A logistics distribution management method, device, equipment and medium

Abstract

The present application relates to a logistics distribution management method, device, equipment and medium. A logistics distribution management method includes extracting initial weight features in customer order information, matching a corresponding first optimal distribution path based on a well-established intelligent matching model, and generating a visual path corresponding to the optimal distribution path; extracting identity features in customer order information, customizing and automatically printing initial distribution labels, and real-time updating the current distribution point on the visual path; obtaining dynamic weight features in real time in the user front-end application, matching a second optimal distribution path according to the dynamic weight features, or automatically printing optimized distribution labels at the next distribution point of the current distribution point in the first optimal distribution path, and automatically matching the optimal distribution path through the intelligent matching model, improving the distribution efficiency, and adjusting the distribution plan by extracting dynamic weight features. It can ensure that the distribution can still proceed smoothly even when the external environment changes.

Description

Technical Field

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

[0002] Currently, in the jewelry industry, logistics management is a 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 usually have high value and strict requirements for the accuracy and safety of distribution. However, traditional logistics management methods generally have problems such as low distribution efficiency, high error rate, and lack of transparency in the logistics progress of customer orders, making it difficult to meet the needs of the jewelry industry in terms of 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.

[0003] To address these pain points, the jewelry industry urgently needs an efficient and intelligent logistics management system to improve distribution efficiency, reduce error rate, and enhance the customer experience. Traditional logistics management methods lack intelligent path planning and flexible distribution plans, and are unable to track and adjust distribution paths in real time, resulting in the inability to make full use of existing resources in complex logistics environments. In addition, under the traditional model, the logistics progress often lacks transparency, and customers cannot understand the logistics information in real time, causing unnecessary anxiety and dissatisfaction. Summary of the Invention

[0004] In order to solve the problems of low distribution efficiency, high error rate, and lack of transparency in the logistics progress of customer orders commonly existing in traditional logistics management methods, the present application provides a logistics distribution management method, device, equipment and medium.

[0005] The first above-mentioned invention object of the present application is achieved through the following technical solutions:

[0006] A logistics distribution management method, the logistics distribution management method includes:

[0007] Obtain customer order information, and match the corresponding outbound goods in the established inbound management system;

[0008] Extract the initial weight features in the customer order information, and based on the established intelligent matching model, match the corresponding first optimal distribution path according to the initial weight features. The first optimal distribution path includes at least a first mailing path and a first self-pickup path, and generate a visual path corresponding to the optimal distribution path in the user front-end application.

[0009] Extract the identity features in the customer's order information, and customize and automatically print the initial delivery label according to the identity features and the initial weight features, where the initial delivery label is used to be pasted on the goods to be shipped out;

[0010] Track the transfer information of the initial delivery label in real time, and update the current delivery point on the visual path in real time according to the transfer information;

[0011] Obtain the dynamic weight features in the user front-end application in real time, 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, where the second optimal delivery path includes at least a second mailing path and a second self-pickup path.

[0012] By adopting the above technical solutions, by obtaining the customer's order information and matching the corresponding goods to be shipped out in combination with the warehousing management system, the need for manual operations is reduced, and the automated outbound process can be accurately carried out. Through the intelligent matching model, the system can automatically match the optimal delivery path according to the initial weight features (such as order urgency, customer requirements, logistics resources, etc.). This intelligent delivery path planning can fully consider the adaptability of different delivery methods, thus greatly improving the delivery efficiency and effectively reducing the probability of human errors; by generating a visual path corresponding to the optimal delivery path in the user front-end application, this problem is solved. Customers can view the logistics status in real time and track the progress of the delivery at any time. This transparency not only improves the customer experience but also provides more data support for logistics management, enabling the timely identification and correction of any potential delivery deviations; in the traditional logistics process, path planning is often static and difficult to cope with changes 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.), updating the delivery path in real time according to these changes, and being able to automatically print the delivery optimization label to further adjust the delivery plan. By obtaining these dynamic features in real time and adjusting the delivery plan accordingly, it can ensure that the delivery can still proceed smoothly even when the external environment changes, thus avoiding the common delays and delivery errors in the traditional mode.

[0013] In a preferred example of this application, it can be further configured that: in the step of matching the corresponding first optimal delivery path according to the initial weight features based on the established intelligent matching model, it includes:

[0014] Classify the initial weight features to generate corresponding classification packages;

[0015] Based on the established intelligent matching model, assign values to each of the classification packages to obtain the first weight value of each classification package;

[0016] According to the classification package, match the corresponding current delivery route, and determine the route load rate of the current delivery route in real time;

[0017] Determine the corresponding weight load rate according to the sum of the first weight values of each classification package;

[0018] Determine the corresponding first optimal delivery route according to the comparison result of the route load rate and the weight load rate.

[0019] By adopting the above technical solution, it is possible to classify the initial weight features and assign weight values to each classification package, effectively matching the customer needs with the characteristics of the delivery route. The creation and assignment process of the classification package ensures that the selection of the delivery route can be dynamically adjusted according to the priority needs of different customers (such as urgent orders, special requirements, etc.). By calculating the weight values of each classification package and merging them, the load situation of each route can be evaluated in real time, ensuring that the load capacity of the logistics network matches the customer needs and avoiding delivery delays or errors caused by overloading. By comparing the route load rate and the weight load rate, the system can optimize the route selection, finally determine the first optimal delivery route, thereby improving the delivery efficiency, ensuring the timely and accurate completion of order delivery, and at the same time enhancing the utilization rate of resources and the overall scheduling ability of the system.

[0020] In a preferred example of the present application, it can be further configured that: in the step of matching the corresponding current delivery route according to the classification package and determining the route load rate of the current delivery route in real time, it includes:

[0021] According to the classification package, match the corresponding project identifier;

[0022] According to the project identifier, screen out the corresponding current delivery route;

[0023] Determine each route item in the current delivery route and the project load rate of each route item. The route items include a primary sorting item, a printing item, a secondary sorting item, and a verification item, where the primary sorting item at least includes a sorting and mailing self-pickup item;

[0024] Perform a weighted average of the project load rates of each route item to generate the corresponding route load rate.

