Enterprise purchase order tracking method and system

Abstract

The invention discloses an enterprise purchase order tracking method and system, and relates to the technical field of order management. The method comprises the following steps: acquiring basic information of a plurality of enterprise purchase orders; setting n order tracking nodes; transport information of each enterprise purchase order between the ith order tracking node and the (i-1) th order tracking node is obtained, and i belongs to [1, n]; based on each piece of basic information and each piece of transportation information, obtaining an importance score of each enterprise purchase order at the ith order tracking node; based on each importance score, classifying each enterprise purchase order to obtain a plurality of order sets corresponding to the ith order tracking node; and determining order tracking logic of all enterprise purchase orders in each order set based on the type corresponding to each order set. According to the technical scheme of the invention, the method can achieve the refined tracking of purchasing orders of different importance, and improves the efficiency and accuracy of purchasing order management.

Description

Technical Field

[0001] The present application relates to the technical field of order management, and in particular to a method and system for tracking enterprise purchase orders. Background Art

[0002] In modern enterprise supply chain management, the management of enterprise purchase orders is crucial. The effective management of purchase orders is not only related to the production plan and cost control of the enterprise, but also affects the market competitiveness and customer satisfaction of the enterprise. At present, enterprises usually use ERP (Enterprise Resource Planning) system to manage purchase orders and use logistics management system (TMS) to track the transportation status of orders. However, these methods have obvious shortcomings in order management.

[0003] Existing order tracking technology practices mainly include static order management and independent transportation information monitoring. The static order management method determines the priority of the order when the order is created and remains unchanged throughout the order life cycle. It lacks a dynamic adjustment mechanism and is difficult to adapt to changes and emergencies that occur during the order execution process. The transportation information monitoring system is usually independent of the order management system, resulting in the basic order information and transportation information being scattered in different systems, making it difficult to conduct comprehensive analysis and dynamic evaluation, affecting the overall efficiency of order management. Due to the lack of comprehensive evaluation and dynamic adjustment mechanisms, the existing order tracking methods are difficult to achieve refined tracking of purchase orders of different importance, resulting in poor efficiency and accuracy in purchase order management.

[0004] Therefore, how to achieve refined tracking of purchase orders of different importance, thereby improving the efficiency and accuracy of purchase order management, has become a technical problem that needs to be solved urgently. Summary of the invention

[0005] The present application provides an enterprise purchase order tracking method and system, which can realize refined tracking of purchase orders of different importance, thereby improving the efficiency and accuracy of purchase order management.

[0006] In a first aspect, the present application provides a method for tracking enterprise purchase orders, the method comprising: obtaining basic information of multiple enterprise purchase orders; setting n order tracking nodes; obtaining transportation information of each of the enterprise purchase orders between the i-th order tracking node and the i-1-th order tracking node, wherein i∈[1,n]; based on each of the basic information and each of the transportation information, obtaining an importance score of each of the enterprise purchase orders at the i-th order tracking node; based on each of the importance scores, classifying each of the enterprise purchase orders to obtain multiple order sets corresponding to the i-th order tracking node; wherein each of the order sets contains at least one of the enterprise purchase orders; based on the type corresponding to each of the order sets, determining the order tracking logic of all the enterprise purchase orders in each of the order sets.

[0007] By adopting the above technical solution, by obtaining the basic information of multiple enterprise purchase orders, the basic data of each order can be fully mastered to ensure the accuracy and completeness of subsequent analysis. By setting n order tracking nodes, the entire life cycle of the order can be systematically monitored, which is convenient for tracking and management, and improves the transparency and controllability of the supply chain. By obtaining the transportation information of each enterprise purchase order between the i-th order tracking node and the i-1-th order tracking node, the transportation status of the order can be grasped in real time, and problems arising during the transportation process can be discovered and handled in a timely manner to ensure the safety and timely delivery of the order. Based on each basic information and each transportation information, the importance score of each enterprise purchase order at the i-th order tracking node is obtained, so as to objectively and dynamically evaluate the priority of each order and ensure the reasonable allocation of resources and management priorities. By classifying each enterprise purchase order based on each importance score, multiple order sets corresponding to the i-th order tracking node are obtained, so as to realize classified management, ensure that orders of different importance receive corresponding attention and processing, and improve management efficiency and response speed. By determining the order tracking logic of all enterprise purchase orders in each order set based on the type corresponding to each order set, targeted management can be achieved to ensure that orders of different importance receive appropriate attention and processing, and to achieve refined tracking of purchase orders of different importance, thereby improving the efficiency and accuracy of purchase order management.

[0008] Optionally, obtaining the importance score of each enterprise purchase order at the i-th order tracking node based on each of the basic information and each of the transportation information specifically includes: constructing a hierarchical model based on each of the basic information and each of the transportation information; constructing a judgment matrix based on the hierarchical model; calculating the eigenvector of the judgment matrix to obtain a first weight vector corresponding to each of the basic information and a second weight vector corresponding to each of the transportation information; obtaining a comprehensive weight vector based on the first weight vector and the second weight vector; determining a first score value corresponding to each of the basic information, and determining a second score value corresponding to each of the transportation information at the i-th order tracking node; and performing weighted summation of each of the first score value and each of the second score value with the comprehensive weight vector to obtain each of the importance scores.

[0009] By adopting the above technical solution, a hierarchical model is constructed based on each basic information and each transportation information, so as to systematically integrate various factors affecting order scoring and ensure the comprehensiveness of the scoring process. By constructing a judgment matrix based on the hierarchical model, the importance of different indicators is quantified, ensuring that each factor can be reasonably weighted when calculating the importance score of the enterprise's purchase order. By calculating the eigenvector of the judgment matrix, the first weight vector corresponding to each basic information and the second weight vector corresponding to each transportation information are obtained, so as to scientifically quantify the relative importance of each basic information and transportation information indicator. By obtaining a comprehensive weight vector based on the first weight vector and the second weight vector, the overall weight distribution of each indicator is achieved, ensuring that each factor can be comprehensively considered and reasonably allocated in the final scoring. By determining the first score value corresponding to each basic information and determining the second score value corresponding to each transportation information at the i-th order tracking node, the performance of each order in terms of basic information and transportation information is quantified, providing basic data for subsequent weighted summation. By weightedly summing each first score value and each second score value with the comprehensive weight vector, each importance score is obtained, thereby comprehensively considering the basic information and transportation information of the order, scientifically calculating the importance score of each order, and providing a basis for subsequent order classification and management.

