Nuclear power plant task dynamic allocation method and applicable system and readable medium thereof

Abstract

The invention provides a nuclear power plant task dynamic allocation method, an applicable system thereof and a readable medium, and relates to the technical field of nuclear power. The nuclear power plant task dynamic allocation method comprises the following steps: acquiring a load difference function, a to-be-allocated task in a current task period, executors in the current task period and task related data of each executor, the task related data comprises a historical task quality standard-reaching rate, a historical task completion average time length, a maximum number of tasks which can be borne by an individual and a historical task time upper limit; and for each to-be-allocated task, according to the task related data and the number of currently allocated tasks of each executor, calculating to obtain an allocation score satisfying a preset condition, and according to the allocation score satisfying the preset condition, allocating the to-be-allocated task to the corresponding executor, the allocation score is calculated according to a performance coefficient corresponding to each executor and a load difference function, and the performance coefficient is calculated according to the number of currently allocated tasks of each executor and task related data.

Description

Technical Field

[0001] This application relates primarily to the field of nuclear power technology, and in particular to a method for dynamic task allocation in nuclear power plants, as well as the applicable system and readable medium thereof. Background Technology

[0002] Nuclear power plants have a variety of ongoing tasks during operation, such as chemical analysis. Chemical analysis involves the systematic and continuous sampling, monitoring, analysis, and evaluation of the chemical and radiochemical properties of various working media and emissions within the nuclear power plant. Chemical analysis plays an irreplaceable core role in the safe, reliable, economical, and environmentally friendly operation of nuclear power plants, such as ensuring nuclear safety and preventing major accidents, protecting critical equipment, ensuring environmental protection and compliant emissions, and optimizing operational efficiency and economy.

[0003] For tasks requiring continuous execution, many nuclear power plants currently adopt a "preemptive" approach, which involves opening up all specific tasks to all personnel and relying primarily on their initiative or the proactive allocation by the supervisor to complete them. However, this common practice can lead to an unreasonable distribution of workload, affecting the quality of some tasks and ultimately impacting nuclear safety. Summary of the Invention

[0004] The technical problem to be solved by this application is to provide a method for dynamic allocation of tasks in nuclear power plants, as well as an applicable system and readable medium, which can improve the rationality of workload allocation, thereby improving the quality of completion and nuclear safety.

[0005] To address the aforementioned technical problems, this application provides a method for dynamic task allocation in nuclear power plants, comprising the following steps: obtaining a load differential function, tasks to be allocated within the current task cycle, executors within the current task cycle, and task-related data for each executor, including historical task quality compliance rate, historical average task completion time, maximum number of tasks an individual can handle, and historical task time limits; sequentially calculating an allocation score that meets preset conditions for each task to be allocated based on the task-related data and the number of currently allocated tasks for each executor, and allocating the tasks to be allocated to the corresponding executors based on the allocation score that meets the preset conditions, wherein the allocation score is calculated based on the performance coefficient and load differential function corresponding to each executor, and the performance coefficient is calculated based on the number of currently allocated tasks for each executor and the task-related data.

[0006] Optionally, the method also includes calculating the performance coefficient based on the number of currently assigned tasks and task-related data for each executor using the following steps: obtaining the quality coefficient corresponding to the executor based on the historical task quality compliance rate, historical task time limit, and historical task completion average duration; and obtaining the performance coefficient corresponding to the executor based on the quality coefficient, the number of currently assigned tasks, and the maximum number of tasks that an individual can handle.

[0007] Optionally, the executor Corresponding quality coefficient The calculation expression is: In the formula For the executor The corresponding historical task quality compliance rate For the executor The corresponding historical task time limit, As an executor The corresponding average time to complete historical tasks This represents the task complexity weight.

[0008] Optionally, the executor Corresponding performance coefficient The calculation expression is: In the formula For the executor The corresponding quality coefficient, For the executor The corresponding number of currently assigned tasks, For the executor The corresponding maximum number of tasks that an individual can handle. It is a nonlinear load attenuation factor. To adjust the parameters, As an executor The corresponding time variation coefficient, As an executor The corresponding collaboration coefficient.

