CN116739316A - Automatic dispatching method and system for emergency tasks - Google Patents
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Abstract
The invention discloses an automatic dispatching method and system for emergency tasks, wherein the method comprises the following steps: acquiring task information and task processing personnel information, wherein the task information comprises: the number of tasks, the urgency of each task, and the skill value required to complete the task, the task processor information includes: the number of task processing personnel and the skill value of the task processing personnel; setting an emergency task dispatch model, inputting the task information and the task processor information into the emergency task dispatch model, and calculating a task dispatch score of each task, wherein the emergency task dispatch model comprises: sequencing the emergency degrees of the tasks through a sequencing function, and calculating the skill matching degree between the tasks and task processing personnel; and distributing the corresponding tasks according to the score according to the task distribution score.
Description
Technical Field
The invention belongs to the technical field of automatic dispatch of emergency tasks, and particularly relates to an automatic dispatch method and system of emergency tasks.
Background
The automatic dispatch method for emergency tasks can be realized by the following steps:
task collection: a task collection system is built to receive user reported emergency tasks through various channels (e.g., telephone, email, mobile applications). These tasks may be various types of emergency events such as equipment failure, safety issues, or customer complaints.
Task classification: a task classification system is developed to classify received tasks according to criteria such as type, urgency, and skill required. This helps determine the team or individual who is appropriate to handle each task.
Automatic dispatch system: based on the task allocation rules, an automatic dispatch system is developed. The system may be an intelligent algorithm or software program that automatically assigns tasks to the appropriate team or person based on the attributes and rules of the task.
Task tracking and monitoring: a task tracking and monitoring system is built to track the status and process progress of tasks in real time. This can help the manager to know the allocation and processing efficiency of tasks, and to adjust and intervene in time.
Feedback and improvement: and collecting feedback of users and teams, evaluating the effect of the automatic dispatch system, and improving according to the feedback result. The dispatch rules and algorithms are continually optimized to improve the processing efficiency of tasks and user satisfaction.
However, the task distribution system in the prior art is too simple and has low intelligent degree.
Disclosure of Invention
In order to solve the technical problems, the invention provides an automatic dispatching method for emergency tasks, which comprises the following steps:
acquiring task information and task processing personnel information, wherein the task information comprises: the number of tasks, the urgency of each task, and the skill value required to complete the task, the task processor information includes: the number of task processing personnel and the skill value of the task processing personnel;
setting an emergency task dispatch model, inputting the task information and the task processor information into the emergency task dispatch model, and calculating a task dispatch score of each task, wherein the emergency task dispatch model comprises: sequencing the emergency degrees of the tasks through a sequencing function, and calculating the skill matching degree between the tasks and task processing personnel;
and distributing the corresponding tasks according to the score according to the task distribution score.
Further, the emergency task dispatch model is as follows:
，
wherein S is the task dispatch score, D is the task urgency attenuation factor, U is the task urgency,for the ranking function, for ranking the urgency U of the plurality of tasks, +.>The skill matching degree weight is that M is the skill matching degree between the task and the task processing personnel, b is the distance weight, L is the distance between the task and the task processing personnel, and P is the resource load balancing factor of the task.
Further, the ranking functionThe method comprises the following steps:
，
where N is the number of tasks participating in the ranking,for the weight of the compensation factor +.>In order to adjust the weight of the factor,for ranking of tasks, ++>For a compensation factor based on urgency and skill matching of tasks, for correcting ranking of tasks, ++>Is an adjustment factor based on the distance between the task and the task processing personnel and the resource load balance.
Further, the skill matching degree M between the task and the task processing personnel is:
,
wherein ,is the weight of cosine similarity, +.>For the skill value required for the task, T is the skill value of the task processor, < ->Weight of Euclidean distance, +.>Euclidean distance of skill values required for completing a task and skill values of task processing personnel.
Further, the resource load balancing factor P of the task is: ratio of task processor to total amount of tasks.