[0010] Optionally, constructing a hierarchical model based on each of the basic information and each of the transportation information specifically includes: determining a target layer of the hierarchical model, the target layer being to calculate an importance score of each of the enterprise purchase orders at the i-th order tracking node; determining a criterion layer under the target layer, the criterion layer including each of the basic information and each of the transportation information; determining an indicator layer under the criterion layer, the indicator layer including basic information indicators and transportation information indicators; the basic information indicators include order amount, delivery time urgency, commodity importance and supplier reliability, and the transportation information indicators include inventory level transportation progress, transportation environment and transportation safety; constructing the hierarchical model based on the target layer, the criterion layer and the indicator layer.

[0011] By adopting the above technical solution, by determining the target layer of the hierarchical model, the target layer is to calculate the importance score of each enterprise's purchase order at the i-th order tracking node, so as to concentrate resources and energy on evaluating the importance of the order, so that the entire scoring process has a clear goal orientation. By determining the criterion layer under the target layer, the criterion layer includes various basic information and various transportation information, so as to systematically integrate the key factors affecting the order scoring, and ensure that the scoring process comprehensively covers the different dimensions of the order. By determining the indicator layer under the criterion layer, the indicator layer includes basic information indicators and transportation information indicators, so as to further refine the criterion layer, clarify specific evaluation indicators, and make the scoring process more specific and operational. By constructing a hierarchical model based on the target layer, the criterion layer and the indicator layer, the various factors affecting the order scoring are systematically integrated to ensure the comprehensiveness of the scoring process.

[0012] Optionally, the judgment matrix includes a basic information judgment matrix and a transportation information judgment matrix; constructing the judgment matrix based on the hierarchical model specifically includes: determining the relative importance of each of the basic information indicators based on a pairwise comparison method, and constructing the basic information judgment matrix; determining the relative importance of each of the transportation information indicators based on a pairwise comparison method, and constructing the transportation information judgment matrix.

[0013] By adopting the above technical solution, the relative importance of each basic information indicator is determined based on the pairwise comparison method, and a basic information judgment matrix is ​​constructed to quantify the importance of different basic information indicators, ensuring that each basic information factor can be reasonably weighted when calculating the importance score of the enterprise's purchase order. By determining the relative importance of each transportation information indicator based on the pairwise comparison method, a transportation information judgment matrix is ​​constructed to quantify the importance of different transportation information indicators, ensuring that each transportation information factor can be reasonably weighted when calculating the importance score of the enterprise's purchase order.

[0014] Optionally, the judgment matrix includes a basic information judgment matrix and a transportation information judgment matrix; and calculating the eigenvector of the judgment matrix to obtain a first weight vector corresponding to each basic information and a second weight vector corresponding to each transportation information specifically includes: calculating the eigenvector of the basic information judgment matrix by the eigenvalue method or normalization processing to obtain each first weight vector; calculating the eigenvector of the transportation information judgment matrix by the eigenvalue method or normalization processing to obtain each second weight vector.

[0015] By adopting the above technical solution, the eigenvectors of the basic information judgment matrix and the transportation information judgment matrix are calculated through the eigenvalue method or normalization processing to obtain the first weight vectors and the second weight vectors, thereby scientifically quantifying the relative importance of the basic information indicators and ensuring that each basic information factor and each transportation information factor can be reasonably weighted when comprehensively scoring.

[0016] Optionally, obtaining a comprehensive weight vector based on the first weight vector and the second weight vector specifically includes: determining a first weight coefficient corresponding to the first weight vector and a second weight coefficient corresponding to the second weight vector, wherein the sum of the first weight coefficient and the second weight coefficient is one; multiplying each component in the first weight vector by the first weight coefficient to obtain a first weight vector; multiplying each component in the second weight vector by the second weight coefficient to obtain a second weight vector; and adding corresponding components of the first weight vector and the second weight vector to obtain the comprehensive weight vector.

[0017] By adopting the above technical solution, by determining the first weight coefficient corresponding to the first weight vector and the second weight coefficient corresponding to the second weight vector, the weight ratio of basic information and transportation information is scientifically allocated to ensure that the two types of information can be reasonably balanced when comprehensively scoring. The first weight vector is obtained by multiplying each component in the first weight vector by the first weight coefficient, thereby ensuring that the importance of the basic information indicator is reasonably reflected in the comprehensive weight. The second weight vector is obtained by multiplying each component in the second weight vector by the second weight coefficient, thereby ensuring that the importance of the transportation information indicator is reasonably reflected in the comprehensive weight. By adding the first weight vector and the second weight vector, a comprehensive weight vector is generated, so that the comprehensive score can fully reflect all important aspects of the order.

[0018] Optionally, based on each of the importance scores, each of the enterprise purchase orders is classified to obtain multiple order sets corresponding to the i-th order tracking node, specifically including: setting multiple importance score thresholds; setting multiple order sets based on the multiple importance score thresholds; and classifying each of the enterprise purchase orders into each of the order sets based on the corresponding relationship between each of the importance scores and each of the importance score thresholds.

[0019] In a second aspect of the present application, a corporate purchase order tracking system is provided, the system comprising: an acquisition module and a processing module; the acquisition module is used to acquire basic information of multiple corporate purchase orders; the processing module is used to set n order tracking nodes; the acquisition module is also used to acquire transportation information of each of the corporate purchase orders between the i-th order tracking node and the i-1-th order tracking node, wherein i∈[1,n]; the processing module is also used to obtain the importance score of each of the corporate purchase orders at the i-th order tracking node based on each of the basic information and each of the transportation information; the processing module is also used to classify each of the corporate purchase orders based on each of the importance scores to obtain multiple order sets corresponding to the i-th order tracking node; wherein each of the order sets contains at least one corporate purchase order; the processing module is also used to determine the order tracking logic of all corporate purchase orders in each of the order sets based on the types corresponding to each of the order sets.

[0020] In the third aspect of the present application, an electronic device is provided, including a processor, a memory, a user interface and a network interface, the memory is used to store instructions, the user interface and the network interface are used to communicate with other devices, and the processor is used to execute the instructions stored in the memory so that the electronic device executes any method as described in the first aspect of the present application.

[0021] In a fourth aspect of the present application, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores a computer program that can be loaded by a processor and execute the method as described in any one of the first aspects of the present application.