[0009] Optionally, the time variation coefficient The calculation expression is: In the formula As an executor The corresponding standard deviation of historical task completion time For the executor The average time to complete the corresponding historical tasks.

[0010] Optionally, the calculation expression for the assigned score is: In the formula To assign scores, The total number of executors, and Executors and executor The corresponding performance coefficient, This is the average of the performance coefficients for all executors.

[0011] Optionally, the dynamic task allocation method for nuclear power plants also includes: determining whether the allocation score of all tasks to be allocated to executors is greater than the score threshold; if the determination result is yes, then generating an early warning message.

[0012] Optionally, the step of sequentially calculating an allocation score that meets preset conditions for each task to be assigned based on task-related data and the number of currently assigned tasks for each executor, and then assigning the task to be assigned to the corresponding executor based on the allocation score that meets the preset conditions, further includes: Step a, constructing and initializing a state space, which includes the number of currently assigned tasks and performance coefficients for each executor, as well as the executor corresponding to each task to be assigned; Step b, constructing a state transition equation based on a load difference function; Step c, taking a task to be assigned that does not have a corresponding executor as the current task, and based on the state transition equation and the state space, taking the executor corresponding to the current task that minimizes the allocation score as the matcher; Step d, assigning the current task to a matcher and updating the state space; Step e, repeating steps c to d until all tasks to be assigned are assigned to executors.

[0013] Optionally, For a set containing all executors, For set The executor in the equation, the calculation expression of the state transition equation is: In the formula To make the first One task to be assigned is distributed to the set The state space corresponding to the executor in the middle The corresponding allocation score is calculated based on the load difference function. To make the first One task to be assigned is distributed to the set The state space corresponding to the executor in the middle The corresponding allocation score is calculated based on the load difference function. For the state space Transition to state space The corresponding change in the assigned score.

[0014] To address the aforementioned technical problems, this application provides a dynamic task allocation system for nuclear power plants, comprising: a memory for storing instructions executable by a processor; and a processor for executing the instructions to implement the aforementioned dynamic task allocation method for nuclear power plants.

[0015] To address the aforementioned technical problems, this application provides a computer-readable medium storing computer program code, which, when executed by a processor, implements the aforementioned method for dynamic allocation of nuclear power plant tasks.

[0016] Compared with existing technologies, this application has the following advantages: It calculates the performance coefficient of each executor by incorporating task-related data including historical task quality achievement rate, average historical task completion time, the maximum number of tasks an individual can handle, and the historical task time limit, along with the current number of assigned tasks. Based on this, when allocating each task to be assigned, the current number of assigned tasks for each executor is adjusted to optimize the allocation score calculated based on the performance coefficient and load difference function, thereby allocating all tasks to be assigned to executors. Since the performance coefficient includes the historical task quality achievement rate related to task quality, the average historical task completion time and the historical task time limit related to task completion efficiency, and the maximum number of tasks an individual can handle related to their individual capacity, solving for an allocation score that meets preset conditions can fairly distribute all tasks to executors while helping to improve the subsequent completion quality and efficiency of all tasks to be assigned. Attached Figure Description

[0017] The accompanying drawings are included to provide a further understanding of this application; they are incorporated into and constitute a part of this application. The drawings illustrate embodiments of this application and, together with this specification, serve to explain the principles of this application. In the drawings: Figure 1 This is a flowchart illustrating a method for dynamic task allocation in a nuclear power plant according to an embodiment of this application. Figure 2 yes Figure 1 A flowchart illustrating the calculation of performance coefficients in step S12; Figure 3 yes Figure 1 A flowchart illustrating the sub-steps of step S12; and Figure 4 This is a schematic diagram of a dynamic task allocation system for a nuclear power plant according to an embodiment of this application. Detailed Implementation

[0018] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are merely some examples or embodiments of this application. For those skilled in the art, these drawings can be applied to other similar scenarios without creative effort. Unless obvious from the context or otherwise specified, the same reference numerals in the drawings represent the same structures or operations.

[0019] As indicated in this application and claims, unless the context clearly indicates otherwise, the words "a," "an," "an," and / or "the" are not specifically singular and may include plural forms. Generally speaking, the terms "comprising" and "including" only indicate the inclusion of explicitly identified steps and elements, which do not constitute an exclusive list, and the method or apparatus may also include other steps or elements.

