A method and device for calibrating a cargo source dispatch priority

Abstract

The application discloses a kind of calibration method and device of goods source scheduling priority, wherein calibration method includes: combing the condition factor of influence pending matching goods source priority;For each condition factor binding trigger event, get the mapping relationship of trigger event and condition factor;Through the configuration interface of visual rule engine, the generation rule of priority label is configured in tree-shaped logic combination mode;When trigger event occurs, real-time positioning affected condition factor and updating its value, load label rule dependent on the condition factor, generate or update goods source priority label by recursive operation tree-shaped logic of rule engine;Through visual interface, priority label generation rule is configured in real time, strategy can be adjusted without code iteration, in addition, based on event-driven mechanism, when the event associated with any influence factor occurs, real-time trigger label recalculation, ensure that label and business state are synchronized, can greatly reduce user threshold and strong flexibility.

Description

Technical Field

[0001] This invention relates to the field of logistics and transportation, and in particular to a method and apparatus for determining the priority of cargo dispatching. Background Technology

[0002] In the current technical field of freight platform scheduling systems, cargo priority tags are the core basis for guiding dispatchers in matching cargo and allocating resources. Existing systems mainly use fixed rules to generate cargo priority tags, which has the following key problems:

[0003] First, the rules lack flexibility: fixed rules cannot adapt to real-time changing business scenarios. When there is a sudden increase or decrease in cargo volume or adjustments to dispatching manpower (such as manpower shortages during peak hours and ample manpower during off-peak hours), employees cannot adjust priority judgment strategies in real time. For example, when there is sufficient capacity, high-value cargo (with higher markups by shippers) should be prioritized, while when there is a shortage of capacity, cargo with high success rates (predicted by algorithms) should be prioritized. The existing system requires iterative code modifications to the rules, resulting in long response cycles and failing to meet real-time business needs.

[0004] Second, the real-time performance of tag generation is poor: the factors affecting the priority of cargo sources are complex. The existing system uses a timed polling method (such as updating the tag every 30 minutes) to calculate the tag, which leads to a lag in tag updates. This may result in situations where "the cargo owner has increased the price but the tag has not been updated, and the dispatcher has not prioritized processing it," which affects the efficiency of cargo matching.

[0005] In summary, existing fixed-rule-driven cargo identification methods can no longer meet the core needs of freight dispatching scenarios, and there is an urgent need for a cargo identification method that can dynamically configure rules and respond to event changes in real time. Summary of the Invention

[0006] To address the aforementioned issues, this invention provides a method for prioritizing cargo dispatching, comprising: identifying conditional factors influencing the priority of cargo to be matched, wherein the conditional factors encompass algorithm prediction dimensions, cargo owner operation dimensions, driver operation dimensions, dispatching behavior dimensions, and cargo attribute dimensions; binding trigger events to each conditional factor to obtain a mapping relationship between the trigger events and the conditional factors, wherein the trigger events are business operations that can cause changes in the value of the conditional factors; configuring priority label generation rules in a tree-like logical combination manner through a visual rule engine configuration interface, wherein the rules are combinations of threshold values ​​and logical relationships of the conditional factors; when a trigger event occurs, locating the affected conditional factor in real time and updating its value, loading the label rules that depend on the conditional factor, and generating or updating the cargo priority label after recursively calculating the tree logic through the rule engine.

[0007] Optionally, the conditional factors for the algorithm's prediction dimension include the predicted transaction rate, which is calculated based on the system algorithm of the price platform.

[0008] Optionally, the shipper's operation dimensions include one or more of the following: shipper's markup amount, shipper's markup percentage, shipper's message status, shipper's online status, and number of times the shipper urges the order.

[0009] Optionally, the scheduling behavior dimension includes one or more of the following: scheduling follow-up number and scheduling callback number.

[0010] Optionally, the cargo attribute dimensions include cargo listing duration, vehicle type required for cargo, and one or more of the matching transportation capacity pool.

[0011] Optionally, the priority label generation rules can be configured in a tree-like logical combination manner through the visual rule engine configuration interface, including: selecting the priority label to be configured in the visual rule engine configuration interface; creating a logical group, wherein the logical group includes condition factors and the logical relationships between condition factors; and setting a judgment threshold for each condition factor.

[0012] Optionally, the step of locating the affected condition factors and updating their values ​​in real time when a trigger event occurs, loading the tag rules that depend on the condition factors, and generating or updating the source priority tags after recursively operating the tree logic through the rule engine includes: listening to all business events; extracting event information when an event occurs; locating the affected condition factors according to the mapping relationship between the trigger event and the condition factors, extracting new factor values ​​from the event information, and updating them to the real-time database; querying all priority tag rules that depend on the factor in the rule engine; loading all current factor values ​​of the source and performing recursive operations according to the tree logic structure of the rules.

