the system obtains a comprehensive path load rate by weighted calculation of the load rates of each path project. The load rate of each path project will be weighted according to the proportion of resources it occupies in the entire distribution process. For example, the workload of the sorting project is large, so the weight of its load rate will be higher; while the workload of the printing project is small and the weight is lower. By weighted averaging the load rates of each path project, the system can obtain an accurate path load rate, thereby evaluating whether the distribution path is suitable for current resource requirements. If the path load rate is too high, the system can choose to adjust the distribution plan to avoid delays and waste of resources caused by path overload. This weighted average calculation method ensures that the system reasonably evaluates and optimizes the resource usage of each path during the distribution process, thereby improving distribution efficiency and accuracy.

[0043] In one embodiment, if Figure 4 As shown, in step S30, i.e., the step of customizing the initial delivery label according to the identity feature and the initial weight feature, it includes: S301. Scan and verify the barcode of the goods pre-attached on the outbound goods; in this embodiment, scanning and verifying the barcode of the goods pre-attached on the outbound goods means that the system verifies whether the goods are consistent with the order information by scanning the barcode or QR code on the goods. The barcode contains the unique identifier of the goods, which is an important data carrier in logistics management. The purpose of scanning and verification is to ensure that the system can obtain and verify the exact information of the outbound goods in real time, thereby avoiding distribution problems caused by manual operation or label errors. For example, when a jewelry product is scanned, the system will retrieve the product information corresponding to the barcode from the database, such as model, specification, quantity, etc. If the scan is successful, the system will mark the goods as confirmed and ready for subsequent processing. The technical effect of this step is to improve the accuracy of goods out of the warehouse, reduce human errors, and ensure the smooth progress of each distribution link.

[0044] S302. If the scan verification is successful, the barcode information corresponding to the barcode of the goods in the established warehousing management system is removed from the shelves; in this embodiment, if the scan verification is successful, the barcode information corresponding to the barcode of the goods in the established warehousing management system is removed from the shelves. This means that after the barcode scanning and verification of the goods is successful, the system will automatically update the inventory information and "remove" the goods from the warehousing management system. Specifically, the system will confirm the identity of the goods through the scanned barcode, and update the inventory status in the background system to ensure that the inventory records reflect the actual flow of goods. Through the automatic removal operation, the system avoids the tedious operation of manually recording and updating inventory information, and reduces the probability of error due to manual intervention. For example, if a product has been shipped from the warehouse, the system will automatically reduce the corresponding inventory quantity based on the scanned information to maintain the real-time accuracy of the inventory information. The technical effect of this step is to ensure the timeliness and accuracy of inventory data and ensure the efficiency of supply chain management.

[0045] S303. Determine the unique code for order transfer based on identity characteristics. In this embodiment, determining the unique code for order transfer based on identity characteristics means that the system generates a unique "unique code for order transfer" based on the customer's identity characteristics (such as customer ID, account information or other identity identification data). This unique code is a unique identifier for each order during the delivery process and is used to track the flow status of the order. The system automatically generates this unique code for each order by combining the identity characteristics with other order information (such as goods, delivery address, time, etc.). Specifically, in the jewelry industry, a customer's order may contain multiple goods, and the delivery path of each product may be different. Through the unique code for order transfer, the system can accurately track the delivery progress of each product to avoid confusion or loss of goods in the same order. The technical effect of this step is to provide each order with a fully traceable identifier, which improves the accuracy and transparency of logistics tracking.

[0046] S304, customize and automatically print the initial delivery label according to the initial weight characteristics and the unique code of the order flow; in this embodiment, customize and automatically print the initial delivery label according to the initial weight characteristics and the unique code of the order flow means that the system automatically generates and prints the initial delivery label according to the initial weight characteristics in the customer order (such as order urgency, customer level, delivery priority, etc.) and the unique order flow unique code. The initial label usually includes product information, delivery path, customer information, estimated delivery time, barcode and other contents. After these labels are attached to the outbound goods, they can provide complete tracking information throughout the delivery process. The system customizes the label content and delivery priority for each order according to different weight characteristics (such as high-priority orders or expedited orders). Specifically, if a jewelry order is marked as high priority, the system will automatically indicate this on the label and arrange priority delivery for it. The technical effect of this step is to improve the automation of logistics management, reduce errors and delays in manual operations, and ensure efficient and accurate delivery arrangements.