[0020] Unless otherwise specifically stated, the relative arrangement, numerical expressions, and values ​​of the components and steps described in these embodiments do not limit the scope of this application. It should also be understood that, for ease of description, the dimensions of the various parts shown in the drawings are not drawn to actual scale. Techniques, methods, and devices known to those skilled in the art may not be discussed in detail, but where appropriate, such techniques, methods, and devices should be considered part of the specification. In all examples shown and discussed herein, any specific values ​​should be interpreted as merely exemplary and not as limitations. Therefore, other examples of exemplary embodiments may have different values. It should be noted that similar reference numerals and letters in the following drawings denote similar items; therefore, once an item is defined in one drawing, it need not be further discussed in subsequent drawings.

[0021] In the description of this application, it should be understood that the orientation or positional relationship indicated by directional terms such as "front, back, up, down, left, right", "horizontal, vertical, horizontal" and "top, bottom" is usually based on the orientation or positional relationship shown in the accompanying drawings, and is only for the convenience of describing this application and simplifying the description. Unless otherwise stated, these directional terms do not indicate or imply that the device or element referred to must have a specific orientation or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation on the scope of protection of this application; the directional terms "inner" and "outer" refer to the inner and outer contours relative to the outline of each component itself.

[0022] For ease of description, spatial relative terms such as "above," "on top of," "on the upper surface of," "above," etc., are used herein to describe the spatial positional relationship of a device or feature as shown in the figures to other devices or features. It should be understood that spatial relative terms are intended to encompass different orientations in use or operation beyond the orientation of the device as described in the figures. For example, if the device in the figures were inverted, a device described as "above" or "on top of" other devices or structures would subsequently be positioned as "below" or "under" other devices or structures. Thus, the exemplary term "above" can include both "above" and "below." The device may also be positioned in other different ways (rotated 90 degrees or in other orientations), and the spatial relative descriptions used herein will be interpreted accordingly.

[0023] Furthermore, it should be noted that the use of terms such as "first" and "second" to define components is merely for the purpose of distinguishing the corresponding components. Unless otherwise stated, these terms have no special meaning and therefore should not be construed as limiting the scope of protection of this application. In addition, although the terminology used in this application is selected from commonly known and used terms, some terms mentioned in this application's specification may have been chosen by the applicant according to his or her judgment, and their detailed meanings are explained in the relevant sections of this description. Moreover, this application should be understood not only through the actual terms used, but also through the meaning implied by each term.

[0024] It should be understood that when a component is referred to as "on another component," "connected to another component," "coupled to another component," or "in contact with another component," it can be directly on, connected to, coupled to, or in contact with that other component, or there may be an intervening component. In contrast, when a component is referred to as "directly on another component," "directly connected to," "directly coupled to," or "directly in contact with" another component, there is no intervening component. Similarly, when a first component is referred to as "electrically contacting" or "electrically coupled to" a second component, there is an electrical path between the first and second components that allows current to flow. This electrical path may include capacitors, coupled inductors, and / or other components that allow current to flow, even if there is no direct contact between the conductive components.

[0025] Flowcharts are used in this application to illustrate the operations performed by the system according to embodiments of this application. It should be understood that the preceding or following operations are not necessarily performed in exact order. Instead, various steps can be processed in reverse order or simultaneously. Furthermore, other operations may be added to these processes, or one or more steps may be removed from these processes.

[0026] Reference Figure 1 One embodiment of this application proposes a dynamic task allocation method 100 for nuclear power plants (hereinafter referred to as allocation method 100). For example... Figure 1 As shown, the allocation method 100 includes the following steps. Step S11 is to obtain the load difference function, the tasks to be allocated in the current task cycle, the executors in the current task cycle, and the task-related data of each executor. The task-related data includes the historical task quality compliance rate, the average historical task completion time, the maximum number of tasks an individual can handle, and the historical task time limit. In this embodiment, the historical task quality compliance rate, the average historical task completion time, and the historical task time limit are obtained from the historical data related to the executor through a dynamic window. For example, by using a task cycle as the dynamic window, the historical task quality compliance rate, the average historical task completion time, and the historical task time limit can be obtained based on the relevant historical data of the executor in the previous task cycle, thereby more accurately reflecting the executor's work quality, work efficiency, etc., based on data closer to the current time. It should be noted that this application does not limit the size of the dynamic window. In some embodiments, multiple task cycles prior to the current task cycle are used as the dynamic window to obtain data on the executor's work quality, work efficiency, etc., over a longer period, in order to filter out the influence of some special factors on the executor's work quality, work efficiency, etc., over a short period.