[0025] By adopting the above technical solution, it is possible to accurately match the corresponding current delivery route according to the item identifier in the classification package, and further screen out the delivery routes related to the item identifier. Each delivery route consists of multiple route items, such as primary sorting, labeling, secondary sorting, and verification, etc. These route items involve different logistics operation links and resource allocations. By evaluating the item load rate of each route item in detail, it is possible to monitor the load status of each link in real time, thereby reflecting the carrying capacity of the overall delivery route. The primary sorting item, labeling item, secondary sorting item, and verification item are given different load values according to their respective workloads and required resources. Finally, by calculating the weighted average of the load rates of these items, the system can comprehensively consider the load conditions of each link and generate an accurate route load rate. The calculation result of this load rate helps the system dynamically adjust the delivery route to ensure that each route is within the optimal load range, thereby improving the delivery efficiency, avoiding excessive congestion or resource waste, and ensuring the smoothness of the logistics delivery process.

[0026] In a preferred example of the present application, it can be further configured that: in the step of customizing the initial delivery label according to the identity feature and the initial weight feature, it includes:

[0027] Scan and verify the goods barcode pre-stuck on the outbound goods;

[0028] If the scan verification is successful, then remove the barcode information corresponding to the goods barcode in the established inbound management system from the shelves;

[0029] Determine the unique order transfer code according to the identity feature;

[0030] Customize and automatically print the initial delivery label according to the initial weight feature and the unique order transfer code;

[0031] Execute the corresponding label pasting operation, and the label pasting operation is used to paste the initial delivery label on the outbound goods.

[0032] By adopting the above technical solutions, during the process of customizing the initial distribution label, the barcode on the goods to be shipped can be scanned and verified first to ensure the consistency between the barcode and the goods, reducing the occurrence of human errors. If the scan verification is successful, the system will automatically remove the corresponding inventory information from the shelves 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 transfer unique code for each order, thus ensuring that each piece of goods can be uniquely identified and tracked in the system. By combining the order transfer unique code and the initial weight characteristics, the system can customize the initial distribution label to ensure that the label content is accurate and meets the logistics requirements. Finally, the system automatically prints and performs the label pasting operation, accurately pasting the initial distribution label on the goods to be shipped to ensure the correct identification and tracking of each package during the distribution process. The automated design of this process improves work efficiency, reduces the error rate of manual intervention, and ensures the information flow and transparency during the entire logistics distribution process.

[0033] In a preferred example of this application, it can be further configured as follows: in the step of real-time tracking the transfer information of the initial distribution label, it includes:

[0034] Obtain the scan information of the initial distribution label;

[0035] Determine the scan node corresponding to the scan information, where the scan node is a sensing device corresponding to one of the path items of the first optimal distribution path;

[0036] Generate corresponding transfer information according to the scan node and the scan information.

[0037] By adopting the above technical solutions, during the process of real-time tracking the transfer information of the initial distribution label, the corresponding scan information can be obtained by scanning the initial distribution label to ensure that the tracking data of each piece of goods is transmitted to the system in real time and accurately. The system identifies the corresponding scan node according to the scan information, and the scan node corresponds to a sensing device in a specific link of the distribution path, such as sensors in a logistics center, sorting station or transport vehicle, etc. By processing these scan nodes and scan information, the system can automatically generate detailed transfer information and update it in the distribution path in a timely manner to ensure 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 queries, thereby improving the management efficiency and accuracy of the entire logistics distribution process.

[0038] In a preferred example, the present application can be further configured as follows: in the user front-end application, real-time acquisition of dynamic weight features, matching the second optimal delivery route according to the dynamic weight features, or in the step of automatically printing a delivery optimization label at the next delivery point of the current delivery point in the first optimal delivery route, includes:

[0039] Call corresponding order influencing factors in the user front-end application, and the order influencing factors include urgent requests, traffic conditions, weather changes, and order changes;

[0040] Assign weights 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;

[0041] Judge whether the eigenvalue corresponding to the dynamic weight feature exceeds a determined change threshold. If it does not exceed, continue to judge;

[0042] If it exceeds, judge whether a second optimal delivery route can be determined according to the path load rate of the first optimal delivery route. If the second optimal delivery route is determined, push a first interaction window for whether to select the second optimal delivery route. If the second optimal delivery route cannot be determined, push a second interaction window for whether to select to automatically print a delivery optimization label at the next delivery point of the current delivery point in the first optimal delivery route.

[0043] By adopting the above technical solution, it is possible to acquire and analyze dynamic weight features in real time in the user front-end application, ensuring that the delivery route can flexibly adapt to changes in order requirements. The system first evaluates the impact of these factors on the delivery route in real time by calling order influencing factors (such as urgent requests, traffic conditions, weather changes, and order changes). Then, weights are assigned to each order influencing factor to generate a second weight value, and all weight values are added together to obtain the final dynamic weight feature. By this method, the system can dynamically adjust the delivery route based on real-time order changes. When the change in the dynamic weight feature exceeds a preset change threshold, the system will judge whether it is necessary to determine a second optimal delivery route according to the path load rate of the first optimal delivery route. If the second optimal route can be determined, the system will push an interaction window for the user to choose whether to adopt this route; if the second optimal route cannot be determined, the system will push an interaction window to prompt the user whether to choose to automatically print a delivery optimization label at the next delivery point of the current delivery route. This flexible adjustment mechanism can effectively cope with external factor changes, improve flexibility and timeliness in the delivery process, and enhance the customer experience at the same time.

[0044] The above second invention object of the present application is achieved by the following technical solutions:

[0045] A logistics distribution management device, the logistics distribution management device includes:

[0046] A first acquisition module, configured to acquire customer order information and match corresponding outbound goods in the established inbound management system;

[0047] A first extraction module, configured to extract initial weight features in the customer order information, and based on the established intelligent matching model, match a corresponding first optimal distribution path according to the initial weight features. The first optimal distribution path includes at least a first mailing path and a first self-pickup path, and generate a visual path corresponding to the optimal distribution path in the user front-end application;

[0048] A second extraction module, configured to extract identity features in the customer order information, and customize and automatically print a distribution initial label according to the identity features and the initial weight features. The distribution initial label is used to be pasted on the outbound goods;

[0049] An update module, configured to track the transfer information of the distribution initial label in real time, and update the current distribution point on the visual path in real time according to the transfer information;

[0050] A second acquisition module, configured to acquire dynamic weight features in real time in the user front-end application, match a second optimal distribution path according to the dynamic weight features, or automatically print a distribution optimization label at the next distribution point of the current distribution point in the first optimal distribution path. The second optimal distribution path includes at least a second mailing path and a second self-pickup path.

[0051] The above object three of the present application is achieved by the following technical solutions:

[0052] A computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the above-mentioned logistics distribution management method are implemented.