[0047] S305, execute the corresponding labeling operation, the labeling operation is used to attach the initial delivery label to the outbound goods. In this embodiment, executing the corresponding labeling operation, the labeling operation is used to attach the initial delivery label to the outbound goods means that after the initial delivery label is printed, the system automatically attaches the label to the goods. The labeling operation is not only a physical labeling process, but also involves ensuring that each label accurately matches the corresponding goods. Through the automated labeling operation, the system can ensure that the label is correctly and tightly attached to each product, avoiding problems such as loose labels and misalignment. For example, in the jewelry industry, since the goods are often small and delicate, the system will accurately attach the label to each product package through automated equipment, and ensure that the label information is consistent with the data in the system. The technical effect of this step is to improve the distribution efficiency, ensure that each product can be accurately identified and tracked during the distribution process, and avoid logistics problems and customer complaints caused by label errors.

[0048] In one embodiment, if Figure 5 As shown, in step S40, i.e., the step of real-time tracking of the transfer information of the initial delivery label, it includes: S401, obtaining the scanning information of the initial delivery label; in this embodiment, obtaining the scanning information of the initial delivery label means that the system obtains the information on the initial delivery label in real time through a scanning device (such as a barcode scanner or an RFID reader). The initial delivery label usually contains basic information of the goods, a barcode, a QR code, etc., which are used to identify the goods and track the logistics status. By scanning the label, the system can read the key information such as the unique identifier, starting position, and target position of the goods, and transmit these data to the background system to ensure subsequent logistics tracking and updates. Specifically, when the goods are delivered to the logistics center or distribution station, the scanner will use the scanning device to obtain the label information and transmit the scanning results to the system, so that the system can record the transfer status and path of each piece of goods in a timely manner. The technical effect of this step is to provide real-time cargo tracking capabilities, provide data support for subsequent distribution path optimization and scheduling, and ensure the transparency and accuracy of the logistics process.

[0049] S402, determine the scanning node corresponding to the scanning information, the scanning node is a sensor device corresponding to one of the path items of the first optimal distribution path; in this embodiment, determining the scanning node corresponding to the scanning information means that the system determines a key node in the distribution path corresponding to the information based on the distribution initial label information obtained from the scanning device. This node is called a "scanning node", which is a specific point on the distribution path, usually a place where the associated sensor device collects data in real time. The scanning node can be a scanning point in the logistics center, a cargo inspection station at the distribution station, an RFID reader on a transport vehicle, etc., any device that can read and confirm the current location of the goods. In actual applications, if the goods pass through an inspection station, after the scanner scans the label, the system can automatically confirm that the scanning information is associated with the data of the station. Specifically, if there are multiple sorting stations on the distribution path of a certain jewelry product, the system can identify each station that the goods pass through, and use these stations as scanning nodes to track the dynamics of the goods. The technical effect of this step is to ensure that each scan data can be associated with the correct path node, so that the logistics information can be accurately circulated and recorded.

[0050] S403, generating corresponding transshipment information according to the scanned node and the scanned information. In this embodiment, generating corresponding transshipment information according to the scanned node and the scanned initial label information of the delivery means that the system generates transshipment information associated with the node according to the scanned node and the scanned initial label information of the delivery. These transshipment information contain dynamic information such as the current location, status, and estimated arrival time of the goods, which are used to update the progress of the delivery path. For example, when the goods are scanned from a sorting station, the system will generate transshipment information including the station information, timestamp and goods status, and store it in the database for subsequent path updates and customer inquiries. The transshipment information not only reflects the physical location of the goods, but also includes the execution status of each key link on the path, such as whether the sorting is completed, whether the transportation tool is ready, etc. Specifically, assuming that a jewelry order is scanned by the warehouse, the system will generate the current transshipment information of the order and update it to the user's logistics progress in real time. The technical effect of this step is that through the real-time generation and update of transshipment information, the system can accurately track the status of each delivery node, improve the traceability and transparency of the delivery path, provide customers with more efficient services, and also help optimize resource scheduling in the logistics process.