[0027] Furthermore, in this embodiment, the historical task quality compliance rate is the first-time approval rate of historical tasks. This means that within the time period corresponding to the dynamic window, the approval rate of each historical task submitted by the executor after the first review, without needing to be returned to the executor for modification, is achieved. It is understandable that the first-time approval rate of historical tasks reflects the quality of the tasks completed by the executor. Correspondingly, in this embodiment, the average completion time of historical tasks is the average completion time of all historical tasks within the time period corresponding to the dynamic window. In this embodiment, the upper limit of historical task time is the longest allowed completion time for all historical tasks within the time period corresponding to the dynamic window.

[0028] Continue to refer to Figure 1 Step S12 involves sequentially calculating an allocation score for each task to be assigned based on task-related data and the number of tasks already assigned to each executor, based on preset conditions. The task to be assigned is then allocated to the corresponding executor according to the allocation score. The allocation score is calculated based on the performance coefficient and load difference function for each executor, and the performance coefficient is calculated based on the number of tasks already assigned to each executor and task-related data. Further reference... Figure 2In this embodiment, the performance coefficient is calculated based on the number of currently assigned tasks and task-related data for each executor using the following steps. Specifically, step S21 involves obtaining the quality coefficient for each executor based on their historical task quality achievement rate, historical task time limit, and historical task completion average duration. Corresponding quality coefficient The calculation expression is: , In the formula For the executor The corresponding historical task quality compliance rate For the executor The corresponding historical task time limit, For the executor The corresponding average time to complete historical tasks This represents the task complexity weight. In this embodiment, the task complexity weight... The value range is from 0.8 to 1.2. Specifically, in this embodiment, the task complexity weight is determined based on the complexity of the historical tasks. In other words, the higher the complexity of the task, the higher its weight. The larger the value, the better. Understandably, by quantitatively analyzing multiple types of historical tasks within a historical time period, the complexity of each historical task can be determined. It should be noted that when the historical task quality compliance rate for an executor is 0, that executor will not participate in the allocation of tasks to be assigned; that is, tasks to be assigned will not be assigned to that executor.

[0029] This embodiment also normalizes the quality coefficients to facilitate subsequent calculations. Specifically, the normalization process includes z-score standardization and data scaling. The expression for z-score standardization in this embodiment is: , In the formula The quality coefficient after z-score standardization. The quality coefficient before z-score standardization. This is the mean of the quality coefficients for all executors. This represents the standard deviation of the quality coefficients for all executors.

[0030] The calculation expression for data scaling in this implementation is: , In the formula The quality coefficient after data scaling. The minimum value among the standardized quality coefficients of the z-score for all executors. This represents the maximum value among the z-score-normalized quality coefficients for all executors. Understandably, the normalized quality coefficients range from 0 to 2, facilitating subsequent processing. It should be noted that this application does not limit the range of data scaling; in some embodiments, by adjusting the calculation expression corresponding to data scaling, the normalized quality coefficients can be set to a range of 0 to 1. Furthermore, this application does not limit the content of the normalization process; in some embodiments, the normalization process only includes z-score standardization, and in others, it only includes data scaling.