The invention also provides an automatic dispatch system for emergency tasks, which comprises the following steps:
the information acquisition module is used for acquiring task information and task processing personnel information, wherein the task information comprises: the number of tasks, the urgency of each task, and the skill value required to complete the task, the task processor information includes: the number of task processing personnel and the skill value of the task processing personnel;
the setting model module is used for setting an emergency task dispatch model, inputting the task information and the task processor information into the emergency task dispatch model, and calculating the task dispatch score of each task, wherein the emergency task dispatch model comprises: sequencing the emergency degrees of the tasks through a sequencing function, and calculating the skill matching degree between the tasks and task processing personnel;
and the dispatch module is used for dispatching the corresponding tasks according to the scores according to the task dispatching scores and the scores.
Further, the emergency task dispatch model is as follows:
,
wherein S is the task dispatch score, D is the task urgency attenuation factor, U is the task urgency,for the ranking function, for ranking the urgency U of the plurality of tasks, +.>The skill matching degree weight is that M is the skill matching degree between the task and the task processing personnel, b is the distance weight, L is the distance between the task and the task processing personnel, and P is the resource load balancing factor of the task.
Further, the ranking functionThe method comprises the following steps:
，
where N is the number of tasks participating in the ranking,for the weight of the compensation factor +.>In order to adjust the weight of the factor,for ranking of tasks, ++>For a compensation factor based on urgency and skill matching of tasks, for correcting ranking of tasks, ++>Is an adjustment factor based on the distance between the task and the task processing personnel and the resource load balance.
Further, the skill matching degree M between the task and the task processing personnel is:
，
wherein ,is the weight of cosine similarity, +.>For the skill value required for the task, T is the skill value of the task processor, < ->Weight of Euclidean distance, +.>Euclidean distance of skill values required for completing a task and skill values of task processing personnel.
Further, the resource load balancing factor P of the task is: ratio of task processor to total amount of tasks.
In general, the above technical solutions conceived by the present invention have the following beneficial effects compared with the prior art:
the invention obtains task information and task processing personnel information, wherein the task information comprises: the number of tasks, the urgency of each task, and the skill value required to complete the task, the task processor information includes: the number of task processing personnel and the skill value of the task processing personnel; setting an emergency task dispatch model, inputting the task information and the task processor information into the emergency task dispatch model, and calculating a task dispatch score of each task, wherein the emergency task dispatch model comprises: sequencing the emergency degrees of the tasks through a sequencing function, and calculating the skill matching degree between the tasks and task processing personnel; and distributing the corresponding tasks according to the score according to the task distribution score. According to the technical scheme, the task can be automatically dispatched according to the emergency degree of the task, the skills of task processing personnel and other parameters.
Drawings
FIG. 1 is a flow chart of the method of embodiment 1 of the present invention;
FIG. 2 is a block diagram of the system of embodiment 2 of the present invention;
fig. 3 is a flow chart of the ranking function of embodiment 1 of the present invention.
Detailed Description
In order to better understand the above technical solutions, the following detailed description will be given with reference to the accompanying drawings and specific embodiments.
The method provided by the invention can be implemented in a terminal environment, wherein the terminal can comprise one or more of the following components: processor, storage medium, and display screen. Wherein the storage medium has stored therein at least one instruction that is loaded and executed by the processor to implement the method described in the embodiments below.
The processor may include one or more processing cores. The processor connects various parts within the overall terminal using various interfaces and lines, performs various functions of the terminal and processes data by executing or executing instructions, programs, code sets, or instruction sets stored in the storage medium, and invoking data stored in the storage medium.
The storage medium may include a random access Memory (Random Access Memory, RAM) or a Read-Only Memory (ROM). The storage medium may be used to store instructions, programs, code sets, or instructions.
The display screen is used for displaying a user interface of each application program.
All subscripts in the formula of the invention are only used for distinguishing parameters and have no practical meaning.
In addition, it will be appreciated by those skilled in the art that the structure of the terminal described above is not limiting and that the terminal may include more or fewer components, or may combine certain components, or a different arrangement of components. For example, the terminal further includes components such as a radio frequency circuit, an input unit, a sensor, an audio circuit, a power supply, and the like, which are not described herein.