[0022] In summary, one or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages: By obtaining the basic information of multiple corporate purchase orders, the basic data of each order can be fully mastered to ensure the accuracy and completeness of subsequent analysis. By setting n order tracking nodes, the entire life cycle of the order can be systematically monitored, which is convenient for tracking and management, and improves the transparency and controllability of the supply chain. By obtaining the transportation information of each corporate purchase order between the i-th order tracking node and the i-1-th order tracking node, the transportation status of the order can be grasped in real time, and problems arising during transportation can be discovered and handled in a timely manner to ensure the safety and timely delivery of the order. Based on various basic information and various transportation information, the importance score of each corporate purchase order at the i-th order tracking node is obtained, so as to objectively and dynamically evaluate the priority of each order and ensure the reasonable allocation of resources and management priorities. By classifying each corporate purchase order based on each importance score, multiple order sets corresponding to the i-th order tracking node are obtained, so as to achieve classified management, ensure that orders of different importance receive corresponding attention and processing, and improve management efficiency and response speed. By determining the order tracking logic of all enterprise purchase orders in each order set based on the type corresponding to each order set, targeted management can be achieved to ensure that orders of different importance receive appropriate attention and processing, and to achieve refined tracking of purchase orders of different importance, thereby improving the efficiency and accuracy of purchase order management. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 This is one of the flow charts of a method for tracking enterprise purchase orders provided in an embodiment of the present application; Figure 2 This is the second flow chart of a method for tracking enterprise purchase orders provided in an embodiment of the present application; Figure 3 It is a structural diagram of an enterprise purchase order tracking system provided by an embodiment of the present application; Figure 4 It is a structural schematic diagram of an electronic device disclosed in an embodiment of the present application.

[0024] Explanation of the reference numerals: 1. Acquisition module; 2. Processing module; 400. Electronic device; 401. Processor; 402. Communication bus; 403. User interface; 404. Network interface; 405. Memory. DETAILED DESCRIPTION

[0025] In order to enable technicians in this field to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this application, not all of the embodiments.

[0026] In the description of the embodiments of the present application, words such as "for example" or "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described as "for example" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "for example" or "for example" is intended to present related concepts in a specific way.

[0027] In the description of the embodiments of the present application, the meaning of the term "multiple" refers to two or more. For example, multiple systems refer to two or more systems, and multiple screen terminals refer to two or more screen terminals. In addition, the terms "first" and "second" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly indicating the indicated technical features. Thus, the features defined as "first" and "second" can explicitly or implicitly include one or more of the features. The terms "include", "comprise", "have" and their variations all mean "including but not limited to", unless otherwise specifically emphasized.

[0028] This application provides a method for tracking enterprise purchase orders. Figure 1 , which shows one of the flow diagrams of a method for tracking enterprise purchase orders provided in an embodiment of the present application. The method includes steps S1-S6, which are as follows: Step S1: Obtain basic information of multiple enterprise purchase orders.

[0029] When implementing step S1, by obtaining the basic information of multiple corporate purchase orders, the basic data of each order can be fully grasped, thereby ensuring the accuracy and completeness of subsequent analysis. The acquisition of basic information is the basis of the entire supply chain management system. Only after fully understanding the specific details of the order can subsequent evaluation and management be carried out.

[0030] First, the system automatically extracts relevant order data from the ERP system. This basic information includes order amount, delivery time urgency, product importance, supplier reliability and inventory level. The order amount reflects the economic value of the order, the delivery time urgency reflects the time requirements of the order, the product importance measures the importance of the product to the company's production or operation, the supplier reliability is evaluated by historical performance records and reputation, and the inventory level shows the current urgency of the inventory.

[0031] Specifically, the system connects to the ERP system through an API interface and obtains these order data from the ERP system in real time. The order amount is directly obtained through the total amount field of the order, and the urgency of delivery time is determined by calculating the difference between the current time and the delivery time required by the order. The importance of goods can be determined based on the commodity category and the company's internal production schedule. The reliability of suppliers is evaluated based on the supplier's historical performance data and credit scoring system. The inventory level is calculated through the current inventory data provided by the warehouse management system (WMS).

[0032] After obtaining this data, the system will initially organize and verify the data to ensure its accuracy and completeness. For example, it will check whether the order amount is consistent with the quantity and unit price of the goods in the order details, verify whether the delivery time is within a reasonable range, and verify the credit score of the supplier. After completing the data organization, this basic information will be stored in a special database for subsequent steps.

[0033] Step S2: Set n order tracking nodes; When implementing step S2, by setting n order tracking nodes, each key link from creation to completion of each order can be clearly identified, so as to systematically monitor the entire life cycle of the order, facilitate tracking and management, and improve the transparency and controllability of the supply chain. The purpose of setting order tracking nodes is to ensure effective monitoring and management at every important stage of the order, so as to timely discover and solve problems and ensure that the order is completed on time.

[0034] First, according to the actual business process and supply chain management needs of the enterprise, determine the key links from order creation to completion. Usually, these key links include order creation, order confirmation, material preparation, shipment, transportation, arrival inspection and warehousing, etc. According to these links, set n order tracking nodes, for example, n can be 7, and each node corresponds to one of the above key links.

[0035] Specifically, the system sets these tracking nodes in the ERP and TMS systems. When each node is set, the trigger conditions of the node, the information to be recorded, and the key indicators to be monitored are defined. For example, the trigger condition of the order creation node is that the order is created in the ERP system, and the recorded information includes the order number, order date, customer information, etc.; the trigger condition of the shipping node is that the shipping operation in the warehouse system is completed, and the recorded information includes the shipping time, shipping quantity, transportation method, etc.; the trigger condition of the transportation node is the transportation status update in the logistics system, and the key indicators to be monitored include transportation progress, transportation environment (such as temperature and humidity) and transportation safety.

[0036] Step S3: Obtain the transportation information of each enterprise purchase order between the i-th order tracking node and the i-1-th order tracking node, where i∈[1,n].

[0037] When implementing step S3, by obtaining the transportation information of each enterprise's purchase order between the i-th order tracking node and the i-1-th order tracking node, the transportation status of the order can be grasped in real time, and problems arising during the transportation process can be discovered and handled in a timely manner to ensure the safety and timely delivery of the order. The purpose of obtaining transportation information is to effectively monitor and manage each transportation stage of the order, thereby improving the transparency and controllability of the transportation process.

[0038] First, the system installs and integrates various IoT devices at each transportation node, such as GPS locators, temperature and humidity sensors, and vibration sensors. These devices can monitor and record the location, environmental conditions, and safety during transportation in real time. The system collects transportation information in real time through these devices and transmits the data to the central management platform through wireless communication technology.