[0031] Continue to refer to Figure 2 Step S22 involves calculating the executor's performance coefficient based on their quality coefficient, the number of currently assigned tasks, and the maximum number of tasks they can handle. Specifically, the executor... Corresponding performance coefficient The calculation expression is: , In the formula For the executor The corresponding quality coefficient, For the executor The corresponding number of currently assigned tasks, For the executor The corresponding maximum number of tasks that an individual can handle. It is a nonlinear load attenuation factor. To adjust the parameters, For the executor The corresponding time variation coefficient, For the executor The corresponding collaboration coefficient. In this embodiment, the collaboration coefficient is determined based on whether the executor collaborates with other executors to process tasks in the historical task cycle. It can be understood that the historical task cycle is the previous task cycle before the current task cycle, or multiple task cycles before the current task cycle. In this embodiment, the standard value of the collaboration coefficient is 1, and the range of the collaboration coefficient is 0.95~1.05. For example, when the executor... When collaborating with other executors or making general contributions to the entire team during the historical mission cycle, Greater than 1, when the executor When not collaborating with other executors during the historical mission cycle Less than 1. In this embodiment, the nonlinear load attenuation factor... The value of this factor is greater than 1, thus avoiding assigning too many tasks to the executor and preventing the executor's workload from approaching its limit in the current task cycle. This reduces the risk that excessive fatigue caused by completing previous tasks will affect the quality of subsequent tasks or cause safety hazards in the next task cycle. For example, in this embodiment, the nonlinear load attenuation factor... The baseline value is 1.2. When the current task cycle is a high-risk or high-requirement task cycle, the nonlinear load attenuation factor is... The value is greater than 1.2 and less than or equal to 2, thus discouraging overwork and improving safety or work quality. In this embodiment, the parameter is adjusted. The value ranges from 0 to 1, and is adjusted according to the focus of the current task cycle. For example, if the current task cycle focuses on handling highly complex tasks or improving overall efficiency, then the parameter is adjusted accordingly. The value should be less than 0.5; when the current task cycle prioritizes both efficiency and stability, the parameter should be adjusted. The value is 0.5; if the current task cycle emphasizes stability, consistency, or predictability, then the parameter is adjusted. The value is greater than 0.5.

[0032] Furthermore, the time variation coefficient in this embodiment The calculation expression is: , In the formula For the executor The corresponding standard deviation of historical task completion time For the executor The corresponding average completion time for historical tasks. It should be noted that this application does not limit the method of obtaining the time variation coefficient; in some embodiments, task-related data includes the time variation coefficient.

[0033] The calculation method for the performance coefficient has been briefly explained above. Please refer to the following... Figure 1 and Figure 3The execution of step S12 in this embodiment specifically includes the following sub-steps. Step S121 is to construct and initialize the state space. The state space includes the number of currently assigned tasks and performance coefficients for each executor, as well as the executor corresponding to each task to be assigned. It is understood that in the initialized state space, the number of currently assigned tasks and performance coefficients for each executor are both 0, and each task to be assigned has no corresponding executor. Step S122 is to construct the state transition equation based on the load difference function. In this embodiment, the load difference function is any existing inequality measure function, where the inequality measure function is used to measure the degree of deviation of a distribution from a perfectly uniform or perfectly equal state. It is understood that the inequality measure function includes any one or more of Shannon entropy, generalized Pareto index, etc. In this embodiment, the load difference function includes the Gini coefficient function, that is, the load difference function is constructed with reference to the Gini coefficient function, then the calculation expression for the allocation score is: , In the formula To assign scores, The total number of executors, and Executors and executor The corresponding performance coefficient, This is the average of the performance coefficients for all executors.

[0034] Based on this, the calculation expression of the state transition equation in this embodiment is as follows: , In the formula For a set containing all executors, For set The executor in To make the first One task to be assigned is distributed to the set The state space corresponding to the executor in the middle The corresponding allocation score is calculated based on the load difference function. To make the first One task to be assigned is distributed to the set The state space corresponding to the executor in the middle The corresponding allocation score is calculated based on the load difference function. For the state space Transition to state space The corresponding change in the assigned score.

[0035] Continue to refer to Figure 3Step S123 involves taking a task without a corresponding executor as the current task and, based on the state transition equation and state space, selecting the executor corresponding to the current task that minimizes the allocation score as the matcher. It can be understood that in this embodiment, step S123 calculates the allocation score corresponding to each available executor based on the state transition equation and state space, and then selects the executor corresponding to the smallest allocation score from all allocation scores as the match value. Since the load difference function includes the Gini coefficient function, the smaller the calculated allocation score, the fairer the corresponding allocation scheme. Therefore, in this embodiment, the allocation score that meets the preset conditions is the smallest allocation score. It should be noted that this application does not limit the specific content of the preset conditions. In some embodiments, when the load difference function includes a function of the generalized Pareto exponent, the allocation score that meets the preset conditions in this embodiment is the largest allocation score.