Example 1
As shown in fig. 1, an embodiment of the present invention provides an automatic emergency task dispatching method, including:
step 101, acquiring task information and task processing personnel information, wherein the task information comprises: the number of tasks, the urgency of each task, and the skill value required to complete the task, the task processor information includes: the number of task processing personnel and the skill value of the task processing personnel;
step 102, setting an emergency task dispatch model, inputting the task information and the task processor information into the emergency task dispatch model, and calculating a task dispatch score of each task, wherein the emergency task dispatch model comprises: sequencing the emergency degrees of the tasks through a sequencing function, and calculating the skill matching degree between the tasks and task processing personnel;
specifically, the emergency task dispatch model is as follows:
，
wherein S is the task dispatch score, D is the task urgency attenuation factor, and the time sensitivity of the task is considered to be in emergencyIn a task, time is usually one of the key factors, so a decay factor can be introduced to represent the decay of the task urgency with time, U is the task urgency,for the ranking function, for ranking the urgency U of the plurality of tasks, +.>For skill matching degree weight, M is skill matching degree between task and task processing personnel, b is distance weight, L is distance between task and task processing personnel, if the geographical position of task is close to the position of team member or person, the value is larger, otherwise, the value is smaller, and P is resource load balancing factor of task.
Specifically, the ranking functionThe method comprises the following steps:
，
where N is the number of tasks participating in the ranking,for the weight of the compensation factor +.>In order to adjust the weight of the factor,for ranking of tasks, ++>For compensation factors based on urgency and skill matching of tasks, for correcting the ranking of tasks, e.g. if the urgency of tasks is high and matches the skill level of team members, the ranking of tasks may be increased,/->To adjust factors based on the distance between the task and the task handler and the resource load balancing, for example, if the geographic location of the task is close to the location of team members or individuals and facilitates resource load balancing, the rank of the task may be increased, with each factor x, the tasks are ranked according to their value, from minimum to maximum.
Specifically, as shown in fig. 3, one example is:
1. assigning an initial ranking to each task, wherein the initial ranking is 1;
2. for tasks with the same degree of urgency, setting their ranks to average ranks;
3. for tasks with different degrees of urgency, different ranks are allocated according to the magnitudes of the values;
4. the ranks of all tasks are calculated.
This ranking method ensures that higher ranking can be achieved for higher urgency tasks without gaps between rankings, and at the same time, it can handle cases with the same urgency and equally distribute their rankings.
Specifically, the skill matching degree M between the task and the task processing personnel is:
,
wherein ,is the weight of cosine similarity, +.>For the skill value required for the task, T is the skill value of the task processor, < ->Weight of Euclidean distance, +.>Skill level required for completing task and skill level of task processorEuclidean distance of (2) represents the straight line distance between two vectors, and smaller values represent higher skill matching degree, euclidean distance +.>Measure skill vector required for task->A smaller distance from the team member or person's skill vector T indicates a higher skill match, so the euclidean distance term is added with a negative sign in order for the euclidean distance in the formula to have the same direction as the cosine similarity term>Skill vector required for representing task>And cosine similarity between team members or individuals' skill vectors T. The cosine similarity ranges from-1 to 1, the closer the value is to 1, the higher the skill matching degree is, and by combining the two indexes, the influence of Euclidean distance on the skill matching degree can be considered while the cosine similarity is considered, and the parameters are-> and />The method can be adjusted according to actual requirements to balance the contribution of the two indexes in skill matching degree calculation.
Specifically, the resource load balancing factor P of the task is: ratio of task processor to total amount of tasks.
And step 103, distributing the corresponding tasks according to the score according to the task distribution score.
Example 2
As shown in fig. 2, an embodiment of the present invention further provides an emergency task automation dispatch system, including:
the information acquisition module is used for acquiring task information and task processing personnel information, wherein the task information comprises: the number of tasks, the urgency of each task, and the skill value required to complete the task, the task processor information includes: the number of task processing personnel and the skill value of the task processing personnel;
the setting model module is used for setting an emergency task dispatch model, inputting the task information and the task processor information into the emergency task dispatch model, and calculating the task dispatch score of each task, wherein the emergency task dispatch model comprises: sequencing the emergency degrees of the tasks through a sequencing function, and calculating the skill matching degree between the tasks and task processing personnel;
specifically, the emergency task dispatch model is as follows:
,
wherein S is the task dispatch score, D is the task urgency attenuation factor, U is the task urgency,for the ranking function, for ranking the urgency U of the plurality of tasks, +.>The skill matching degree weight is that M is the skill matching degree between the task and the task processing personnel, b is the distance weight, L is the distance between the task and the task processing personnel, and P is the resource load balancing factor of the task.
