Task processing method and system applying robot process automation

Abstract

The invention discloses a task processing method and system applying robot process automation, and relates to the technical field of robot process automation, and the method comprises the steps: S1, carrying out the priority evaluation of tasks in a task queue based on a preset rule, S2, sorting the evaluation results to generate a priority task queue, s3, allocating execution resources to the tasks according to the priority task queues; S4, monitoring task execution states and dynamically adjusting the priorities of the task queues; according to the task processing method and system applying robot process automation, task scheduling requirements in complex and changeable business scenes are met, efficient operation of the system in a dynamic environment is ensured, key tasks are ensured to be completed on time, continuity and stability of a business process are improved, business risks are reduced, and the task processing efficiency is improved. The problem that how to regulate and control the priority of the task queue to solve the service influence caused by the fact that key tasks are preempted by low-priority tasks is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of robotic process automation, and in particular to a task processing method and system using robotic process automation. Background Art

[0002] In the existing technology, robotic process automation is widely used in various business processes to automate repetitive tasks, improve efficiency and reduce human errors. However, in task scheduling and execution, especially for multi-task parallel processing scenarios, task priority management still has significant problems.

[0003] Most current RPA systems use static task queues or predefined priority rules to sort and allocate tasks. However, this approach has the following limitations in actual applications: When low-priority tasks occupy system resources, critical tasks may be blocked, resulting in their inability to execute in time, which has a negative impact on the business. For example, in the financial industry, if certain high-priority payment tasks are delayed due to low-priority report generation tasks, it may lead to a decline in customer experience or business losses. In existing RPA systems, priority rules are usually predefined and difficult to dynamically adjust according to real-time business needs. Especially in scenarios with high-frequency business changes, static priority models cannot effectively adapt to dynamic environments, resulting in reduced efficiency in task allocation. When multiple tasks are processed in parallel, RPA robots may cause high-priority tasks to wait for the release of resources for low-priority tasks due to resource competition, further exacerbating the execution delay of critical tasks. Although some systems have introduced weight-based dynamic allocation methods, these methods usually only consider priority adjustment in a single dimension and lack a comprehensive dynamic regulation mechanism. Faced with complex and changing business scenarios, this method cannot fully solve the problem of critical tasks being preempted by low-priority tasks. Summary of the invention

[0004] The purpose of the present invention is to provide a task processing method and system using robotic process automation to solve the problem of how to regulate the priority of task queues to solve the business impact caused by key tasks being preempted by low-priority tasks.

[0005] To achieve the above object, the present invention provides the following technical solution: a task processing method using robotic process automation, the method comprising: S1. Evaluate the priority of tasks in the task queue based on preset rules; S2. Sort the evaluation results to generate a priority task queue, including collecting the priority scores of all tasks, generating an initial queue according to the order in which the tasks are created, calculating the optimization consistency of the sorting, and adjusting the order of the task priority queue. The specific formula is: ; Where τ represents the consistency coefficient between the priority evaluation result of the task and the initial sorting, P(i) represents the priority score of task i, P(j) represents the priority score of task j, i, j represent the index of the task in the queue, Q(i) represents the initial order value of task i in the queue, Q(j) represents the initial order value of task j in the queue, sgn represents the symbolic function, and n represents the total number of tasks in the current task queue; S3, allocating execution resources to tasks according to the priority task queue; S4. Monitor the task execution status and dynamically adjust the priority of the task queue.

[0006] Preferably, the S1 comprises: Set the potential benefits and completion costs of each task, collect the deadline and opportunity cost rate of the task, estimate the volatility caused by task complexity through historical data, and calculate the priority score of the task. The specific formula is: ; Where P(i) represents the priority score of task i, S represents the expected benefit after the task is completed, K represents the resource consumption or cost required to execute the task, r represents the potential loss ratio caused by failure to complete the task per unit time, t represents time, N(d1) and N(d2) represent the calculation results of probability weights in the task priority evaluation process, d1 and d2 represent the intermediate parameters for calculating the task priority score, i represents the index of the task in the queue, and e represents the base of the natural logarithm; Record all tasks according to their priority scores as input for subsequent sorting.