[0036] Continue to refer to Figure 3 Step S124 involves assigning the current task to a matcher and updating the state space. Understandably, after assigning the current task to a matcher in step S124, the number of currently assigned tasks, performance coefficients, and information about the executors for each unassigned task in the state space are updated to facilitate the next execution of step S123. Step S125 involves repeating steps S123 to S124 until all unassigned tasks are assigned to executors. That is, step S125 determines whether each unassigned task corresponds to an executor; if the result is no, step S123 continues. Understandably, in this embodiment, step S12 iteratively calculates the minimum allocation score using the state space and state transition equations, thereby assigning each unassigned task to its corresponding executor. This allows obtaining the information about the executors for each unassigned task from the final state space, thus enabling the assignment of all unassigned tasks to their respective executors.

[0037] For example, in step S12, five chemical analysis tasks are designated as tasks to be assigned within the current task cycle, and five engineers are designated as executors. The five executors are numbered 1 to 5, and their historical task quality achievement rates are 0.7, 0.8, 0.9, 0.9, and 0, respectively. Their historical task completion average times are 1, 1, 1, 2, and 3, respectively, and each executor's maximum number of tasks is 2. Therefore, executor number 5 is removed from the current task assignment set, and a corresponding state space is constructed based on executors 1 to 4. Based on this, the five tasks to be assigned are assigned sequentially. After the first four tasks are assigned, executors 1 to 4 each have one task to be assigned. When calculating the assignment score for the last task to be assigned, it is found that assigning this task to executor number 3 yields the minimum score; therefore, the last task to be assigned is assigned to executor number 3. Finally, the number of tasks to be assigned to the five engineers are 1, 1, 2, 1, and 0, respectively.

[0038] Continue to refer to Figure 1 Step S13 involves determining whether the allocation score of all tasks to be assigned to executors is greater than a scoring threshold. If the determination result is yes, an early warning message is generated. In this embodiment, the scoring threshold is 3.5. That is, when the allocation score of all tasks to be assigned to their corresponding executors is greater than 3.5, an early warning signal corresponding to the allocation scheme is generated to remind the administrator that the final allocation scheme containing all tasks to be assigned is unstable. This allows the administrator to optimize and adjust the final allocation scheme, such as removing some tasks to be assigned or adding executors and then regenerating the final allocation scheme. It should be noted that this application does not limit step S13 to being mandatory. In some embodiments, the allocation method includes steps S11 and S12, but not step S13.

[0039] Understandably, the allocation method 100 in this embodiment calculates the performance coefficient of the corresponding executor using task-related data including historical task quality achievement rate, average historical task completion time, maximum number of tasks an individual can handle, and historical task time limit, along with the current number of assigned tasks. Based on this, when allocating each task to be assigned, the current number of assigned tasks for each executor is adjusted to optimize the allocation score calculated based on the performance coefficient and load difference function, thereby allocating all tasks to be assigned to the executor. Since the performance coefficient includes the historical task quality achievement rate related to task quality, the average historical task completion time and historical task time limit related to task completion efficiency, and the maximum number of tasks an individual can handle related to the executor's personal capacity, solving for an allocation score that meets preset conditions can fairly allocate all tasks to the executor while helping to improve the subsequent completion quality and efficiency of all tasks to be assigned. Furthermore, this embodiment also uses a scoring threshold corresponding to the objective function to further adjust unreasonable final allocation schemes, thereby achieving efficient and high-quality processing of tasks to be assigned.

[0040] An embodiment of this application also proposes a method such as Figure 4 The nuclear power plant task dynamic allocation system 200 shown is referred to as the allocation system 200. According to... Figure 4 The allocation system 200 may include an internal communication bus 21, a processor 22, a read-only memory (ROM) 23, a random access memory (RAM) 24, and a communication port 25. When applied to a personal computer, the allocation system 200 may also include a hard disk 26.