[0039] Specifically, between the i-th order tracking node and the i-1-th order tracking node, the system uses the GPS locator to obtain the location data of the transport vehicle in real time and monitor the transport progress. The temperature and humidity sensor is used to monitor the temperature and humidity in the transport environment to ensure that the environmental conditions meet the order requirements, especially for orders with high environmental requirements such as perishable goods and medicines. The vibration sensor monitors whether there is abnormal vibration or collision during transportation to ensure transportation safety.

[0040] The system sets up a processing module on the central management platform to receive and process the transportation information uploaded from various sensors in real time. For location data, the system displays the real-time location and route of the transport vehicle through the map interface, calculates the estimated arrival time, and generates a transportation progress report based on the deviation between the actual transportation progress and the planned progress. For temperature and humidity data, the system sets threshold monitoring. When the temperature and humidity exceed the set range, the system automatically generates an alarm and notifies relevant personnel to handle it. For vibration data, the system records and analyzes vibration events, determines whether there are any transportation safety hazards, and takes corresponding measures.

[0041] Step S4: Based on various basic information and various transportation information, the importance score of each enterprise purchase order at the i-th order tracking node is obtained.

[0042] When implementing step S4, by obtaining the importance score of each enterprise purchase order at the i-th order tracking node based on each basic information and each transportation information, the priority of each order can be objectively and dynamically evaluated to ensure the reasonable allocation of resources and management priorities. The purpose of obtaining the importance score is to accurately evaluate the importance of the order at each tracking node of the order, thereby providing a basis for subsequent classification management and tracking logic.

[0043] In one possible implementation, refer to Figure 2 , which shows the second flow chart of a method for tracking enterprise purchase orders provided in an embodiment of the present application. Step S4 specifically includes steps S41-S46: Step S41: construct a hierarchical structure model based on various basic information and various transportation information.

[0044] In a possible implementation, step S41 specifically includes the following steps: Determine the target layer of the hierarchical model, which is to calculate the importance score of each enterprise's purchase order at the i-th order tracking node.

[0045] Determine the criterion layer under the target layer, the criterion layer includes various basic information and various transportation information.

[0046] Determine the indicator layer under the criterion layer, which includes basic information indicators and transportation information indicators; basic information indicators include order amount, delivery time urgency, commodity importance and supplier reliability, and transportation information indicators include inventory level, transportation progress, transportation environment and transportation safety.

[0047] A hierarchical model is constructed based on the target layer, criterion layer and indicator layer.

[0048] When implementing step S41, by constructing a hierarchical model based on various basic information and various transportation information, a scientific structure and basis can be provided for the subsequent order importance scoring, thereby ensuring the accuracy and rationality of the scoring. The purpose of constructing a hierarchical model is to systematically integrate various influencing factors so that the scoring process can comprehensively consider all aspects of the order, and calculate the weight vector through the hierarchical analysis method (AHP) to ensure the fairness and accuracy of the scoring.

[0049] First, the system needs to determine the target layer of the hierarchical model. The target layer is to calculate the importance score of each enterprise's purchase order at the i-th order tracking node, which is the ultimate goal of the entire model. Clarifying the target layer can help the system focus resources and energy on the most important tasks, thereby improving overall efficiency and effectiveness.

[0050] Next, the system determines the criteria layer under the target layer. The criteria layer consists of two main parts: basic information and shipping information. These two parts represent the basic data when the order is created and the dynamic data of the order during execution. By incorporating these two parts into the criteria layer, it can ensure that the model takes into account both the initial conditions of the order and the real-time status of the order when scoring, providing a comprehensive evaluation basis.

[0051] Then, the system determines the indicator layer under the criterion layer. The indicator layer is a further refinement of the criterion layer, including specific evaluation indicators. For each basic information, the indicator layer includes order amount, delivery time urgency, commodity importance and supplier reliability. The order amount reflects the economic value of the order, the delivery time urgency reflects the time requirement, the commodity importance measures the importance of the commodity to the company's production or operation, and the supplier reliability is based on the supplier's historical performance and reputation. For each transportation information, the indicator layer includes inventory level, transportation progress, transportation environment and transportation safety. The inventory level shows the urgency of the current inventory, the transportation progress monitors the actual transportation status of the order, the transportation environment monitors the suitability of environmental conditions during transportation, and transportation safety ensures the safety of the order during transportation.

[0052] Step S42: construct a judgment matrix based on the hierarchical structure model.

[0053] In a possible implementation, step S42 specifically includes the following steps: Based on the pairwise comparison method, the relative importance of each basic information indicator is determined and the basic information judgment matrix is ​​constructed.

[0054] Based on the pairwise comparison method, the relative importance of each transportation information indicator is determined, and the transportation information judgment matrix is ​​constructed.

[0055] When implementing step S42, by constructing a judgment matrix based on the hierarchical model, the relative importance of each basic information and transportation information indicator can be scientifically determined, thereby laying the foundation for the subsequent calculation of the weight vector. The purpose of constructing the judgment matrix is ​​to quantify the importance of different indicators and ensure that each factor can be reasonably weighted when calculating the importance score of the enterprise's purchase order.

[0056] First, based on the criterion layer and indicator layer in the hierarchical model, the system constructs two judgment matrices: the basic information judgment matrix and the transportation information judgment matrix. The judgment matrix determines the relative importance of each indicator through a pairwise comparison method. This is a systematic process. Specifically, it compares each factor in the criterion layer and the indicator layer in pairs and assigns a relative importance value.

[0057] Specifically, the system constructs a basic information judgment matrix through a pairwise comparison method. Based on the basic information indicators in the hierarchical model, such as order amount, delivery time urgency, commodity importance, and supplier reliability, the system compares these indicators in turn. For example, the system compares the order amount with the delivery time urgency. If the order amount is more important than the delivery time urgency, it assigns a higher value; otherwise, it assigns a lower value. In this way, the system compares all basic information indicators in turn and constructs a basic information judgment matrix.

[0058] Similarly, the system constructs a transportation information judgment matrix through a pairwise comparison method. Based on the transportation information indicators in the hierarchical model, such as inventory level, transportation progress, transportation environment, and transportation safety, the system compares these indicators in turn. For example, the system compares the transportation progress with the transportation environment. If the transportation progress is more important than the transportation environment, a higher value is assigned; otherwise, a lower value is assigned. In this way, the system compares all transportation information indicators in turn and constructs a transportation information judgment matrix.