[0013] If the calculation result meets the tagging rules, a corresponding tag is generated for the goods; if multiple tagging rules are met at the same time, the final tag is determined according to the preset priority, and the tag is updated to the search engine and MySQL database.

[0014] Optionally, all business events are monitored through a message queue.

[0015] On the other hand, the present invention also provides a calibration device for cargo dispatch priority, characterized in that it includes: a sorting unit for sorting out conditional factors affecting the priority of cargo to be matched, wherein the conditional factors cover algorithm prediction dimension, cargo owner operation dimension, driver operation dimension, dispatch behavior dimension, and cargo attribute dimension; a binding unit for binding trigger events to each conditional factor to obtain the mapping relationship between the trigger events and the conditional factors, wherein the trigger events are business operations that can cause changes in the value of the conditional factors; a configuration unit for configuring priority label generation rules in a tree-like logical combination manner through a visual rule engine configuration interface, wherein the rules are a combination of thresholds and logical relationships of the conditional factors; and a calibration unit for locating the affected conditional factors in real time and updating their values ​​when the trigger event occurs, loading the label rules that depend on the conditional factors, and generating or updating cargo priority labels after recursively calculating the tree logic through the rule engine.

[0016] The advantages of this invention over the prior art are:

[0017] 1. Significantly improved rule flexibility: Through the visual rule engine, employees can adjust priority strategies in real time, and the rule effective time is greatly shortened to adapt to dynamic changes in business scenarios;

[0018] 2. Improved real-time tag generation: Based on an event-driven mechanism, the tag update delay is significantly reduced, ensuring that the tags obtained by dispatchers are consistent with the latest status of the goods, reducing the situation where high-priority goods are not processed in a timely manner;

[0019] 3. Lower the operational threshold: Rule configuration can be completed without code development, and non-technical employees can operate independently, reducing reliance on R&D resources;

[0020] 4. High scalability: Supports adding new condition factors and triggering events. Only the factor definitions and the mapping relationship between triggering events and condition factors need to be added to the system, without modifying the core calculation logic. Attached Figure Description

[0021] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0022] Figure 1 This is a flowchart of a method for determining the priority of cargo scheduling provided by the present invention;

[0023] Figure 2 This is a structural diagram of a cargo scheduling priority calibration device provided by the present invention. Detailed Implementation

[0024] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0025] Reference Figure 1 This embodiment provides a method for determining the priority of cargo scheduling, including the following steps:

[0026] S10: Identify the factors that influence the priority of cargo sources to be matched, including algorithm prediction dimension, cargo owner operation dimension, driver operation dimension, dispatch behavior dimension, and cargo source attribute dimension.

[0027] Based on market research, this embodiment derives the following conditional factors, covering dimensions such as algorithm prediction, cargo owner operation, driver operation, dispatching behavior, and cargo attribute, as shown in Table 1.

[0028] Table 1 Condition Factor Table

[0029]

[0030] It should be noted that users can modify, add, or delete the condition factor names and related definitions of the above dimensions as needed.

[0031] It should also be noted that the system algorithm used in predicting the success rate is an existing prediction algorithm, which is not within the scope of protection of this embodiment.

[0032] S20: Bind a trigger event to each condition factor to obtain the mapping relationship between the trigger event and the condition factor. The trigger event is a business operation that can cause a change in the value of the condition factor.

[0033] Specifically, each triggering event that can cause a change in factor value is bound to a specific event, forming a mapping relationship between the triggering event and the conditional factor. This ensures that the affected conditional factor can be accurately located when any event occurs. Some of the relationships in this embodiment are shown in Table 2 below:

[0034] Table 2. Mapping Relationships Related to Conditions

[0035]

[0036] It should be noted that users can modify, add, or delete the above conditions according to their needs due to the associated mapping relationships.

[0037] S30: Configure the priority label generation rules through the visual rule engine configuration interface in a tree-like logical combination manner. The rules are combinations of thresholds and logical relationships of condition factors.

[0038] Specifically, in the visual rule configuration interface, priority label (such as SS, S, A, B, C, J levels) generation rules can be configured without coding by dragging and dropping factors, setting thresholds, and configuring logical relationships. Rule configuration supports tree-like logical combinations, meaning it supports nested "AND (&&)" and "OR (||)" logic between multiple factors. The specific configuration process is as follows:

[0039] First, select the tag type: In the interface, select the priority tag to be configured, such as SS-level tag.