Specifically, the ranking functionThe method comprises the following steps:
,
where N is the number of tasks participating in the ranking,for the weight of the compensation factor +.>In order to adjust the weight of the factor,for ranking of tasks, ++>For a compensation factor based on urgency and skill matching of tasks, for correcting ranking of tasks, ++>Is an adjustment factor based on the distance between the task and the task processing personnel and the resource load balance.
Specifically, the skill matching degree M between the task and the task processing personnel is:
,
wherein ,is the weight of cosine similarity, +.>Skill value required for completing a task +.>Skill value for task processor +.>Weight of Euclidean distance, +.>Euclidean distance of skill values required for completing a task and skill values of task processing personnel.
Specifically, the resource load balancing factor P of the task is: ratio of task processor to total amount of tasks.
And the dispatch module is used for dispatching the corresponding tasks according to the scores according to the task dispatching scores and the scores.
Example 3
The embodiment of the invention also provides a storage medium which stores a plurality of instructions for realizing the automatic dispatch method of the emergency task.
Alternatively, in this embodiment, the storage medium may be located in any one of the computer terminals in the computer terminal group in the computer network, or in any one of the mobile terminals in the mobile terminal group.
Alternatively, in the present embodiment, the storage medium is configured to store program code for performing the steps of: step 101, acquiring task information and task processing personnel information, wherein the task information comprises: the number of tasks, the urgency of each task, and the skill value required to complete the task, the task processor information includes: the number of task processing personnel and the skill value of the task processing personnel;
step 102, setting an emergency task dispatch model, inputting the task information and the task processor information into the emergency task dispatch model, and calculating a task dispatch score of each task, wherein the emergency task dispatch model comprises: sequencing the emergency degrees of the tasks through a sequencing function, and calculating the skill matching degree between the tasks and task processing personnel;
specifically, the emergency task dispatch model is as follows:
,
wherein S is the task dispatch score, D is the task urgency attenuation factor, U is the task urgency,for the ranking function, for ranking the urgency U of the plurality of tasks, +.>The skill matching degree weight is that M is the skill matching degree between the task and the task processing personnel, b is the distance weight, L is the distance between the task and the task processing personnel, and P is the resource load balancing factor of the task.
Specifically, the ranking functionThe method comprises the following steps:
,
where N is the number of tasks participating in the ranking,for the weight of the compensation factor +.>In order to adjust the weight of the factor,for ranking of tasks, ++>For a compensation factor based on urgency and skill matching of tasks, for correcting ranking of tasks, ++>Is an adjustment factor based on the distance between the task and the task processing personnel and the resource load balance.
Specifically, the skill matching degree M between the task and the task processing personnel is:
，
wherein ,is the weight of cosine similarity, +.>To complete tasksThe skill value required, T is the skill value of the task processor, < ->Weight of Euclidean distance, +.>Euclidean distance of skill values required for completing a task and skill values of task processing personnel.
Specifically, the resource load balancing factor P of the task is: ratio of task processor to total amount of tasks.
And step 103, distributing the corresponding tasks according to the score according to the task distribution score.
Example 4
The embodiment of the invention also provides electronic equipment, which comprises a processor and a storage medium connected with the processor, wherein the storage medium stores a plurality of instructions, and the instructions can be loaded and executed by the processor so that the processor can execute the emergency task automatic dispatch method.
Specifically, the electronic device of the present embodiment may be a computer terminal, and the computer terminal may include: one or more processors, and a storage medium.