[0053] The above object four of the present application is achieved by the following technical solutions:

[0054] A computer-readable storage medium, the 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.

[0055] In summary, the present application includes at least one of the following beneficial technical effects:

[0056] 1. By obtaining customer order information and matching the corresponding outbound goods through the warehousing 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 route based on initial weight features such as order urgency, customer requirements, and logistics resources. This intelligent delivery route planning can fully consider the adaptability of different delivery methods, thus greatly improving the delivery efficiency and effectively reducing the probability of human errors;

[0057] 2. This problem is solved by generating a visual route corresponding to the optimal delivery route in the user front-end application. Customers can view the logistics status in real time and track the progress of the delivery at any time. This transparency not only improves the customer experience but also provides more data support for logistics management, enabling the timely identification and correction of any potential delivery deviations;

[0058] 3. In the traditional logistics process, route planning is often static and difficult to cope with changes 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 the delivery optimization label 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 the delivery can still proceed smoothly even when the external environment changes, thus avoiding common delays and delivery errors in the traditional mode. Brief Description of the Drawings

[0059] Figure 1 is a flowchart of a logistics distribution management method in an embodiment of the present application.

[0060] Figure 2 is a flowchart for implementing step S20 in a logistics distribution management method in an embodiment of the present application;

[0061] Figure 3 is a flowchart for implementing step S203 in a logistics distribution management method in an embodiment of the present application;

[0062] Figure 4 is a flowchart for implementing step S30 in a logistics distribution management method in an embodiment of the present application;

[0063] Figure 5 is a flowchart for implementing step S40 in a logistics distribution management method in an embodiment of the present application;

[0064] Figure 6 is a flowchart for implementing step S50 in a logistics distribution management method in an embodiment of the present application;

[0065] Figure 7 It is a principle block diagram of a logistics distribution management device in an embodiment of the present application;

[0066] Figure 8 It is a schematic diagram of the device in an embodiment of the present application. Specific embodiments

[0067] The present application will be further described in detail below with reference to the accompanying drawings.

[0068] In one embodiment, as Figure 1 shown, the present application discloses a logistics distribution management method, which specifically includes the following steps:

[0069] S10. Obtain customer order information and match the corresponding outbound goods in the established inbound management system; in this embodiment, obtaining customer order information means that after the customer submits an order through the e-commerce platform, the system extracts the detailed information related to the order. This information includes the types, quantities, delivery addresses, customer requirements, etc. of the goods. By matching the corresponding outbound goods from the inbound management system, the system can automatically select the suitable goods in the inventory according to the specific requirements in the customer 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 of goods, avoiding incorrect deliveries caused by 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 for delivery.

[0070] S20. 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. The first optimal delivery path includes at least 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; in this embodiment, extracting the initial weight features in the customer order information means that the system extracts the 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 time limit 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 one mailing path and one self-pickup path. According to the customer's choice, the system can flexibly provide the optional paths of the two delivery methods for the customer. The system will generate and display the visual path corresponding to the first optimal delivery path in real time in the user front-end application, enabling the customer to intuitively understand the delivery progress of their order. Specifically, if the order requires urgency, 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.

[0071] S30. Extract the identity features in the customer's order placement information. Based on the identity features and the initial weight features, customize and automatically print the initial delivery label, which is used to be attached to the goods out of the warehouse. In this embodiment, extracting the identity features in the customer's order placement 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 features are not only a code for identifying the customer, but may also involve information such as the customer's historical purchase records and loyalty levels. Based on the customer's identity features and the initial weight features, the system will customize and automatically print the initial delivery label for this order. The initial delivery label will contain key information such as product information, customer information, delivery route, and estimated arrival time, and will be attached to the goods out of the warehouse. The technical effect of this step is to automatically generate and attach the delivery label, which not only improves the operation 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 a higher delivery priority to their order according to the customer's identity features and generate a special delivery label for this order.

[0072] S40. Real-time track the transfer information of the initial delivery label. According to the transfer information, real-time update the current delivery point on the visual path. In this embodiment, real-time tracking the transfer information of the initial delivery label means tracking the transportation process of the goods in real time by scanning the initial delivery label (such as a barcode or RFID tag). Whenever the goods pass through a key transfer node, the system will obtain the transfer information by scanning the sensing devices at the node (such as RFID readers, barcode scanners, etc.) and feed this information back to the system in a timely manner. The system updates the current delivery point on the visual path through the transfer information to ensure that users 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, increasing the transparency of the delivery process and allowing customers to know the progress of the order at any time. For example, assume that the order is passing through multiple sorting centers and delivery stations. The system will dynamically update each station that the goods pass through in the user's application until it is finally delivered to the customer.

[0073] S50. Obtain dynamic weight features in real time in the user front-end application, match the second optimal delivery route according to the dynamic weight features, or automatically print a delivery optimization label at the next delivery point of the current delivery point in the first optimal delivery route. The second optimal delivery route includes at least a second mailing route and a second self-pickup route. In this embodiment, obtaining dynamic weight features in real time 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 urgent requests, etc.) during the delivery process. These dynamic weight features will be reflected in the selection of the delivery route according to the actual situation. The system matches the second optimal delivery route according to these real-time changes, or in the first optimal delivery route, automatically prints a delivery optimization label according to the next delivery point of the current delivery point. The second optimal delivery route includes a second mailing route and a second self-pickup route, mainly used to cope with unforeseen situations such as traffic congestion and weather changes, ensuring that the order can be delivered on time. The technical effect of this step is to flexibly cope with unexpected situations during the delivery process and adjust the delivery route in real time to ensure the shortest delivery time and the most efficient route. For example, in some emergencies (such as bad weather or traffic accidents), the system will automatically calculate the second optimal route and notify the customer of the latest delivery information or choose whether to continue to optimize the route to avoid delays or incorrect deliveries.

[0074] In summary, by obtaining customer order information and matching the corresponding outbound goods in combination with the warehousing 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 route according to the initial weight features (such as order urgency, customer requirements, logistics resources, etc.). This intelligent delivery route planning can fully consider the adaptability of different delivery methods, thus greatly improving the delivery efficiency and effectively reducing the probability of human errors; by generating a visual route corresponding to the optimal delivery route in the user front-end application, this problem is solved. Customers can view the logistics status in real time and track the progress of the 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; in the traditional logistics process, route planning is often static and difficult to cope with changes during delivery, such as traffic congestion, sudden weather changes, or other unforeseen factors. By extracting dynamic weight features (such as traffic conditions, order changes, customer feedback, etc.), updating the delivery route in real time according to these changes, and being able to automatically print a delivery optimization label to further adjust the delivery plan. By obtaining these dynamic features in real time and adjusting the delivery plan accordingly, it can be ensured that even when the external environment changes, the delivery can still proceed smoothly, thus avoiding common delays and delivery errors in the traditional mode.