[0059] In specific implementation, the system can be scored by experts or compared pairwise using historical data. Invite supply chain management experts to compare each pair of indicators and assign corresponding values ​​based on their experience and judgment. Alternatively, the system can analyze historical order data to determine the actual impact of each indicator in past orders and assign values ​​accordingly. Regardless of which method is used, ensure that the judgment is scientific and reasonable.

[0060] After constructing the judgment matrix, the system needs to perform a consistency check to ensure the rationality and consistency of the judgment matrix. The consistency check of the judgment matrix is ​​to confirm the consistency between the various comparison results. If the consistency is passed, the system will input the judgment matrix into the subsequent eigenvector calculation step.

[0061] Step S43: Calculate the eigenvector of the judgment matrix to obtain the first weight vector corresponding to each basic information and the second weight vector corresponding to each transportation information.

[0062] In a possible implementation, step S43 specifically includes the following steps: The eigenvalue method or normalization processing is used to calculate the eigenvectors of the basic information judgment matrix to obtain each first weight vector.

[0063] The eigenvalue method or normalization processing is used to calculate the eigenvectors of the transportation information judgment matrix to obtain each second weight vector.

[0064] When implementing step S43, by calculating the eigenvector of the judgment matrix, the weight vector corresponding to each basic information and transportation information can be obtained, thereby providing accurate weight distribution for the subsequent comprehensive scoring. The purpose of calculating the eigenvector is to quantify the relative importance of each indicator and ensure that each factor can be scientifically and fairly weighted when making a comprehensive score.

[0065] First, the system calculates the eigenvectors of the basic information judgment matrix through the eigenvalue method or normalization processing. The basic information judgment matrix includes indicators such as order amount, delivery time urgency, commodity importance, and supplier reliability. The eigenvalue method is a commonly used mathematical method that can be used to calculate the eigenvectors of the matrix, reflecting the relative importance of each indicator. The system first calculates the eigenvalues ​​and eigenvectors of the basic information judgment matrix, and converts the eigenvectors into the first weight vector through normalization processing to ensure that the sum of all weights is 1.

[0066] Similarly, the system calculates the eigenvector of the transportation information judgment matrix by the eigenvalue method or normalization processing. The transportation information judgment matrix includes indicators such as inventory level, transportation progress, transportation environment and transportation safety. The system calculates the eigenvalue and eigenvector of the transportation information judgment matrix, and converts the eigenvector into a second weight vector by normalization processing.

[0067] Specifically, the system first inputs the basic information judgment matrix and the transportation information judgment matrix. Then, the system uses the eigenvalue method to calculate the eigenvalues ​​and eigenvectors of the basic information judgment matrix. The calculation results of the eigenvectors are converted into the first weight vector through normalization. Then, the system uses the same method to calculate the eigenvalues ​​and eigenvectors of the transportation information judgment matrix, and converts them into the second weight vector through normalization. In the whole process, the eigenvalue method can effectively extract the key information in the judgment matrix and reflect the relative importance of each indicator, while the normalization process ensures that the sum of all weights is 1, which is convenient for subsequent weighted calculations.

[0068] Step S44: Obtain a comprehensive weight vector based on the first weight vector and the second weight vector.

[0069] In a possible implementation, step S44 specifically includes the following steps: A first weighting coefficient corresponding to the first weight vector and a second weighting coefficient corresponding to the second weight vector are determined, wherein a sum of the first weighting coefficient and the second weighting coefficient is one.

[0070] Each component in the first weight vector is multiplied by the first weight coefficient to obtain the first weight vector.

[0071] Each component in the second weight vector is multiplied by the second weight coefficient to obtain a second weight vector.

[0072] The corresponding components of the first weighted vector and the second weighted vector are added to obtain a comprehensive weighted vector.

[0073] When implementing step S44, by obtaining a comprehensive weight vector based on the first weight vector and the second weight vector, the overall weight distribution of each indicator can be achieved, thereby ensuring that each factor can be comprehensively considered and reasonably distributed in the final scoring. The purpose of obtaining the comprehensive weight vector is to scientifically combine the weights of the basic information and the transportation information, so that the final scoring is more comprehensive and accurate.

[0074] First, the system needs to determine the weighting coefficients of the first weight vector and the second weight vector. The setting of the weighting coefficients should be adjusted according to the management needs and actual conditions of the enterprise so that they can be flexibly applied in different situations. Assume that the system determines that the weighting coefficient of the first weight vector is α, the weighting coefficient of the second weight vector is β, and that α+β=1. In this way, it can be ensured that the weighted comprehensive weight vector remains consistent in sum.

[0075] Next, the system multiplies each component of the first weight vector by the weight coefficient α to obtain the first weight vector. Similarly, the system multiplies each component of the second weight vector by the weight coefficient β to obtain the second weight vector. Specifically, assuming that the first weight vector is W_basic and the second weight vector is W_transport, then each component of the first weight vector is W_basic[i]×α, and each component of the second weight vector is W_transport[i]×β.

[0076] Then, the system adds the corresponding components of the first weighted vector and the second weighted vector to obtain a comprehensive weight vector. For example, the i-th component of the comprehensive weight vector is W_basic[i]×α+W_transport[i]×β. In this way, the weights of basic information and transport information can be scientifically integrated to form a weight vector that comprehensively considers various factors.

[0077] Step S45: determining a first scoring value corresponding to each basic information, and determining a second scoring value corresponding to each transportation information at the i-th order tracking node.

[0078] When implementing step S45, by determining the first score value corresponding to each basic information and determining the second score value corresponding to each transportation information at the i-th order tracking node, basic data can be provided for the subsequent weighted summation, thereby calculating the importance score of each order at the current node. The purpose of determining the first score value and the second score value is to quantify the performance of each order in terms of basic information and transportation information, so as to calculate a scientific and accurate order importance score under the weighting of the comprehensive weight vector.

[0079] First, the system needs to determine the first score value based on the basic information of the order. The basic information includes indicators such as order amount, delivery time urgency, commodity importance, and supplier reliability. The system quantitatively scores the basic information of each order. For example, the order amount can be divided into different scoring levels according to a certain interval. The higher the amount, the higher the score. The urgency of delivery time can be scored according to the remaining days of delivery time. The more urgent the time, the higher the score. The importance of goods can be scored according to the internal classification of goods in the enterprise, and important goods have higher scores. Supplier reliability can be scored based on historical data and reputation evaluation. The higher the reliability, the higher the score.