[0040] Next, create logic groups, which include condition factors and the logical relationships between them; such as "predicted transaction rate" and "owner's markup ratio" are added to the condition group.

[0041] Then, set factor thresholds: set a judgment threshold for each factor (such as "predicted transaction rate ≥ 80%" and "owner markup ratio ≥ 10%").

[0042] Finally, configure nested logic: add sub-condition groups within condition groups to achieve multi-level nested logic (e.g., "(Predicted transaction rate ≥ 80% && Cargo owner markup ratio ≥ 10%) || (Number of drivers with markup ≥ 5 && Driver markup ratio ≥ 15%)").

[0043] It should also be noted that after configuring the nested logic, the rules need to be saved so that the rules take effect in real time and are stored in the rule database.

[0044] S40: When a trigger event occurs, locate the affected condition factors in real time and update their values, load the label rules that depend on the condition factors, and generate or update the source priority labels after recursively calculating the tree logic through the rule engine.

[0045] Specifically, an event-driven tagging mechanism is implemented based on a rules engine. When any event is triggered, the cargo priority tag is updated in real time through a process of event capture, factor update, rule matching, and tag generation. The specific steps are as follows:

[0046] First, listen for all business events through a message queue (Kafka). When an event occurs, extract the event information, such as the source ID and event type.

[0047] Next, the affected condition factors are located based on the mapping relationship between the triggering event and the condition factors, and new factor values ​​are extracted from the event information and updated to the real-time database.

[0048] Then, query all priority tag rules in the rule engine that depend on this factor. For example, when the cargo owner's markup percentage factor changes, query all SS-level and S-level rules that contain this factor.

[0049] Then, load all the current factor values ​​of the source and perform recursive calculations according to the tree-like logical structure of the rules. For example, calculate the results of the sub-condition group first, and then calculate the results of the parent condition group.

[0050] Finally, if the calculation result meets the tagging rules, a corresponding tag is generated for the goods; if multiple tagging rules are met at the same time, the final tag is determined according to the preset priority (such as SS level > S level > A level), and the tag is updated to the search engine (and MySQL database).

[0051] The cargo scheduling priority labeling method described in this embodiment allows for real-time configuration of priority label generation rules through a visual interface, enabling strategy adjustments without code iteration. Furthermore, based on an event-driven mechanism, when any event associated with an influencing factor occurs, the label is recalculated in real time, ensuring that the label is synchronized with the business status. This significantly reduces the user threshold and offers high flexibility.

[0052] Reference Figure 2 This embodiment also provides a calibration device for cargo scheduling priority, including:

[0053] Sorting Unit 100: Used to sort out the conditional factors that affect the priority of cargo sources to be matched. The conditional factors cover the algorithm prediction dimension, cargo owner operation dimension, driver operation dimension, dispatch behavior dimension, and cargo source attribute dimension. It should be noted that since the specific sorting method and process have been described in detail in step S10 of the above-mentioned cargo source dispatch priority calibration method, they will not be repeated here.

[0054] Binding unit 200 is used to bind trigger events to each condition factor to obtain the mapping relationship between trigger events and condition factors. The trigger event is a business operation that can cause a change in the value of the condition factor. It should be noted that since the specific binding method and process have been described in detail in step S20 of the above-mentioned method for calibrating the priority of cargo scheduling, they will not be repeated here.

[0055] Configuration unit 300 is used to configure the priority label generation rules in a tree-like logical combination manner through the visual rule engine configuration interface. The rules are the combination of threshold and logical relationship of condition factors. It should be noted that since the specific configuration method and process have been described in detail in step S30 of the above-mentioned method for marking the priority of cargo scheduling, they will not be repeated here.

[0056] The calibration unit 400, when a trigger event occurs, locates the affected condition factors in real time and updates their values, loads the label rules that depend on the condition factors, and generates or updates the source priority labels after recursively operating the tree logic through the rule engine. It should be noted that since the specific calibration method and process have been described in detail in step S40 of the above-mentioned source scheduling priority calibration method, they will not be repeated here.

[0057] In addition, embodiments of the present invention also provide a computer-readable storage medium, wherein the computer-readable storage medium may store a program, which, when executed, includes some or all of the steps of any cargo scheduling priority calibration method described in the above method embodiments.

[0058] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0059] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage device (CMD). Based on this understanding, the technical solution of this invention, in essence, 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. This computer software product is stored in a memory and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this invention. The aforementioned memory includes various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0060] Those skilled in the art will understand that all or part of the steps in the various methods of the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage device, which may include: a flash drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk, etc.