[0075] In one embodiment, as Figure 2 shown, in step S20, that is, in the step of matching the corresponding first optimal delivery route according to the initial weight features based on the established intelligent matching model, it includes:

[0076] 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 demand, the order amount, the commodity type, the delivery time limit requirement, etc.). These features may involve different dimensions of the order, and the system will divide the order into different classification packages according to these features. Each classification package represents a type of order with similar delivery requirements. For example, for urgent orders, regular orders, and reserved orders, the system will put them into different classification packages respectively. The technical effect of this step is to be able to establish a clear feature model 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 requirements, improving the overall logistics response ability and accuracy.

[0077] S202. Based on the established intelligent matching model, assign values to each classification package to obtain the first weight value of each classification package; in this embodiment, assigning values to each classification package based on the established intelligent matching model means that the system assigns a first weight value to each classification package according to the features of each classification package by using an intelligent matching model (such as a machine learning model, a rule engine, etc.). This weight value reflects the priority and delivery requirements of this classification package in the overall delivery route. The intelligent matching model will calculate according to the actual business rules, historical data, and the dynamic requirements of the current order to generate a weight value suitable for the current classification package. Specifically, if an order belongs to the urgent delivery category, the system will assign a higher weight value to this classification package to ensure that the order can be given priority in delivery. The technical effect of this step is to reasonably allocate the delivery priority of each classification package by assigning weights, thereby providing a scientific basis for the optimal path selection.

[0078] 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 requirements represented by each classification package. The intelligent matching model will assign values according to these requirements to determine the weight value of each classification package. This assignment process is based on a data-driven approach, and the priority, timeliness of orders and special requirements of customers are processed through a combination of algorithms and rules. 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 requirements of the customer (such as whether it is urgent), the distance to the destination, the selection of the delivery time period, etc. Each characteristic will be assigned a specific numerical value according to the preset business rules and historical data, and these numerical values reflect the degree of influence of each characteristic on the delivery route. For example, if an order belongs to the urgent delivery category, the system will assign a higher weight value to this classification package to ensure that its delivery route can be processed preferentially. On the other hand, for orders with regular delivery, the weight value is relatively low, and the system may choose a more standard delivery route. In addition, the intelligent matching model will also consider the volume and weight of the order. If the order is for large commodities, the system will allocate more delivery resources or preferentially select a suitable transportation method to ensure that the delivery is not restricted by the physical attributes of the goods. The calculation of the first weight value not only depends on static data but also combines real-time data for dynamic adjustment. For example, during peak hours, the selection of the 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 situation. This dynamic assignment of the weight value can ensure that the order can select the most suitable delivery route in different situations, thus optimizing the delivery timeliness and resource utilization. Once the weight values of each classification package are assigned, the system can optimize and match the subsequent delivery routes based on these weight values, thus realizing intelligent and efficient logistics management.

[0079] S203. Match the corresponding current delivery route according to the classification package, and determine the route load rate of the current delivery route in real time. In this embodiment, matching the corresponding current delivery route according to the classification package means that the system uses the classification package information with assigned weight values to match the most suitable delivery route. The characteristics of each classification package determine the suitable delivery route. For example, urgent orders may require a faster express delivery method, while regular orders can choose the standard delivery route. The system will combine the route resources and delivery requirements in the current delivery network to select the most suitable delivery route for each classification package. In addition, determining the route load rate of the current delivery route in real time means that the system will monitor and calculate the load situation of each delivery route in real time. The route load rate reflects the usage of transportation resources on the current route, such as whether there are high-density delivery tasks or whether there are sufficient resources to handle new delivery requirements. The technical effect of this step is that by monitoring the route load in real time, the system can dynamically adjust the delivery route according to the actual situation of resources, avoiding delays or delivery errors caused by overloaded routes.

[0080] Specifically, the process of determining the route load rate of the current delivery route in real time mainly involves monitoring and analyzing the resource usage of each link on the delivery route, so as to evaluate the bearing capacity of the route and the utilization rate of transportation resources. Specifically, the route load rate is calculated based on the dynamic data in the actual transportation process, involving multiple factors such as transportation capacity, current task quantity, delivery time window, traffic conditions, etc. The system continuously adjusts the evaluation of the route load by collecting these data in real time to ensure the effectiveness of the route and the reasonable allocation of resources.

[0081] First, the system will obtain the usage of transportation resources for each delivery route in real time. These resources include vehicles, delivery staff, warehouse capacity, transportation tools, etc. By integrating with other data in the logistics management system, the system can understand the quantity and load of the resources already 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 situation of this route based on this information. The higher the load rate, the closer the resource usage on this 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. Under 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 delivery time and resource consumption. By analyzing these external data in real time, the system can effectively predict the feasibility of the route and the resource requirements, so as to adjust the load rate in a timely manner and avoid continuing to allocate more orders when the route load is too high, thus causing delivery delays or resource waste. 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 route load calculation, especially when the route involves multiple delivery items, such as sorting, printing, and packaging. The increase in these workloads will affect the load of the route. The system updates the route 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 this node and may dispatch more resources or adjust the route. Finally, all of these data - including transportation resources, traffic and weather impacts, workloads of each link, etc. - will be aggregated into the system, and the system will perform a weighted analysis on them to calculate the final route load rate. The value of this load rate can reflect the current resource usage situation of the route in real time, providing an important basis for subsequent delivery route optimization and resource adjustment. If the load rate of a certain route is too high, the system will prompt the dispatcher or automatically select other routes to avoid over-concentration of resources, thus ensuring the smooth and efficient delivery process. In short, determining the route load rate of the current delivery route in real time is calculated by dynamically monitoring the resource usage of each link, the changes in real-time external factors, and the workloads during the transportation process. Through this comprehensive analysis, the system can evaluate the route load status in real time, ensure the reasonable allocation of delivery resources, and avoid delays or resource waste during the delivery process.

[0082] 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 based on the weight value of each classification package. This load rate reflects the priority and resource requirements of all classification packages on the delivery path. The weight load rate is obtained by summing up the weight values of each classification package, which can comprehensively reflect the impact of different order requirements on the delivery path. For example, if a delivery path involves multiple high-priority orders (such as urgent orders), the weight load rate of this path is relatively high, indicating that the system will give priority to processing 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 a basis for the system to evaluate whether different paths are suitable for the current order requirements, thus achieving a more accurate path selection.