[0051] In one embodiment, if Figure 6 As shown, in step S50, i.e., obtaining the dynamic weight feature in real time in the user front-end application, matching the second optimal delivery path according to the dynamic weight feature, or performing the step of automatically printing the delivery optimization label at the next delivery point of the current delivery point in the first optimal delivery path, includes: S501. Calling corresponding order influencing factors in the user front-end application. Order influencing factors include expedited requests, traffic conditions, weather changes, and order changes. In this embodiment, calling corresponding order influencing factors in the user front-end application means that the system obtains dynamic change information related to the order in real time through the user front-end application. These influencing factors include but are not limited to expedited requests, traffic conditions, weather changes, and order changes. Expedited requests may mean that the order needs to be delivered first. Traffic conditions and weather changes will directly affect the selection and timeliness of the delivery path. Order changes may be due to changes in customer needs (such as changing the address or modifying the delivery time period). The system can dynamically adjust the delivery plan by analyzing these influencing factors. For example, if a customer makes an expedited request, the system will automatically give the order a higher weight and give priority to the delivery resources. The technical effect of this step is to make the selection of the delivery path more flexible and responsive to real-time changes, thereby improving the timeliness and customer satisfaction of the delivery.

[0052] S502, weighting each order influencing factor to generate a second weight value, and adding each second weight value to generate a corresponding dynamic weight feature; in this embodiment, weighting each order influencing factor means that the system assigns a value to each influencing factor according to its importance to generate a second weight value. Each order influencing factor (such as expedited request, traffic conditions, weather changes, etc.) will be assigned a weight value according to its impact on delivery timeliness or resources. The assignment of these weight values ​​is completed through historical data analysis, real-time data input and intelligent algorithms. For example, traffic conditions may be assigned according to the congestion of the road section or the severity of weather changes. If a certain path may be delayed due to bad weather, the system will assign a higher weight to the weather change factor and adjust the delivery plan. Finally, the system sums up these individual weight values ​​to form a comprehensive dynamic weight feature to influence the selection of the delivery path. In this way, the system can flexibly adjust the delivery path according to real-time changes, thereby ensuring efficiency and accuracy in the delivery process.

[0053] S503. Determine whether the characteristic value corresponding to the dynamic weight feature exceeds the determined change threshold. If not, continue to judge. In this embodiment, judging whether the characteristic value corresponding to the dynamic weight feature exceeds the determined change threshold means that the system evaluates the generated dynamic weight features to determine whether these characteristic values ​​exceed the preset change threshold. If the change of the dynamic weight feature exceeds the set threshold, it means that the current delivery conditions have changed significantly and the delivery path may need to be readjusted. For example, if the combined weight of the expedited request and the traffic condition is high and exceeds the set threshold, the system will start the matching mechanism of the second optimal path. If the threshold is not exceeded, the system will continue to judge and maintain the original delivery path. The technical effect of this step is to ensure that the delivery path selection can respond to changes in order demand in a timely manner through real-time monitoring and dynamic judgment, thereby avoiding delivery delays or errors.