[0041] The internal communication bus 21 enables data communication between components of the in-vehicle voice interaction system 20. The processor 22 can make judgments and issue prompts. In some embodiments, the processor 22 may consist of one or more processors. The communication port 25 enables data communication between the distribution system 200 and external systems. In some embodiments, the distribution system 200 can send and receive information and data from a network via the communication port 25.

[0042] The allocation system 200 may also include different types of program storage units and data storage units, such as hard disk 26, read-only memory (ROM) 23, and random access memory (RAM) 24, capable of storing various data files used for computer processing and / or communication, as well as possible program instructions executed by processor 22. The processor executes these instructions to implement the main part of the method. The results of processor processing are transmitted to the user equipment via a communication port and displayed on the user interface.

[0043] In addition, this application also proposes a computer-readable medium storing computer program code, which implements the above-described dynamic task allocation method for nuclear power plants when executed by a processor.

[0044] The basic concepts have been described above. Obviously, for those skilled in the art, the above disclosure is merely illustrative and does not constitute a limitation of this application. Although not explicitly stated herein, those skilled in the art may make various modifications, improvements, and corrections to this application. Such modifications, improvements, and corrections are suggested in this application, and therefore remain within the spirit and scope of the exemplary embodiments of this application.

[0045] Furthermore, this application uses specific terms to describe embodiments of the application. For example, "an embodiment," "one embodiment," and / or "some embodiments" refer to a particular feature, structure, or characteristic related to at least one embodiment of the application. Therefore, it should be emphasized and noted that "an embodiment," "one embodiment," or "an alternative embodiment" mentioned twice or more in different locations in this specification do not necessarily refer to the same embodiment. In addition, certain features, structures, or characteristics in one or more embodiments of the application can be appropriately combined.

[0046] Similarly, it should be noted that, in order to simplify the description of the present application and thus aid in the understanding of one or more embodiments, the foregoing description of the embodiments of the present application sometimes combines multiple features into a single embodiment, drawing, or description thereof. However, this disclosure method does not imply that the subject matter of the present application requires more features than those mentioned in the claims. In fact, the embodiments contain fewer features than all the features of the single embodiments disclosed above.

[0047] Some aspects of this application can be executed entirely by hardware, entirely by software (including firmware, resident software, microcode, etc.), or by a combination of hardware and software. The aforementioned hardware or software may be referred to as a "data block," "module," "engine," "unit," "component," or "system." The processor may be one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DAPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), processors, controllers, microcontrollers, microprocessors, or combinations thereof. Furthermore, aspects of this application may manifest as computer products residing in one or more computer-readable media, including computer-readable program code. For example, computer-readable media may include, but are not limited to, magnetic storage devices (e.g., hard disks, floppy disks, magnetic tapes, etc.), optical discs (e.g., compressed CDs, digital multifunction DVDs, etc.), smart cards, and flash memory devices (e.g., cards, sticks, key drives, etc.).

[0048] A computer-readable medium may contain a propagated data signal containing computer program code, for example, on baseband or as part of a carrier wave. This propagated signal may take various forms, including electromagnetic, optical, and so on, or suitable combinations thereof. A computer-readable medium can be any computer-readable medium other than a computer-readable storage medium, which can be connected to an instruction execution system, apparatus, or device to enable communication, propagation, or transmission of a program for use. The program code located on the computer-readable medium can be propagated through any suitable medium, including radio, cable, fiber optic cable, radio frequency signals, or similar media, or any combination of the above media.

[0049] Although this application has been described with reference to specific embodiments, those skilled in the art should recognize that the above embodiments are only used to illustrate this application, and various equivalent changes or substitutions can be made without departing from the spirit of this application. Therefore, any changes or modifications to the above embodiments within the essential spirit of this application will fall within the scope of the claims of this application.

Claims

1. A method for dynamic task allocation in a nuclear power plant, characterized in that, Includes the following steps: Obtain the load difference function, the tasks to be assigned in the current task cycle, the executors in the current task cycle, and the task-related data of each executor. The task-related data includes the historical task quality compliance rate, the historical task average completion time, the maximum number of tasks that an individual can handle, and the historical task time limit. For each of the tasks to be assigned, an allocation score that meets preset conditions is calculated based on the task-related data and the number of tasks currently assigned to each executor. The tasks to be assigned are then assigned to the corresponding executors based on the allocation scores that meet the preset conditions. The allocation score is calculated based on the performance coefficient of each executor and the load difference function. The performance coefficient is calculated based on the number of currently assigned tasks and the task-related data of each executor.