The storage medium may be used to store a software program and a module, for example, in an emergency task automation dispatching method in the embodiment of the present invention, and the processor executes various functional applications and data processing by running the software program and the module stored in the storage medium, that is, implements the emergency task automation dispatching method. The storage medium may include a high-speed random access storage medium, and may also include a non-volatile storage medium, such as one or more magnetic storage systems, flash memory, or other non-volatile solid-state storage medium. In some examples, the storage medium may further include a storage medium remotely located with respect to the processor, and the remote storage medium may be connected to the terminal through a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The processor may invoke the information stored in the storage medium and the application program via the transmission system to perform the following steps: step 101, acquiring task information and task processing personnel information, wherein the task information comprises: the number of tasks, the urgency of each task, and the skill value required to complete the task, the task processor information includes: the number of task processing personnel and the skill value of the task processing personnel;
step 102, setting an emergency task dispatch model, inputting the task information and the task processor information into the emergency task dispatch model, and calculating a task dispatch score of each task, wherein the emergency task dispatch model comprises: sequencing the emergency degrees of the tasks through a sequencing function, and calculating the skill matching degree between the tasks and task processing personnel;
specifically, the emergency task dispatch model is as follows:
，
wherein S is the task dispatch score, D is the task urgency attenuation factor, U is the task urgency,for the ranking function, for ranking the urgency U of the plurality of tasks, +.>The skill matching degree weight is that M is the skill matching degree between the task and the task processing personnel, b is the distance weight, L is the distance between the task and the task processing personnel, and P is the resource load balancing factor of the task.
Specifically, the ranking functionThe method comprises the following steps:
，
where N is the number of tasks participating in the ranking,for the weight of the compensation factor +.>In order to adjust the weight of the factor,for ranking of tasks, ++>For a compensation factor based on urgency and skill matching of tasks, for correcting ranking of tasks, ++>Is an adjustment factor based on the distance between the task and the task processing personnel and the resource load balance.
Specifically, the skill matching degree M between the task and the task processing personnel is:
，
wherein ,is the weight of cosine similarity, +.>For the skill value required for the task, T is the skill value of the task processor, < ->Weight of Euclidean distance, +.>Euclidean distance of skill values required for completing a task and skill values of task processing personnel.
Specifically, the resource load balancing factor P of the task is: ratio of task processor to total amount of tasks.
And step 103, distributing the corresponding tasks according to the score according to the task distribution score.
The foregoing embodiment numbers of the present invention are merely for the purpose of description, and do not represent the advantages or disadvantages of the embodiments.
In the foregoing embodiments of the present invention, the descriptions of the embodiments are emphasized, and for a portion of this disclosure that is not described in detail in this embodiment, reference is made to the related descriptions of other embodiments.
In the embodiments provided in the present invention, it should be understood that the disclosed technology may be implemented in other manners. The system embodiments described above are merely exemplary, and for example, the division of the units is merely a logic function division, and there may be another division manner in actual implementation, for example, multiple units or components may be combined or integrated into another system, or some features may be omitted or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be through some interfaces, units or modules, or may be in electrical or other forms.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of 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.
In addition, each functional unit in the embodiments of the present invention may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.
The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied essentially or partly in the form of a software product or all or part of the technical solution, which is stored in a storage medium, and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a Read-Only Memory (ROM), a random access Memory (RAM, randomAccess Memory), a removable hard disk, a magnetic disk, or an optical disk, or the like, which can store program codes.
It is apparent that the above examples are given by way of illustration only and are not limiting of the embodiments. Other variations or modifications of the above teachings will be apparent to those of ordinary skill in the art. It is not necessary here nor is it exhaustive of all embodiments. While still being apparent from variations or modifications that may be made by those skilled in the art are within the scope of the invention.
Claims (10)
1. An automated emergency task dispatching method is characterized by comprising the following steps:
acquiring task information and task processing personnel information, wherein the task information comprises: the number of tasks, the urgency of each task, and the skill value required to complete the task, the task processor information includes: the number of task processing personnel and the skill value of the task processing personnel;
setting an emergency task dispatch model, inputting the task information and the task processor information into the emergency task dispatch model, and calculating a task dispatch score of each task, wherein the emergency task dispatch model comprises: sequencing the emergency degrees of the tasks through a sequencing function, and calculating the skill matching degree between the tasks and task processing personnel;
and distributing the corresponding tasks according to the score according to the task distribution score.
2. The automated emergency task dispatch method of claim 1, wherein the emergency task dispatch model is:
，
wherein S is the task dispatch score, D is the task urgency attenuation factor, U is the task urgency,for the ranking function, for ranking the urgency U of the plurality of tasks, +.>Weight for skill matching, ++>For the skill matching degree between task and task processing personnel, < ->Is distance weight, ++>For the distance between task and task processor, < ->And (5) balancing factors for the resource load of the task.