[0054] S504, if it exceeds, then determine whether the second optimal delivery path can be determined according to the path load rate of the first optimal delivery path, if the second optimal delivery path is determined, then push the first interactive window for whether to select the second optimal delivery path, if the second optimal delivery path is not determined, then push the second interactive window for whether to select the next delivery point of the current delivery point in the first optimal delivery path to perform automatic printing of the delivery optimization label. In this embodiment, if it exceeds, then determine whether the second optimal delivery path can be determined according to the path load rate of the first optimal delivery path means that when the dynamic weight feature exceeds the threshold, the system will decide whether to select the second optimal delivery path according to the current load of the first optimal delivery path. If the load rate of the first optimal path is too high, the system will evaluate other available paths and select the second optimal path according to the load rate, timeliness and other factors of the path. The path load rate indicates the resource utilization of the current path, such as the occupancy of the transportation tool, the workload of the sorting center, etc. If the second optimal path meets the timeliness requirements and has a low load, the system will select this path for delivery. The technical effect of this step is to ensure automatic optimization of the route when resources are tight through real-time load evaluation, so as to avoid delivery delays caused by route congestion; after successfully determining the second best delivery route, the system will push an interactive window to the customer or operator to ask whether to confirm the selection of the route. This interactive window usually appears in the user front-end application, allowing the customer or logistics dispatcher to see the current delivery route selection and make a decision whether to modify it. For example, the system may remind the customer that based on the current traffic and weather conditions, the second best route may be faster, and the customer can choose whether to change the delivery route. The technical effect of this step is to ensure flexible adjustment of the delivery route through interaction with the user, while giving the customer a certain degree of control, enhancing the customer's sense of participation and satisfaction; when the second best route cannot be determined, the system will continue to optimize the delivery process on the first best route, specifically by adjusting the route through the next station of the current delivery point and automatically printing the optimization label. The system will push an interactive window to the user, informing the customer or dispatcher that the current route will pass through a new node, and asking whether to continue to print the optimization label. The optimization label can include updated delivery information, estimated arrival time, etc. The technical effect of this operation is to ensure that even if it is impossible to switch to the second best path, the delivery efficiency can still be improved by optimizing the next node of the existing path, thereby maximizing resource utilization and timeliness, ensuring delivery accuracy and customer satisfaction.

[0055] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0056] In one embodiment, a logistics distribution management device is provided, and the logistics distribution management device corresponds one-to-one to a logistics distribution management method in the above embodiment. Figure 7 As shown, the logistics distribution management device includes a first acquisition module, a first extraction module, a second extraction module, an update module and a second acquisition module. The detailed description of each functional module is as follows: The first acquisition module is used to obtain customer order information and match the corresponding outbound goods in the established inbound warehouse management system; A first extraction module is used to extract the initial weight features in the customer order information, and based on the established intelligent matching model, match the corresponding first optimal delivery path according to the initial weight features, wherein the first optimal delivery path at least includes a first mailing path and a first self-pickup path, and generate a visual path corresponding to the optimal delivery path in the user front-end application; A second extraction module is used to extract the identity features in the customer order information, customize and automatically print the initial delivery label according to the identity features and the initial weight features, and the initial delivery label is used to be attached to the outbound goods; An updating module, used for tracking the transfer information of the initial delivery label in real time, and updating the current delivery point on the visualized path in real time according to the transfer information; The second acquisition module is used to acquire the dynamic weight characteristics in real time in the user front-end application, match the second optimal delivery path according to the dynamic weight characteristics, or automatically print the delivery optimization label at the next delivery point of the current delivery point in the first optimal delivery path, and the second optimal delivery path includes at least a second mailing path and a second self-pickup path.