[0080] At the same time, the system needs to determine the second scoring value based on the transportation information. Transportation information includes indicators such as inventory level, transportation progress, transportation environment and transportation safety. The system quantitatively scores the transportation information of each order. For example, the inventory level can be scored based on the ratio of the current inventory to the demand. The lower the inventory, the higher the score. The transportation progress can be scored based on the deviation between the actual transportation time and the planned transportation time. The smaller the deviation, the higher the score. The transportation environment can be scored based on whether the environmental conditions such as temperature and humidity during transportation meet the requirements. The more the conditions meet the requirements, the higher the score. Transportation safety can be scored based on whether abnormal events occur during transportation. The higher the safety, the higher the score.

[0081] Step S46: Perform weighted summation of each first score value and each second score value with the comprehensive weight vector to obtain each importance score.

[0082] When implementing step S46, by weighted summing each first score value and each second score value with the comprehensive weight vector, the importance score of each enterprise purchase order at the i-th order tracking node can be obtained. The purpose of this is to comprehensively consider the basic information and transportation information of the order, and obtain the importance score of each order through scientific weighted calculation, so as to provide a basis for subsequent order classification and management.

[0083] First, the system has calculated the first and second ratings of each order in the previous step, and obtained a comprehensive weight vector. The comprehensive weight vector is obtained by linear weighting based on the first and second weight vectors, ensuring that each factor can be reasonably weighted when the weighted sum is calculated.

[0084] Specifically, the system multiplies the first score value of each order by the corresponding basic information weight component in the comprehensive weight vector. For example, for order i, the first score value is S basic,i , the corresponding basic information weight component is W basic , then calculate S basic,i ×Wbasic Next, the system multiplies the second score of each order by the corresponding transportation information weight component in the comprehensive weight vector. For example, for order i, the second score is S transport,i , the corresponding transportation information weight component is W transport , then calculate S transport,i ×W transport Then, the weighted results of the above two parts are summed to obtain the final importance score of each order.

[0085] Step S5: Based on each importance score, classify each enterprise purchase order to obtain multiple order sets corresponding to the i-th order tracking node; each order set contains at least one enterprise purchase order.

[0086] In a possible implementation, step S5 specifically includes the following steps: Set multiple importance score thresholds.

[0087] Based on multiple importance score thresholds, multiple order sets are set.

[0088] Based on the corresponding relationship between each importance score and each importance score threshold, each enterprise purchase order is classified into each order set.

[0089] When implementing step S5, by classifying the purchase orders of each enterprise based on each importance score, multiple order sets corresponding to the i-th order tracking node can be obtained, thereby realizing classified management, ensuring that orders of different importance receive corresponding attention and processing, and improving management efficiency and response speed. The purpose of this is to reasonably allocate resources, give priority to important orders, optimize the supply chain management process, and improve overall operational efficiency.

[0090] First, the system needs to set multiple importance scoring thresholds. The setting of importance scoring thresholds should be adjusted according to the actual needs and management strategies of the enterprise so that it can be flexibly applied in different situations. Assume that the system sets three thresholds of high importance, medium importance and low importance, so that orders can be classified into three importance levels: high, medium and low. For example, the scoring threshold of high importance orders is set to more than 8 points, the scoring threshold of medium importance orders is set to 5-8 points, and the scoring threshold of low importance orders is set to less than 5 points.

[0091] Next, the system sets the corresponding order sets based on the set multiple importance score thresholds. The high importance order set includes all orders with scores higher than 8 points, the medium importance order set includes all orders with scores between 5-8 points, and the low importance order set includes all orders with scores lower than 5 points.

[0092] Then, the system compares the scores of each enterprise's purchase order and classifies each order into a corresponding order set according to the corresponding relationship between the importance score of each order and the size of each score threshold. For example, for an order, if its importance score is 9 points, the system will classify it into the high importance order set; if its importance score is 6 points, it will be classified into the medium importance order set; if its importance score is 3 points, it will be classified into the low importance order set.

[0093] Step S6: Based on the type corresponding to each order set, determine the order tracking logic of all enterprise purchase orders in each order set.

[0094] When implementing step S6, by determining the order tracking logic of all enterprise purchase orders in each order set based on the type corresponding to each order set, targeted management can be achieved to ensure that orders of different importance receive appropriate attention and processing, thereby improving the efficiency and response speed of overall supply chain management. The purpose of this is to take different tracking measures according to the importance of the order, optimize resource allocation, and improve the accuracy and effectiveness of order management.

[0095] First, the system develops targeted order tracking logic based on the high, medium, and low importance order sets obtained in step S5. For the high-importance order set, the system sets up real-time monitoring and high-frequency update tracking logic. These orders are usually critical to the production and operation of the enterprise, so they need to be closely monitored. The system tracks the status of orders in real time by integrating various IoT devices (such as GPS, temperature and humidity sensors), and updates information instantly when the order status changes. In addition, the system sets up an abnormal situation alarm function. When an order is delayed, or the temperature and humidity are abnormal during transportation, the system will automatically send an alarm to notify relevant personnel to handle it.

[0096] For the medium-importance order set, the system sets up regular monitoring and medium-frequency update tracking logic. These orders are less important than high-importance orders, but still need to maintain a certain level of attention. The system updates the order status information daily and generates a status report for management personnel to refer to. When an abnormal situation occurs, the system generates an abnormal report and takes appropriate measures based on the specific situation.

[0097] For low-importance order sets, the system sets up regular monitoring and tracking logic for low-frequency updates. These orders have relatively little impact on the company, so they do not need to be monitored frequently. The system updates order status information once a week and generates a status summary report. Only when there is an obvious abnormality will the system generate an alarm message and notify relevant personnel to handle it.

[0098] Through the above methods, the system can formulate appropriate order tracking logic based on the type of order collection and achieve targeted management. The effect of this is that enterprises can take different tracking measures according to the importance of orders, ensure that important orders are given priority, optimize resource allocation, and improve the accuracy and effectiveness of order management. Through targeted management, enterprises can reduce resource waste and improve the overall operational efficiency and response speed of the supply chain.