3. An automated emergency task dispatch method according to claim 2, wherein the ranking functionThe method comprises the following steps:
，
where N is the number of tasks participating in the ranking,for the weight of the compensation factor +.>To adjust the weight of the factor +.>For ranking of tasks, ++>For a compensation factor based on urgency and skill matching of tasks, for correcting ranking of tasks, ++>Is an adjustment factor based on the distance between the task and the task processing personnel and the resource load balance.
4. An automated task dispatch method according to claim 2, wherein skill matching between tasks and task handling personnel is achievedThe method comprises the following steps:
,
wherein ,is the weight of cosine similarity, +.>Skill value required for completing a task +.>Skill value for task processor +.>Weight of Euclidean distance, +.>Euclidean distance of skill values required for completing a task and skill values of task processing personnel.
5. The automated task dispatch method of claim 2, wherein the resource load balancing factor P of the task is: ratio of task processor to total amount of tasks.
6. An automated emergency task dispatch system, comprising:
the information acquisition module is used for acquiring task information and task processing personnel information, wherein the task information comprises: the number of tasks, the urgency of each task, and the skill value required to complete the task, the task processor information includes: the number of task processing personnel and the skill value of the task processing personnel;
the setting model module is used for setting an emergency task dispatch model, inputting the task information and the task processor information into the emergency task dispatch model, and calculating the task dispatch score of each task, wherein the emergency task dispatch model comprises: sequencing the emergency degrees of the tasks through a sequencing function, and calculating the skill matching degree between the tasks and task processing personnel;
and the dispatch module is used for dispatching the corresponding tasks according to the scores according to the task dispatching scores and the scores.
7. An emergency task automation dispatch system in accordance with claim 6, wherein the emergency task dispatch model is:
，
wherein S is the task dispatch score, D is the task urgency attenuation factor, U is the task urgency,for the ranking function, for ranking the urgency U of the plurality of tasks, +.>The skill matching degree weight is that M is the skill matching degree between the task and the task processing personnel, b is the distance weight, L is the distance between the task and the task processing personnel, and P is the resource load balancing factor of the task.
8. An automated emergency task dispatch system as recited in claim 7, wherein the ranking functionThe method comprises the following steps:
,
where N is the number of tasks participating in the ranking,for the weight of the compensation factor +.>To adjust the weight of the factor +.>For ranking of tasks, ++>For correcting ranking of tasks based on compensation factors of urgency and skill matching of tasks，/>Is an adjustment factor based on the distance between the task and the task processing personnel and the resource load balance.
9. The automated task dispatch system of claim 7, wherein the skill match M between task and task handling personnel is:
,
wherein ,is the weight of cosine similarity, +.>For the skill value required for the task, T is the skill value of the task processor, < ->Weight of Euclidean distance, +.>Euclidean distance of skill values required for completing a task and skill values of task processing personnel.
10. The automated dispatch system of claim 7, wherein the resource load balancing factor P for a task is: ratio of task processor to total amount of tasks.
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| CN115994651A (en) * | 2022-11-18 | 2023-04-21 | 国网河北省电力有限公司营销服务中心 | Work order distribution method, device, terminal and storage medium |
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| US20140180741A1 (en) * | 2012-12-20 | 2014-06-26 | Abb Technology Ag | System and method for automatic allocation of mobile resources to tasks |
| CN109784625A (en) * | 2018-12-10 | 2019-05-21 | 南京南瑞信息通信科技有限公司 | A kind of work order intelligence distributing method based on personnel ability's analysis |
| CN113283749A (en) * | 2021-05-26 | 2021-08-20 | 深圳前海微众银行股份有限公司 | Task distribution method, device, equipment, storage medium and program product |
| CN113537845A (en) * | 2021-09-16 | 2021-10-22 | 深圳市信润富联数字科技有限公司 | Task distribution method and device, electronic equipment and computer readable storage medium |
| CN115994651A (en) * | 2022-11-18 | 2023-04-21 | 国网河北省电力有限公司营销服务中心 | Work order distribution method, device, terminal and storage medium |
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