[0083] 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 judge 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 the selection of a path that not only meets the order priority requirements but also can reasonably allocate resources. For example, if the load rate of a path is relatively 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 situation of the path, the system can ensure the optimal utilization of delivery resources, while ensuring that customer orders can be delivered on time and accurately, improving the efficiency and response ability of the overall logistics system.

[0084] In one embodiment, as Figure 3 shown, in step S203, that is, in 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, it includes:

[0085] S2031. Match the corresponding item identifier according to the classification package. In this embodiment, matching the corresponding item identifier according to the classification package means that the system assigns a unique item identifier to each order based on the order characteristics and requirements obtained through the classification package previously. This item identifier is used to distinguish different delivery tasks and routes and can be accurately matched with the corresponding delivery items. The item identifier can represent each link in the delivery process, such as sorting, packaging, shipping, etc. The task volume, priority, and resource requirements of each link can be tracked and managed through this identifier. Specifically, if an order needs to be processed preferentially or contains multiple tasks (such as mailing and self-pickup), the system will assign corresponding identifiers to these orders for tracking and adjusting the delivery route in subsequent steps.

[0086] S2032. Filter out the corresponding current delivery route according to the item identifier. In this embodiment, filtering out the corresponding current delivery route according to the item identifier means that the system determines the current delivery route where the order is located through the item identifier. Each item identifier is associated with a specific delivery route, and these routes usually consist of multiple links, such as sorting, transportation, delivery, etc. By analyzing the item identifier, the system can filter out the corresponding current delivery route to ensure that each order can be delivered according to the predetermined route. For example, if an order belongs to an urgent delivery task, the system will filter out a fast delivery route suitable for this urgent task; if it is an ordinary order, the system will select a standard delivery route. This step ensures that the system can dynamically match the most suitable delivery route for the current order requirements.

[0087] S2033. Determine each path item in the current delivery route and the item load rate of each path item. The path items include the first sorting item, the printing item, the second sorting item, and the verification item, where the first sorting item at least includes sorting mailing and self-pickup items. In this embodiment, determining each path item in the current delivery route and the item load rate of each path item means that the system calculates the load rate of each path item by analyzing each link of the current delivery route in detail. The path items include but are not limited to the first sorting item, the printing item, the second sorting item, and the verification item, where the first sorting item at least includes sorting mailing and self-pickup items. Each path item has different workloads and resource requirements, so the system needs to assign a load value to each item according to the actual situation. For example, the first sorting item may involve a large amount of item classification and packaging operations, with a relatively high load rate; while the printing item may mainly involve commodity label printing, with a lower load. By accurately evaluating the load rate of each path item, the system can understand the resource usage of each link on the delivery route in real time to ensure that each link in the entire delivery process can be reasonably allocated resources.

[0088] Specifically, the first sorting project is specifically to distinguish orders that need to be typed and printed, orders lacking external factory goods, and orders with complete mailed / pick-up goods. Among them, after the first sorting of orders that need to be typed and printed, the scanned transfer form of the typing and printing project can be used to burn the typing and printing. And after the first sorting of orders lacking external factory goods, the data of external factory goods is exported (the external factory delivers goods to the platform based on this data). After the external factory goods are received, the barcode of the goods is scanned to automatically match the order, and the app synchronizes the shipment status (warehousing + goods allocation). Then, the goods allocation and outbound order form is exported (to verify whether the weight and processing fee are consistent with those provided by the manufacturer, and this comparison data comes from the data when the goods are created). Moreover, in the step of scanning the barcode of the goods to automatically match the order and the app synchronizing the shipment status (warehousing + goods allocation), it can also be divided into the warehousing and goods allocation of external factory goods, which are uniformly warehoused and allocated according to one factory and one batch. Then, the goods are automatically matched with the order and a goods allocation and warehousing prompt is given. The goods allocation and warehousing prompt can be: First, the first scan (this goods is the first piece of goods of this order from this external factory); Second, already existing in the waiting area for goods allocation and complete set (there are other goods from this external factory for this order besides this piece of goods); Third, the order is not complete set, but the factory is complete set (the goods of this order from this external factory are already complete); Fourth, the order is complete set (the goods of this order are already complete). Moreover, in the second sorting project, it can be directly seen whether the goods of the order are allocated and completed.

[0089] After the goods allocation and outbound order form is exported, it can continue to the second sorting project to sort orders that need tags, orders that need boxes, and orders that need certificates. Among them, after the first sorting of orders with complete mailed / pick-up goods, it also directly goes to the second sorting project. If it is to sort an order that needs a tag, an automatically generated tag number is printed (the data is synchronized with the certificate institution through an interface), and then the transfer form and the barcode of the goods are scanned (to check the certificate / tag, matching). If it is to sort an order that needs a box, a sorting batch form is generated, and then the transfer form and the barcode of the goods are scanned (to check the certificate / tag, matching). If it is to sort an order that needs a certificate, a production batch form is generated (synchronize with the certificate institution for production and receipt of goods), and then the transfer form and the barcode of the goods are scanned (to check the certificate / tag, matching). After scanning the transfer form and the barcode of the goods (to check the certificate / tag, matching), the data is automatically compared for consistency. Then, a judgment is made on the mailed / pick-up form generated after the first sorting. If it is for pick-up, the user clicks manually / automatically generates a pick-up code after 6 minutes (synchronized to the customer's account). If it is for mailing, the express delivery form is automatically printed and the app synchronizes the logistics status, and then it is packed and waiting for the courier to pick up;

[0090] Among them, all steps of verifying whether the weight and processing fee are consistent with those provided by the manufacturer, and this comparison data comes from the data when the goods are created, checking the certificate / tag, matching, etc. are verification items, and the app mentioned above is the so-called user front-end application.

[0091] S2034. Weight-average the item load rates of each path item to generate the corresponding path load rate. In this embodiment, weight-averaging the item load rates of each path item to generate the corresponding path load rate means that the system calculates the weighted load rates of each path item to obtain a comprehensive path load rate. The load rate of each path item is weighted according to the proportion of resources it occupies in the entire distribution process. For example, the sorting item has a larger workload, so its load rate has a higher weight; while the labeling item has a smaller workload and a lower weight. By weight-averaging the load rates of each path item, the system can obtain an accurate path load rate, thereby evaluating whether the distribution path is suitable for the current resource requirements. If the path load rate is too high, the system can choose to adjust the distribution plan to avoid delays and resource waste 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, improving the distribution efficiency and accuracy.