[0057] Optionally, the first extraction module includes: A generating unit, used for classifying the initial weight features to generate corresponding classification packages; A first acquisition unit, configured to assign a value to each of the classification packages based on the established intelligent matching model, so as to obtain a first weight value of each of the classification packages; A matching unit, used to match the corresponding current delivery path according to the classification package, and determine the path load rate of the current delivery path in real time; A first determining unit, configured to determine a corresponding weight load rate according to a sum of first weight values ​​of each of the classification packets; A second determining unit, configured to determine a corresponding first optimal delivery path according to a comparison result between the path load rate and the weighted load rate; Optionally, the matching unit includes: A first matching subunit, configured to match a corresponding project identifier according to the classification package; A screening subunit, used to screen out the corresponding current delivery path according to the project identifier; A determination subunit is used to determine each path item in the current delivery path and the item load rate of each path item, wherein the path items include a primary sorting item, a printing item, a secondary sorting item and a verification item, wherein the primary sorting item includes at least a sorting mail pick-up item; A generating subunit, used for performing weighted averaging on the project load rates of the respective path projects to generate a corresponding path load rate; Optionally, the second extraction module includes: A scanning and verification unit, used for scanning and verifying the product barcodes pre-attached on the outbound goods; A delisting unit, used for delisting the barcode information corresponding to the product barcode in the established warehousing management system if the scanning verification is successful; A third determining unit, configured to determine an order transfer unique code according to the identity feature; A customization unit, used to customize and automatically print an initial delivery label according to the initial weight feature and the order transfer unique code; An execution unit, used to execute a corresponding label attaching operation, wherein the label attaching operation is used to attach the initial delivery label to the outbound goods; Optionally, the update module includes: A second acquisition unit, used to acquire the scanning information of the initial delivery label; A fourth determining unit, configured to determine a scanning node corresponding to the scanning information, wherein the scanning node is a sensor device corresponding to one of the path items of the first optimal delivery path; A first generating unit, configured to generate corresponding transfer information according to the scanning node and the scanning information; Optionally, the second acquisition module includes: A calling unit, used to call corresponding order influencing factors in the user front-end application, wherein the order influencing factors include expedited requests, traffic conditions, weather changes, and order changes; A second generating unit, configured to assign a weight to each of the order influencing factors to generate a second weight value, and add the second weight values ​​to generate a corresponding dynamic weight feature; A first judgment unit, used to judge whether the characteristic value corresponding to the dynamic weight characteristic exceeds the determined change threshold, and if not, continue to judge; The second judgment unit is used to judge whether a second optimal delivery path can be determined according to the path load rate of the first optimal delivery path if it exceeds the limit; if the second optimal delivery path is determined, a first interactive window for selecting whether to select the second optimal delivery path is pushed; if the second optimal delivery path is not determined, a second interactive window for selecting whether to automatically print a delivery optimization label at the next delivery point of the current delivery point in the first optimal delivery path is pushed.

[0058] For the specific definition of a logistics distribution management device, please refer to the definition of a logistics distribution management method above, which will not be repeated here. Each module in the above-mentioned logistics distribution management device can be implemented in whole or in part by software, hardware and their combination. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0059] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as follows: Figure 8 As shown. The computer device includes a processor, a memory, a network interface and a database connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a logistics distribution management method is implemented.

[0060] In one embodiment, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the following steps when executing the computer program: S10. Obtain customer order information and match the corresponding outbound goods in the established inbound warehouse management system; S20, extracting the initial weight features in the customer order information, and matching the corresponding first optimal delivery path according to the initial weight features based on the established intelligent matching model, where the first optimal delivery path includes at least a first mailing path and a first self-pickup path, and generating a visual path corresponding to the optimal delivery path in the user front-end application; S30, extracting identity features from the customer's order information, and customizing and automatically printing an initial delivery label based on the identity features and initial weight features, the initial delivery label being used to be affixed to the outbound goods; S40, real-time tracking of the transfer information of the initial delivery label, and updating the current delivery point on the visualized path in real time according to the transfer information; S50. Acquire dynamic weight features in real time in the user front-end application, match the second optimal delivery path according to the dynamic weight features, or automatically print the delivery optimization label at the next delivery point of the current delivery point in the first optimal delivery path, and the second optimal delivery path includes at least a second mailing path and a second self-pickup path.

[0061] In one embodiment, a computer readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented: S10. Obtain customer order information and match the corresponding outbound goods in the established inbound warehouse management system; S20, extracting the initial weight features in the customer order information, and matching the corresponding first optimal delivery path according to the initial weight features based on the established intelligent matching model, where the first optimal delivery path includes at least a first mailing path and a first self-pickup path, and generating a visual path corresponding to the optimal delivery path in the user front-end application; S30, extracting identity features from the customer's order information, and customizing and automatically printing an initial delivery label based on the identity features and initial weight features, the initial delivery label being used to be affixed to the outbound goods; S40, real-time tracking of the transfer information of the initial delivery label, and updating the current delivery point on the visualized path in real time according to the transfer information; S50. Acquire dynamic weight features in real time in the user front-end application, match the second optimal delivery path according to the dynamic weight features, or automatically print the delivery optimization label at the next delivery point of the current delivery point in the first optimal delivery path, and the second optimal delivery path includes at least a second mailing path and a second self-pickup path.