[0099] Reference Figure 3 , which shows a structural schematic diagram of an enterprise purchase order tracking system provided by an embodiment of the present application, the system includes: an acquisition module 1 and a processing module 2; the acquisition module 1 is used to acquire basic information of multiple enterprise purchase orders; the processing module 2 is used to set n order tracking nodes; the acquisition module 1 is also used to acquire the transportation information of each enterprise purchase order between the i-th order tracking node and the i-1-th order tracking node, where i∈[1,n]; the processing module 2 is also used to obtain the importance score of each enterprise purchase order at the i-th order tracking node based on each basic information and each transportation information; the processing module 2 is also used to classify each enterprise purchase order based on each importance score to obtain multiple order sets corresponding to the i-th order tracking node; each order set contains at least one enterprise purchase order; the processing module 2 is also used to determine the order tracking logic of all enterprise purchase orders in each order set based on the type corresponding to each order set.

[0100] In a possible implementation, processing module 2 is further used to construct a hierarchical model based on each basic information and each transportation information; processing module 2 is further used to construct a judgment matrix based on the hierarchical model; processing module 2 is further used to calculate the eigenvector of the judgment matrix to obtain a first weight vector corresponding to each basic information and a second weight vector corresponding to each transportation information; processing module 2 is further used to obtain a comprehensive weight vector based on the first weight vector and the second weight vector; processing module 2 is further used to determine a first scoring value corresponding to each basic information, and determine a second scoring value corresponding to each transportation information at the i-th order tracking node; processing module 2 is further used to perform weighted summation of each first scoring value and each second scoring value with the comprehensive weight vector to obtain each importance score.

[0101] In a possible implementation, processing module 2 is further used to determine a target layer of the hierarchical model, the target layer being to calculate an importance score of each enterprise purchase order at the i-th order tracking node; processing module 2 is further used to determine a criterion layer under the target layer, the criterion layer comprising various basic information and various transportation information; processing module 2 is further used to determine an indicator layer under the criterion layer, the indicator layer comprising basic information indicators and transportation information indicators; basic information indicators include order amount, delivery time urgency, commodity importance and supplier reliability, and transportation information indicators include inventory level, transportation progress, transportation environment and transportation safety; processing module 2 is further used to construct a hierarchical model based on the target layer, criterion layer and indicator layer.

[0102] In a possible implementation, processing module 2 is also used to determine the relative importance of each basic information indicator based on a pairwise comparison method to construct a basic information judgment matrix; processing module 2 is also used to determine the relative importance of each transportation information indicator based on a pairwise comparison method to construct a transportation information judgment matrix.

[0103] In a possible implementation, the processing module 2 is also used to calculate the eigenvectors of the basic information judgment matrix by the eigenvalue method or normalization processing to obtain each first weight vector; the processing module 2 is also used to calculate the eigenvectors of the transportation information judgment matrix by the eigenvalue method or normalization processing to obtain each second weight vector.

[0104] In one possible implementation, processing module 2 is also used to determine a first weighting coefficient corresponding to the first weight vector and a second weighting coefficient corresponding to the second weight vector, wherein the sum of the first weighting coefficient and the second weighting coefficient is one; processing module 2 is also used to multiply each component in the first weight vector by the first weighting coefficient to obtain a first weight vector; processing module 2 is also used to multiply each component in the second weight vector by the second weighting coefficient to obtain a second weight vector; processing module 2 is also used to add the corresponding components of the first weight vector and the second weight vector to obtain a comprehensive weight vector.

[0105] In a possible implementation, processing module 2 is also used to set multiple importance score thresholds; processing module 2 is also used to set multiple order sets based on the multiple importance score thresholds; processing module 2 is also used to classify each enterprise purchase order into each order set based on the corresponding relationship between each importance score and each importance score threshold.

[0106] It should be noted that: when the device provided in the above embodiment realizes its function, only the division of the above functional modules is used as an example. In actual application, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. In addition, the device and method embodiments provided in the above embodiment belong to the same concept, and the specific implementation process is detailed in the method embodiment, which will not be repeated here.

[0107] The present application also discloses an electronic device. Figure 4 , Figure 4 The electronic device 400 may include: at least one processor 401 , at least one network interface 404 , a user interface 403 , a memory 405 , and at least one communication bus 402 .

[0108] The communication bus 402 is used to realize the connection and communication between these components.

[0109] The user interface 403 may include a display screen (Display) and a camera (Camera). Optionally, the user interface 403 may also include a standard wired interface and a wireless interface.

[0110] The network interface 404 may optionally include a standard wired interface or a wireless interface (such as a WI-FI interface).

[0111] Among them, the processor 401 may include one or more processing cores. The processor 401 uses various interfaces and lines to connect various parts in the entire server, and executes various functions of the server and processes data by running or executing instructions, programs, code sets or instruction sets stored in the memory 405, and calling data stored in the memory 405. Optionally, the processor 401 can be implemented in at least one hardware form of digital signal processing (Digital Signal Processing, DSP), field programmable gate array (Field-Programmable Gate Array, FPGA), and programmable logic array (Programmable Logic Array, PLA). The processor 401 can integrate one or a combination of a central processing unit (Central Processing Unit, CPU), a graphics processor (Graphics Processing Unit, GPU) and a modem. Among them, the CPU mainly processes the operating system, user interface and application programs; the GPU is responsible for rendering and drawing the content to be displayed on the display screen; the modem is used to process wireless communications. It can be understood that the above-mentioned modem may not be integrated into the processor 401, and it can be implemented separately through a chip.

[0112] Among them, the memory 405 may include a random access memory (Random Access Memory, RAM) and may also include a read-only memory (Read-Only Memory). Optionally, the memory 405 includes a non-transitory computer-readable storage medium. The memory 405 can be used to store instructions, programs, codes, code sets or instruction sets. The memory 405 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playback function, an image playback function, etc.), instructions for implementing the above-mentioned method embodiments, etc.; the data storage area may store data involved in the above-mentioned method embodiments, etc. The memory 405 may optionally be at least one storage device located away from the aforementioned processor 401. Refer to Figure 4 , the memory 405 as a computer-readable storage medium may include an operating system, a network communication module, a user interface module and an application program.

[0113] exist Figure 4In the electronic device 400 shown, the user interface 403 is mainly used to provide an input interface for the user and obtain the data input by the user; and the processor 401 can be used to call an application stored in the memory 405, and when executed by one or more processors 401, the electronic device 400 executes one or more methods in the above-mentioned embodiments. It should be noted that for the aforementioned method embodiments, for the sake of simple description, they are all expressed as a series of action combinations, but those skilled in the art should know that the present application is not limited by the described order of actions, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required for the present application.

[0114] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0115] In the several embodiments provided in this application, it should be understood that the disclosed devices can be implemented in other ways. For example, the device embodiments described above are only schematic, such as the division of units, which is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some service interfaces, and the indirect coupling or communication connection of devices or units can be electrical or other forms.