[0061] The above description, with reference to the accompanying drawings, illustrates an exemplary flowchart of a method for prioritizing cargo scheduling according to an embodiment of the present invention. It should be noted that the numerous details included in the above description are merely illustrative of the invention and not intended to limit it. In other embodiments of the invention, the method may have more, fewer, or different steps, and the order, inclusion, function, and other relationships between the steps may differ from those described and illustrated.

Claims

1. A method for determining the priority of cargo dispatching, characterized in that, include: The factors influencing the priority of pending cargo matching are summarized, encompassing algorithmic prediction, shipper operation, driver operation, dispatching behavior, and cargo attribute dimensions. The algorithmic prediction dimension includes the predicted success rate, calculated based on the pricing platform's system algorithm. The shipper operation dimension includes one or more of the following: shipper markup amount, shipper markup percentage, shipper message status, shipper in-line status, and number of shipper order reminders. The dispatching behavior dimension includes one or more of the following: number of dispatch follow-ups and number of dispatch callbacks. The cargo attribute dimension includes one or more of the following: cargo listing duration, vehicle type required for the cargo, and suitable capacity pool. The driver operation dimension includes the driver markup amount and driver markup percentage. A trigger event is bound to each condition factor to obtain the mapping relationship between the trigger event and the condition factor. The trigger event is a business operation that can cause a change in the value of the condition factor. The priority label generation rules are configured through the visual rule engine configuration interface in a tree-like logical combination manner. The rules are combinations of thresholds and logical relationships of condition factors. When a trigger event occurs, the affected condition factors are located and their values ​​are updated in real time. Tag rules that depend on the condition factors are loaded, and the source priority tags are generated or updated after the tree logic is recursively calculated by the rule engine.

2. The calibration method according to claim 1, characterized in that, The priority label generation rules are configured in a tree-like logical combination manner through the visual rule engine configuration interface, including: selecting the priority label to be configured in the visual rule engine configuration interface; creating a logic group, which includes condition factors and the logical relationships between condition factors; and setting a judgment threshold for each condition factor.

3. The calibration method according to claim 1, characterized in that, When a triggering event occurs, the affected conditional factors are located in real time and their values ​​are updated. Tag rules that depend on the conditional factors are loaded, and priority tags for goods are generated or updated after recursively calculating the tree logic of the rule engine. This includes: listening to all business events; extracting event information when an event occurs; locating the affected conditional factors according to the mapping relationship between triggering events and conditional factors, extracting new factor values ​​from the event information, and updating them to the real-time database; querying all priority tag rules that depend on the factor in the rule engine; loading all current factor values ​​of the goods and performing recursive calculations according to the tree logic structure of the rules; generating corresponding tags for the goods if the calculation result satisfies the tag rules; and determining the final tag according to a preset priority if multiple tag rules are satisfied simultaneously, and updating the tags to the search engine and MySQL database.

4. The calibration method according to claim 3, characterized in that: All business events are monitored through a message queue.

5. A device for determining the priority of cargo dispatching, characterized in that, include: The sorting unit is used to sort out the conditional factors affecting the priority of cargo to be matched. These conditional factors cover algorithm prediction, cargo owner operation, driver operation, dispatch behavior, and cargo attribute dimensions. The algorithm prediction dimension includes the predicted success rate, which is calculated based on the pricing platform's system algorithm. The cargo owner operation dimension includes one or more of the following: cargo owner premium amount, cargo owner premium percentage, cargo owner message status, cargo owner online status, and cargo owner order reminders. The dispatch behavior dimension includes one or more of the following: dispatch follow-up times and dispatch callback times. The cargo attribute dimension includes one or more of the following: cargo listing duration, vehicle type required for the cargo, and suitable capacity pool. The driver operation dimension includes the driver premium amount and driver premium percentage. The binding unit is used to bind a trigger event to each condition factor to obtain the mapping relationship between the trigger event and the condition factor. The trigger event is a business operation that can cause a change in the value of the condition factor. The configuration unit is used to configure the generation rules of priority labels in a tree-like logical combination manner through the configuration interface of the visual rule engine. The rules are a combination of thresholds and logical relationships of condition factors. The calibration unit is used to locate the affected condition factors in real time and update their values ​​when a trigger event occurs, load the label rules that depend on the condition factors, and generate or update the source priority labels after recursively calculating the tree logic through the rule engine.

6. A computer-readable storage medium, comprising a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of a method for determining the priority of cargo scheduling as described in any one of claims 1 to 4.

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