[0062] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0063] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0064] The embodiments described above are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, a person skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. A logistics distribution management method, characterized in that: The logistics distribution management method comprises: Obtain customer order information and match the corresponding outbound goods in the established inbound warehouse management system; Extract the initial weight features in the customer order information, and based on the established intelligent matching model, match the corresponding first optimal delivery path according to the initial weight features, where the first optimal delivery path at least includes a first mailing path and a first self-pickup path, and generate a visual path corresponding to the optimal delivery path in the user front-end application; Extracting identity features from the customer order information, and customizing and automatically printing an initial delivery label based on the identity features and the initial weight features, wherein the initial delivery label is used to be affixed to the outbound goods; Tracking the transfer information of the initial delivery label in real time, and updating the current delivery point on the visualized path in real time according to the transfer information; Dynamic weight features are acquired in real time in the user front-end application, and a second optimal delivery path is matched according to the dynamic weight features, or automatic printing of a delivery optimization label is performed at the next delivery point of the current delivery point in the first optimal delivery path, wherein the second optimal delivery path includes at least a second mailing path and a second self-pickup path.

2. A logistics distribution management method according to claim 1, characterized in that: The step of matching the corresponding first optimal delivery path according to the initial weight features based on the established intelligent matching model includes: Classifying the initial weight features to generate corresponding classification packages; Based on the established intelligent matching model, assigning values ​​to each of the classification packages to obtain a first weight value of each of the classification packages; According to the classification package, a corresponding current delivery path is matched, and a path load rate of the current delivery path is determined in real time; Determining a corresponding weight load rate according to a sum of the first weight values ​​of each of the classification packets; According to the comparison result of the path load rate and the weight load rate, a corresponding first optimal delivery path is determined.

3. A logistics distribution management method according to claim 2, characterized in that: The step of matching the corresponding current delivery path according to the classification package and determining the path load rate of the current delivery path in real time includes: According to the classification package, matching the corresponding project identification; According to the project identifier, the corresponding current delivery path is selected; Determine each path item in the current delivery path and the item load rate of each path item, wherein the path items include a primary sorting item, a printing item, a secondary sorting item and a verification item, wherein the primary sorting item includes at least a sorting mail pick-up item; The item load rates of the various path items are weighted averaged to generate a corresponding path load rate.

4. A logistics distribution management method according to claim 1, characterized in that: The step of customizing the initial delivery label according to the identity feature and the initial weight feature includes: Scan and verify the product barcodes pre-attached to the outbound goods; If the scanning verification is successful, the barcode information corresponding to the product barcode in the established warehousing management system is removed from the shelf; Determine the unique code for order transfer based on the identity characteristics; Customize and automatically print the initial delivery label according to the initial weight feature and the order transfer unique code; A corresponding label attaching operation is performed, wherein the label attaching operation is used to attach the initial delivery label to the outbound goods.

5. A logistics distribution management method according to claim 1, characterized in that: The step of real-time tracking of the transfer information of the initial delivery label includes: Obtaining scan information of the initial delivery label; Determine a scanning node corresponding to the scanning information, where the scanning node is a sensor device corresponding to one of the path items of the first optimal delivery path; Corresponding transfer information is generated according to the scanning node and the scanning information.

6. A logistics distribution management method according to claim 1, characterized in that: The step of acquiring the dynamic weight feature in real time in the user front-end application, matching the second optimal delivery path according to the dynamic weight feature, or automatically printing the delivery optimization label at the next delivery point of the current delivery point in the first optimal delivery path includes: Calling corresponding order influencing factors in the user front-end application, wherein the order influencing factors include expedited requests, traffic conditions, weather changes, and order changes; Assigning weights to each of the order influencing factors to generate a second weight value, and adding the second weight values ​​to generate a corresponding dynamic weight feature; Determine whether the characteristic value corresponding to the dynamic weight characteristic exceeds the determined change threshold, and if not, continue to determine; If it exceeds, it is determined whether the second optimal delivery path can be determined according to the path load rate of the first optimal delivery path. If the second optimal delivery path is determined, a first interactive window for selecting whether to select the second optimal delivery path is pushed. If the second optimal delivery path is not determined, a second interactive window for selecting whether to automatically print the delivery optimization label at the next delivery point of the current delivery point in the first optimal delivery path is pushed.