[0116] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0117] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0118] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, which is stored in a memory and includes several instructions for a computer device (which can be a personal computer, server or network device, etc.) to execute all or part of the steps of the various embodiments of the present application. The aforementioned memory includes: various media that can store program codes, such as USB flash drives, mobile hard drives, magnetic disks or optical disks.

[0119] The above are only exemplary embodiments of the present disclosure and cannot be used to limit the scope of the present disclosure. That is, any equivalent changes and modifications made according to the teachings of the present disclosure are still within the scope of the present disclosure. After considering the disclosure of the specification and the truth of practice, those skilled in the art will easily think of other embodiments of the present disclosure.

[0120] This application is intended to cover any variation, use or adaptation of the present disclosure, which follows the general principles of the present disclosure and includes common knowledge or customary technical means in the art not described in the present disclosure. The description and examples are to be regarded as exemplary only, and the scope and spirit of the present disclosure are defined by the claims.

Claims

1. A method for tracking enterprise purchase orders, characterized in that: The method comprises: Obtain basic information of purchase orders of multiple enterprises; Set n order tracking nodes; Obtaining the transportation information of each of the enterprise purchase orders between the i-th order tracking node and the i-1-th order tracking node, where i∈[1,n]; Based on each of the basic information and each of the transportation information, obtain an importance score of each of the enterprise purchase orders at the i-th order tracking node; Based on each of the importance scores, each of the enterprise purchase orders is classified to obtain a plurality of order sets corresponding to the i-th order tracking node; wherein each of the order sets contains at least one of the enterprise purchase orders; Based on the type corresponding to each of the order sets, the order tracking logic of all enterprise purchase orders in each of the order sets is determined.

2. The method according to claim 1, characterized in that The obtaining of the importance score of each enterprise purchase order at the i-th order tracking node based on each of the basic information and each of the transportation information specifically includes: Building a hierarchical structure model based on each of the basic information and each of the transportation information; Based on the hierarchical structure model, construct a judgment matrix; Calculating the eigenvector of the judgment matrix to obtain a first weight vector corresponding to each of the basic information and a second weight vector corresponding to each of the transportation information; Obtaining a comprehensive weight vector based on the first weight vector and the second weight vector; Determine a first scoring value corresponding to each of the basic information, and determine a second scoring value corresponding to each of the transportation information at the i-th order tracking node; Perform a weighted summation of each of the first scoring values, each of the second scoring values, and the comprehensive weight vector to obtain each of the importance scores.

3. The method according to claim 2, characterized in that The constructing of a hierarchical structure model based on each of the basic information and each of the transportation information specifically includes: Determining a target layer of the hierarchical model, wherein the target layer is to calculate the importance score of each of the enterprise purchase orders at the i-th order tracking node; Determine a criterion layer under the target layer, wherein the criterion layer includes each of the basic information and each of the transportation information; Determine an indicator layer under the criterion layer, wherein the indicator layer includes basic information indicators and transportation information indicators; the basic information indicators include order amount, delivery time urgency, commodity importance and supplier reliability, and the transportation information indicators include inventory level, transportation progress, transportation environment and transportation safety; The hierarchical structure model is constructed based on the target layer, the criterion layer and the indicator layer.

4. The method according to claim 3, characterized in that The judgment matrix includes a basic information judgment matrix and a transportation information judgment matrix; the judgment matrix is ​​constructed based on the hierarchical structure model, specifically including: Determine the relative importance of each of the basic information indicators based on a pairwise comparison method, and construct the basic information judgment matrix; The relative importance of each of the transportation information indicators is determined based on a pairwise comparison method, and the transportation information judgment matrix is ​​constructed.

5. The method according to claim 2, characterized in that: The judgment matrix includes a basic information judgment matrix and a transportation information judgment matrix; the calculating of the eigenvector of the judgment matrix to obtain the first weight vector corresponding to each basic information and the second weight vector corresponding to each transportation information specifically includes: Calculating the eigenvectors of the basic information judgment matrix by an eigenvalue method or normalization processing to obtain each of the first weight vectors; The eigenvalue method or normalization processing is used to calculate the eigenvectors of the transportation information judgment matrix to obtain each of the second weight vectors.

6. The method according to claim 2, characterized in that The obtaining a comprehensive weight vector based on the first weight vector and the second weight vector specifically includes: Determine a first weighting coefficient corresponding to the first weight vector and a second weighting coefficient corresponding to the second weight vector, wherein a sum of the first weighting coefficient and the second weighting coefficient is one; multiplying each component in the first weight vector by the first weight coefficient to obtain a first weight vector; multiplying each component in the second weight vector by the second weight coefficient to obtain a second weight vector; The first weighted vector and the corresponding components of the second weighted vector are added to obtain the comprehensive weight vector.

7. The method according to claim 1, characterized in that Based on each of the importance scores, each of the enterprise purchase orders is classified to obtain multiple order sets corresponding to the i-th order tracking node, specifically including: Set multiple importance scoring thresholds; Based on a plurality of importance scoring thresholds, setting a plurality of order sets; Based on the corresponding relationship between each importance score and each importance score threshold, each enterprise procurement order is classified into each order set.

8. An enterprise purchase order tracking system, characterized in that: The system comprises: an acquisition module and a processing module; The acquisition module is used to acquire basic information of multiple enterprise purchase orders; The processing module is used to set n order tracking nodes; The acquisition module is further used to acquire the transportation information of each of the enterprise purchase orders between the i-th order tracking node and the i-1-th order tracking node, where i∈[1,n]; The processing module is further used to obtain the importance score of each of the enterprise purchase orders at the i-th order tracking node based on each of the basic information and each of the transportation information; The processing module is further used to classify each of the enterprise purchase orders based on each of the importance scores to obtain a plurality of order sets corresponding to the i-th order tracking node; wherein each of the order sets contains at least one of the enterprise purchase orders; The processing module is further used to determine the order tracking logic of all enterprise purchase orders in each of the order sets based on the type corresponding to each of the order sets.

9. An electronic device, characterized in that: The electronic device (400) comprises a processor (401), a memory (405), a user interface (403) and a network interface (404), wherein the memory (405) is used to store instructions, the user interface (403) and the network interface (404) are used to communicate with other devices, and the processor (401) is used to execute the instructions stored in the memory (405) so that the electronic device (400) executes the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores instructions, and when the instructions are executed, the method according to any one of claims 1 to 7 is executed.

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