2. The nuclear power plant task dynamic allocation method as described in claim 1, characterized in that, The method also includes calculating the performance coefficient based on the number of currently assigned tasks and the task-related data for each executor using the following steps: The quality coefficient corresponding to the executor is obtained based on the historical task quality compliance rate, the historical task time limit, and the historical task completion average duration. The performance coefficient of the executor is obtained based on the quality coefficient corresponding to the executor, the number of currently assigned tasks, and the maximum number of tasks that an individual can handle.

3. The nuclear power plant task dynamic allocation method as described in claim 2, characterized in that, executor Corresponding quality coefficient The calculation expression is: ， In the formula For the executor The corresponding historical task quality compliance rate, For the executor The corresponding historical task time limit, For the executor The corresponding average completion time of the historical tasks, This represents the task complexity weight.

4. The nuclear power plant task dynamic allocation method as described in claim 2, characterized in that, executor Corresponding performance coefficient The calculation expression is: ， In the formula For the executor The corresponding quality coefficient, For the executor The corresponding number of currently assigned tasks, For the executor The corresponding maximum number of tasks that an individual can handle. It is a nonlinear load attenuation factor. To adjust the parameters, For the executor The corresponding time variation coefficient, For the executor The corresponding collaboration coefficient.

5. The nuclear power plant task dynamic allocation method as described in claim 4, characterized in that, The time variation coefficient The calculation expression is: ， In the formula For the executor The corresponding standard deviation of historical task completion time For the executor The corresponding average time to complete the historical tasks.

6. The method for dynamic allocation of nuclear power plant tasks as described in claim 1, characterized in that, The calculation expression for the assigned score is: ， In the formula Assign scores to the given scores. The total number of the executors. and Executors and executor The corresponding performance coefficient, The average of the performance coefficients corresponding to all the executors.

7. The method for dynamic allocation of nuclear power plant tasks as described in claim 1, characterized in that, The dynamic task allocation method for nuclear power plants also includes: Determine whether the allocation score after all the tasks to be assigned to the executor is greater than the score threshold. If the determination result is yes, then generate an early warning message.

8. The method for dynamic allocation of nuclear power plant tasks as described in claim 1, characterized in that, The step of sequentially assigning each of the tasks to be assigned to a corresponding executor to a task that meets preset conditions, based on the task-related data and the number of tasks currently assigned to each executor, further includes: Step a, construct and initialize a state space, which includes the number of currently assigned tasks and the performance coefficient of each executor, as well as the executor corresponding to each task to be assigned; Step b: Construct the state transition equation based on the load difference function; Step c: Take a task to be assigned that does not correspond to the executor as the current task, and according to the state transition equation and the state space, take the executor corresponding to the current task when the assignment score is minimized as the matcher; Step d: Assign the current task to the matcher and update the state space; Step e: Repeat steps c to d until all the tasks to be assigned correspond to the executors.

9. The nuclear power plant task dynamic allocation method as described in claim 8, characterized in that, The calculation expression for the state transition equation is as follows: ， In the formula For a set containing all the aforementioned executors, For set The executor mentioned in the text, To make the first The tasks to be assigned are distributed to the set. The state space corresponding to the executor in the above. The corresponding allocation score is calculated based on the load difference function. To make the first The tasks to be assigned are distributed to the set. The state space corresponding to the executor in the above. The corresponding allocation score is calculated based on the load difference function. For the state space Transition to state space The corresponding change in the assigned score.

10. A dynamic task allocation system for a nuclear power plant, comprising: Memory is used to store instructions that can be executed by the processor; And a processor for executing the instructions to implement the nuclear power plant task dynamic allocation method as described in any one of claims 1-9.

11. A computer-readable medium storing computer program code that, when executed by a processor, implements the dynamic task allocation method for nuclear power plants as described in any one of claims 1-9.

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