[0092] In one embodiment, as Figure 4 shown, in step S30, that is, the step of customizing the initial distribution label according to the identity feature and the initial weight feature, includes:

[0093] S301. Scan and verify the product barcode pre-stuck on the outbound goods; in this embodiment, scanning and verifying the product barcode pre-stuck on the outbound goods means that the system scans the barcode or QR code on the product to verify whether the product is consistent with the order information. The barcode contains the unique identifier of the product, 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 operations or label errors. For example, when a piece of jewelry product is scanned, the system retrieves 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 product as confirmed and ready for subsequent processing. The technical effect of this step is to improve the accuracy of goods outbound, reduce human errors, and ensure the smooth progress of each distribution link.

[0094] S302. If the scan verification is successful, then remove the barcode information corresponding to the goods barcode in the established warehousing management system. In this embodiment, if the scan verification is successful, then removing the barcode information corresponding to the goods barcode in the established warehousing management system means that after the barcode scan 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 goods turnover. Through the automatic removal operation, the system avoids the cumbersome operation of manually recording and updating inventory information and reduces the error probability of manual intervention. For example, if a commodity has been shipped from the warehouse, the system will automatically reduce the corresponding inventory quantity according to the scan information to maintain the real-time accuracy of the inventory information. The technical effect of this step is to ensure the immediacy and accuracy of the inventory data and the efficiency of supply chain management.

[0095] S303. Determine the unique order transfer code according to the identity characteristics. In this embodiment, determining the unique order transfer code according to the identity characteristics means that the system generates a unique "order transfer unique code" based on the customer's identity characteristics (such as customer ID, account information, or other identity recognition data). This unique code is the only identifier for each order during the distribution process and is used to track the transfer status of the order. The system combines the identity characteristics with other order information (such as goods, delivery address, time, etc.) to automatically generate this unique code for each order. Specifically, in the jewelry industry, a customer's order may contain multiple goods, and the delivery routes of each good may be different. Through the order transfer unique code, the system can accurately track the delivery progress of each good and avoid confusion or loss of goods in the same order. The technical effect of this step is to provide a fully traceable identifier for each order, improving the accuracy and transparency of logistics tracking.

[0096] S304. Customize and automatically print the initial delivery label according to the initial weight characteristics and the unique order transfer code. In this embodiment, customizing and automatically printing the initial delivery label according to the initial weight characteristics and the unique order transfer code means that the system automatically generates and prints the initial delivery label based on the initial weight characteristics (such as order urgency, customer level, delivery priority, etc.) in the customer order and the unique order transfer code. The initial label usually includes information such as product information, delivery route, customer information, estimated delivery time, barcode, etc. After these labels are attached to the goods leaving the warehouse, 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 (for example, orders with high priority or urgent orders). Specifically, if a jewelry order is marked as high priority, the system will automatically indicate this on the label and arrange for priority delivery. The technical effect of this step is to improve the automation level of logistics management, reduce errors and delays in manual operations, and ensure efficient and accurate delivery arrangements.

[0097] S305. Perform the corresponding label affixing operation, which is used to affix the initial delivery label to the goods leaving the warehouse. In this embodiment, performing the corresponding label affixing operation, which is used to affix the initial delivery label to the goods leaving the warehouse means that after the initial delivery label is printed, the system automatically attaches the label to the goods. The label affixing operation is not only a physical label affixing process but also involves ensuring the accurate matching of each label with the corresponding goods. Through the automated affixing operation, the system can ensure that the label is correctly and tightly attached to each item, avoiding problems such as label loosening and misalignment. For example, in the jewelry industry, since the products are often small and delicate, the system will accurately affix 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 delivery efficiency, ensure that each product can be accurately identified and tracked during the delivery process, and avoid logistics problems and customer complaints caused by incorrect labels.

[0098] In one embodiment, as Figure 5 shown, in step S40, that is, the step of real-time tracking the transfer information of the initial delivery label, includes:

[0099] S401. Obtain 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, barcodes, QR codes, etc., which are used to identify the goods and track the logistics status. By scanning this label, the system can read out key information such as the unique identifier of the goods, the starting location, and the target location, and transmit this data to the back-end system to ensure subsequent logistics tracking and updating. 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 result to the system, so that the system can timely record the transfer status and path of each piece of goods. The technical effect of this step is to provide real-time goods tracking ability, provide data support for subsequent delivery path optimization and scheduling, and ensure the transparency and accuracy of the logistics process.

[0100] S402. Determine the scanning node corresponding to the scanning information, where the scanning node is a sensing device corresponding to one of the path items of the first optimal delivery path; in this embodiment, determining the scanning node corresponding to the scanning information means that the system determines a key node in the delivery path corresponding to the information obtained from the scanning device according to the information on the initial delivery label. This node is called the "scanning node", which is a specific point on the delivery path and is usually a place where data is collected in real time by an associated sensing device. The scanning node can be a scanning point in the logistics center, an inspection station in the distribution station, an RFID reader on the transport vehicle, etc., any device that can read and confirm the current location of the goods. In practical applications, if the goods pass through a checkpoint and the scanner scans the label, the system can automatically confirm the association between the scanning information and the data of this site. Specifically, if there are multiple sorting stations on the delivery path of a certain jewelry item, 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 piece of scanning data can be associated with the correct path node, so that the logistics information can be accurately transferred and recorded.

[0101] S403. Generate corresponding transfer information based on the scanned nodes and scanning information. In this embodiment, generating corresponding transfer information based on the scanned nodes and scanning information means that the system generates transfer information associated with the node according to the scanned nodes and the initial delivery label information scanned. These transfer information include 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 route. For example, when the goods are scanned at a sorting station, the system generates transfer information including the information of the station, timestamp, and the status of the goods, and stores it in the database for subsequent route update and customer query. The transfer information not only reflects the physical location of the goods but also includes the execution status of each key link on the route, such as whether the sorting is completed and whether the transportation vehicle is ready. Specifically, assuming a jewelry order is scanned out of the warehouse, the system generates the current transfer information of the order and updates it in real time to the logistics progress of the user. The technical effect of this step is that through the real-time generation and update of transfer information, the system can accurately track the status of each delivery node, improve the traceability and transparency of the delivery route, provide more efficient services for customers, and also help optimize the resource scheduling in the logistics process.