7. A logistics distribution management device, characterized in that: The logistics distribution management device comprises: The first acquisition module is used to obtain customer order information and match the corresponding outbound goods in the established inbound warehouse management system; A first extraction module is used to extract the initial weight features in the customer order information, and based on the established intelligent matching model, match the corresponding first optimal delivery path according to the initial weight features, wherein the first optimal delivery path at least includes a first mailing path and a first self-pickup path, and generate a visual path corresponding to the optimal delivery path in the user front-end application; A second extraction module is used to extract the identity features in the customer order information, customize and automatically print the initial delivery label according to the identity features and the initial weight features, and the initial delivery label is used to be attached to the outbound goods; An updating module, used for tracking the transfer information of the initial delivery label in real time, and updating the current delivery point on the visualized path in real time according to the transfer information; The second acquisition module is used to acquire the dynamic weight characteristics in real time in the user front-end application, match the second optimal delivery path according to the dynamic weight characteristics, or automatically print the delivery optimization label at the next delivery point of the current delivery point in the first optimal delivery path, and the second optimal delivery path includes at least a second mailing path and a second self-pickup path.

8. A logistics distribution management device according to claim 7, characterized in that: The first extraction module comprises: A generating unit, used for classifying the initial weight features to generate corresponding classification packages; A first acquisition unit, configured to assign a value to each of the classification packages based on the established intelligent matching model, so as to obtain a first weight value of each of the classification packages; A matching unit, used to match the corresponding current delivery path according to the classification package, and determine the path load rate of the current delivery path in real time; A first determining unit, configured to determine a corresponding weight load rate according to a sum of first weight values ​​of each of the classification packets; A second determining unit, configured to determine a corresponding first optimal delivery path according to a comparison result between the path load rate and the weighted load rate; The matching unit comprises: A first matching subunit, configured to match a corresponding project identifier according to the classification package; A screening subunit, used to screen out the corresponding current delivery path according to the project identifier; A determination subunit is used to determine each path item in the current delivery path and the item load rate of each path item, wherein the path items include a primary sorting item, a printing item, a secondary sorting item and a verification item, wherein the primary sorting item includes at least a sorting mail pick-up item; A generating subunit, used for performing weighted averaging on the project load rates of the respective path projects to generate a corresponding path load rate; The second extraction module comprises: A scanning and verification unit, used for scanning and verifying the product barcodes pre-attached on the outbound goods; A delisting unit, used for delisting the barcode information corresponding to the product barcode in the established warehousing management system if the scanning verification is successful; A third determining unit, configured to determine an order transfer unique code according to the identity feature; A customization unit, used to customize and automatically print an initial delivery label according to the initial weight feature and the order transfer unique code; An execution unit, used to execute a corresponding label attaching operation, wherein the label attaching operation is used to attach the initial delivery label to the outbound goods; The update module includes: A second acquisition unit, used to acquire the scanning information of the initial delivery label; A fourth determining unit, configured to determine a scanning node corresponding to the scanning information, wherein the scanning node is a sensor device corresponding to one of the path items of the first optimal delivery path; A first generating unit, configured to generate corresponding transfer information according to the scanning node and the scanning information; The second acquisition module includes: A calling unit, used to call corresponding order influencing factors in the user front-end application, wherein the order influencing factors include expedited requests, traffic conditions, weather changes, and order changes; A second generating unit, configured to assign a weight to each of the order influencing factors to generate a second weight value, and add the second weight values ​​to generate a corresponding dynamic weight feature; A first judgment unit, used to judge whether the characteristic value corresponding to the dynamic weight characteristic exceeds the determined change threshold, and if not, continue to judge; The second judgment unit is used to judge whether a second optimal delivery path can be determined according to the path load rate of the first optimal delivery path if it exceeds the limit; if the second optimal delivery path is determined, a first interactive window for selecting whether to select the second optimal delivery path is pushed; if the second optimal delivery path is not determined, a second interactive window for selecting whether to automatically print a delivery optimization label at the next delivery point of the current delivery point in the first optimal delivery path is pushed.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of a logistics distribution management method as described in any one of claims 1 to 6 are implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of a logistics distribution management method as described in any one of claims 1 to 6 are implemented.

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