[0102] In one embodiment, as Figure 6 shown, in step S50, that is, in the user front-end application, real-time obtain dynamic weight features, and match the second optimal delivery route according to the dynamic weight features, or in the step of automatically printing the delivery optimization label at the next delivery point of the current delivery point in the first optimal delivery route, it includes:

[0103] S501. Call the corresponding order influencing factors in the user front-end application. The order influencing factors include urgent requests, traffic conditions, weather changes, and order changes. In this embodiment, calling the corresponding order influencing factors in the user front-end application means that the system obtains the 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, urgent requests, traffic conditions, weather changes, and order changes. An urgent request may mean that the order needs to be delivered preferentially. Traffic conditions and weather changes will directly affect the selection and timeliness of the delivery route. Order changes may be due to changes in customer requirements (such as changing the address or modifying the delivery time period). By analyzing these influencing factors, the system can dynamically adjust the delivery plan. For example, if the customer makes an urgent request, the system will automatically assign a higher weight to the order and give priority to arranging delivery resources. The technical effect of this step is to make the selection of the delivery route more flexible and responsive to real-time changes, improving the timeliness of delivery and customer satisfaction.

[0104] S502. Assign weights to each order influencing factor to generate a second weight value, and sum up the second weight values to generate the corresponding dynamic weight feature. In this embodiment, assigning weights to each order influencing factor means that the system assigns values to each influencing factor according to its importance to generate a second weight value. Each order influencing factor (such as urgent requests, 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, the traffic condition may be assigned a value according to the congestion level of the road section or the severity of weather changes. If a certain route 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, which is used to influence the selection of the delivery route. In this way, the system can flexibly adjust the delivery route according to real-time changes, thereby ensuring the efficiency and accuracy in the delivery process.

[0105] S503. Determine whether the eigenvalue corresponding to the dynamic weight feature exceeds the determined variation threshold. If not, continue the determination. In this embodiment, determining whether the eigenvalue corresponding to the dynamic weight feature exceeds the determined variation threshold means that the system evaluates the generated dynamic weight feature to determine whether these eigenvalue exceed the preset variation threshold. If the change in the dynamic weight feature exceeds the set threshold, it indicates that the current delivery conditions have changed significantly, and it may be necessary to readjust the delivery route. For example, if the combined weight of urgent requests and traffic conditions is high and exceeds the set threshold, the system will activate the matching mechanism for the second optimal route. If the threshold is not exceeded, the system will continue to determine and maintain the original delivery route. The technical effect of this step is to ensure that the selection of the delivery route can respond in a timely manner to changes in order requirements through real-time monitoring and dynamic determination, avoiding delivery delays or errors.

[0106] S504. If it exceeds, determine whether the second optimal delivery route can be determined based on the route load rate of the first optimal delivery route. If the second optimal delivery route is determined, push the first interaction window for whether to select the second optimal delivery route. If the second optimal delivery route is not determined, push the second interaction window for whether to select to automatically print the delivery optimization label at the next delivery point of the current delivery point in the first optimal delivery route. In this embodiment, if it exceeds, determining whether the second optimal delivery route can be determined based on the route load rate of the first optimal delivery route means that when the dynamic weight feature exceeds the threshold, the system will determine whether to select the second optimal delivery route according to the current load condition of the first optimal delivery route. If the load rate of the first optimal route is too high, the system will evaluate other available routes and select the second optimal route according to the route load rate, timeliness and other factors. The route load rate represents the resource utilization degree of the current route, such as the occupancy of transportation tools, the workload of the sorting center, etc. If the second optimal route meets the timeliness requirements and has a low load, the system will select this route for delivery. The technical effect of this step is to ensure automatic route optimization when resources are tight through real-time load assessment, avoiding delivery delays caused by route congestion; after successfully determining the second optimal delivery route, the system will push an interaction window to the customer or operator to ask whether to confirm the selection of this route. This interaction window usually appears in the user front-end application, allowing the customer or logistics dispatcher to see the selection of the current delivery route and make a decision on whether to modify it. For example, the system may remind the customer that based on the current traffic and weather conditions, the second optimal 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 optimal route cannot be determined, the system will continue to optimize the delivery process on the first optimal route. Specifically, the route will be adjusted through the next station of the current delivery point to perform the automatic printing of the optimization label. The system will push an interaction window to the user to inform the customer or dispatcher that the current route will pass through a new node and ask whether to continue the operation of printing the optimization label. The optimization label may include updated delivery information, estimated arrival time, etc. The technical effect of this operation is to ensure that even if the second optimal route cannot be switched, the delivery efficiency can still be improved by optimizing the next node of the existing route, thereby maximizing resource utilization and timeliness, and ensuring the accuracy of delivery and customer satisfaction.

[0107] It should be understood that the magnitudes of the sequence numbers of the steps in the above embodiments do not mean the order of execution. The order of execution of each process should be determined according to its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present application.

[0108] In one embodiment, a logistics distribution management device is provided, and the logistics distribution management device corresponds one-to-one with the logistics distribution management method in the above embodiment. As Figure 7 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:

[0109] The first acquisition module is used to acquire customer order information and match the corresponding outbound goods in the established inbound management system;

[0110] The 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 distribution path according to the initial weight features. The first optimal distribution path includes at least a first mailing path and a first self-pickup path, and a visual path corresponding to the optimal distribution path is generated in the user front-end application;

[0111] The second extraction module is used to extract the identity features in the customer order information, and customize and automatically print a distribution initial label according to the identity features and the initial weight features. The distribution initial label is used to be pasted on the outbound goods;

[0112] The update module is used to track the transfer information of the distribution initial label in real time, and update the current distribution point on the visual path in real time according to the transfer information;

[0113] The second acquisition module is used to acquire dynamic weight features in real time in the user front-end application, match the second optimal distribution path according to the dynamic weight features, or automatically print a distribution optimization label at the next distribution point of the current distribution point in the first optimal distribution path. The second optimal distribution path includes at least a second mailing path and a second self-pickup path.

[0114] Optionally, the first extraction module includes:

[0115] A generation unit, configured to classify the initial weight features to generate corresponding classification packages;

[0116] A first acquisition unit, configured to assign values to each of the classification packages based on the established intelligent matching model to obtain the first weight value of each classification package;

[0117] A matching unit, configured to match the corresponding current distribution path according to the classification package and determine the path load rate of the current distribution path in real time;

[0118] A first determination unit, configured to determine the corresponding weight load rate according to the sum of the first weight values of each classification package;

[0119] A second determination unit, configured to determine a corresponding first optimal delivery path according to a comparison result between the path load rate and the weight load rate;

[0120] Optionally, the matching unit includes:

[0121] A first matching subunit, configured to match a corresponding item identifier according to the classified package;

[0122] A screening subunit, configured to screen a corresponding current delivery path according to the item identifier;

[0123] A determination subunit, configured to determine each path item in the current delivery path and the item load rate of each path item, where the path items include a primary sorting item, a word printing item, a secondary sorting item, and a verification item, and the primary sorting item includes at least a sorting mail pick-up item;

[0124] A generation subunit, configured to perform weighted averaging on the item load rates of each of the path items to generate a corresponding path load rate;

[0125] Optionally, the second extraction module includes:

[0126] A scanning verification unit, configured to perform scanning verification on a goods barcode pre-stuck on the outbound goods;

[0127] A shelving unit, configured to, if the scanning verification is successful, shelve the barcode information corresponding to the goods barcode in the established inbound management system;

[0128] A third determination unit, configured to determine a unique order transfer code according to the identity feature;

[0129] A customization unit, configured to customize and automatically print a delivery initial label according to the initial weight feature and the unique order transfer code;

[0130] An execution unit, configured to perform a corresponding label pasting operation, where the label pasting operation is used to paste the delivery initial label on the outbound goods;

[0131] Optionally, the update module includes:

[0132] A second acquisition unit, configured to acquire the scanning information of the delivery initial label;

[0133] A fourth determination unit, configured to determine a scanning node corresponding to the scanning information, where the scanning node is a sensing device corresponding to one of the path items of the first optimal delivery path;

[0134] A first generation unit for generating corresponding transfer information according to the scanned node and the scan information;

[0135] Optionally, the second acquisition module includes:

[0136] An invocation unit for invoking corresponding order influencing factors in a user front-end application, where the order influencing factors include urgent requests, traffic conditions, weather changes, and order changes;

[0137] A second generation unit for assigning weights to each of the order influencing factors to generate second weight values, and adding the second weight values to generate corresponding dynamic weight features;

[0138] A first determination unit for determining whether the eigenvalue corresponding to the dynamic weight feature exceeds a determined change threshold. If not, continue the determination;

[0139] A second determination unit for, if it exceeds, determining whether a second optimal delivery route can be determined according to the route load rate of the first optimal delivery route. If the second optimal delivery route is determined, push a first interaction window for whether to select the second optimal delivery route. If the second optimal delivery route is not determined, push a second interaction window for whether to select to automatically print a delivery optimization label at the next delivery point of the current delivery point in the first optimal delivery route.

[0140] For the specific limitations of a logistics distribution management device, reference can be made to the limitations of a logistics distribution management method in the above text, which will not be elaborated here. Each module in the above logistics distribution management device can be implemented in whole or in part by software, hardware, and their combination. The above modules can be embedded in the processor of a computer device in hardware form or independent of it, or stored in the memory of a computer device in software form, so that the processor can call and execute the operations corresponding to the above modules.

[0141] In one embodiment, a computer device is provided. The computer device can be a server, and its internal structure diagram can be as Figure 8 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. The computer program, when executed by the processor, implements a logistics distribution management method.

[0142] In one embodiment, a computer device is provided, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, the following steps are implemented:

[0143] S10. Obtain customer order information, and match the corresponding outbound goods in the established warehousing management system;

[0144] S20. Extract the initial weight features from the customer order information. Based on the established intelligent matching model, match the corresponding first optimal delivery path according to the initial weight features. The first optimal delivery path includes at least 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;

[0145] S30. Extract the identity features from the customer order information, and customize and automatically print the initial delivery label according to the identity features and the initial weight features. The initial delivery label is used to be pasted on the outbound goods;

[0146] S40. Real-time track the transfer information of the initial delivery label, and update the current delivery point on the visual path in real time according to the transfer information;

[0147] S50. Real-time obtain the dynamic weight features in the user front-end application, match the second optimal delivery path according to the dynamic weight features, or automatically print the optimized delivery label at the next delivery point of the current delivery point on the first optimal delivery path. The second optimal delivery path includes at least a second mailing path and a second self-pickup path.

[0148] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the following steps are implemented:

[0149] S10. Obtain customer order information, and match the corresponding outbound goods in the established warehousing management system;

[0150] S20. Extract the initial weight features from the customer order information. Based on the established intelligent matching model, match the corresponding first optimal delivery path according to the initial weight features. The first optimal delivery path includes at least 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;

[0151] S30. Extract the identity features from the customer order information, and customize and automatically print the initial delivery label according to the identity features and the initial weight features. The initial delivery label is used to be pasted on the outbound goods;

[0152] S40. Track the transfer information of the initial delivery label in real time, and update the current delivery point on the visualized path in real time according to the transfer information;

[0153] S50. Obtain the 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. The second optimal delivery path includes at least a second mailing path and a second pick-up path.

[0154] Those of ordinary skill in the art can understand that all or part of the processes of implementing the methods in the above embodiments can be completed by instructing relevant hardware through a computer program. 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 methods. Among them, any reference to a memory, storage, database, or other medium used in the various embodiments provided in the present application can include non-volatile and / or volatile memories. Non-volatile memories can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memories can include random access memory (RAM) or external cache memory. By way of 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), etc.

[0155] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the above-mentioned division of each functional unit and module is used for illustration. In actual applications, the above functions can be allocated to different functional units and modules as needed, that is, the internal structure of the device is divided into different functional units or modules to complete all or part of the functions described above.

[0156] 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 foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included within 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; In the user front-end application, dynamic weight features are acquired in real time, and a second optimal delivery path is matched according to the dynamic weight features, or a delivery optimization label is automatically printed 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; 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; Determine a first optimal delivery path according to a comparison result of the path load rate and the weighted load rate; 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.

2. 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.

3. 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.

4. 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.

5. 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; A second acquisition module is used to acquire dynamic weight features in real time in the user front-end application, match a second optimal delivery path according to the dynamic weight features, or automatically print a delivery optimization label 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; 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; The generating subunit is used to perform weighted averaging on the item load rates of the various path items to generate a corresponding path load rate.

6. A logistics distribution management device according to claim 5, characterized in that: 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.

7. 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 the logistics distribution management method as described in any one of claims 1 to 4 are implemented.

8. 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 claimed in any one of claims 1 to 4 are implemented.

Images