[0007] Preferably, the calculation formula of the intermediate parameter d1 for calculating the task priority score in S1 is: ; Among them, d1 represents the intermediate parameter for calculating the task priority score, S represents the expected benefit after the task is completed, K represents the resource consumption or cost required to execute the task, r represents the potential loss ratio caused by failure to complete the task per unit time, t represents time, and σ represents the volatility caused by task complexity.

[0008] Preferably, the calculation formula of the intermediate parameter d2 for calculating the task priority score in S1 is: ; Among them, d2 represents the intermediate parameter for calculating the task priority score, d1 represents the intermediate parameter for calculating the task priority score, σ represents the volatility caused by task complexity, and t represents time.

[0009] Preferably, S3 includes: Taking the weighted sum of task priority scores as the goal, maximizing benefits, setting the total amount of resources and the resource requirements of tasks, and solving the optimal resource allocation plan, the specific formula is: maximize: , The constraints are: ; Where n represents the total number of tasks, i represents the index of the task in the queue, P(i) represents the priority score of task i, and x i represents the resource allocation status of task i, R(i) represents the amount of resources required to complete task i, and R total Represents the total amount of resources that can be allocated to all tasks.

[0010] Preferably, in S3, when the resource allocation state x of task i i =1, indicating that task i is assigned resources. i When =0, it means that no resources are allocated to task i.

[0011] Preferably, S4 includes: Collect the execution progress and delay error of the task, and describe the law of task priority changing over time. The specific formula is: ; Where P(i) represents the priority score of task i, i represents the index of the task in the queue, e(t) represents the deviation between the expected completion time and the actual completion time during the execution of the task, k1 and k2 represent weight coefficients, and t represents time; The task priority score is dynamically updated according to the above formula, the task priority is recalculated and the task queue order is adjusted.

[0012] Preferably, S2 further includes: When P(i)>P(j), sgn(P(i)-P(j))=1, indicating that the priority of task i is higher than that of task j; When P(i)<P(j), sgn(P(i)-P(j))=-1, indicating that the priority of task i is lower than that of task j; When P(i) = P(j), sgn(P(i) - P(j)) = 0, indicating that the priorities of tasks i and j are equal; Where P(i) represents the priority score of task i, P(j) represents the priority score of task j, and sgn represents the sign function.

[0013] Preferably, S2 further includes: When Q(i)>Q(j), sgn(Q(i)-Q(j))=1, indicating that task i is ranked after task j; When Q(i)<Q(j), sgn(Q(i)-Q(j))=-1, indicating that task i is ranked before task j; When Q(i) = Q(j), sgn(Q(i) - Q(j)) = 0, indicating that the initial order of task i and task j is the same; Among them, Q(i) represents the initial order value of task i in the queue, Q(j) represents the initial order value of task j in the queue, and sgn represents the symbol function.

[0014] A task processing system using robotic process automation is used to implement the steps of the task processing method using robotic process automation, the system comprising: A priority evaluation module is used to evaluate the priority of tasks in the task queue based on preset rules and generate a priority score for the task; A task sorting module connected to the priority evaluation module is used to receive the priority scores of the tasks and sort the evaluation results to generate a priority task queue; A resource allocation module connected to the task sorting module is used to allocate execution resources to tasks according to the generated priority task queue; The task monitoring module connected to the resource allocation module is used to monitor the execution status of the task and collect the task execution progress and delay error information; The dynamic adjustment module connected to the task monitoring module and the task sorting module is used to dynamically adjust the priority of the task according to the delay error information in the task execution status and update the priority task queue.

[0015] It can be seen from the above technical solution that the present invention has the following beneficial effects: The task processing method and system using robot process automation evaluates the priority of tasks in the task queue based on preset rules, sorts the evaluation results to generate a priority task queue, allocates execution resources to tasks according to the priority task queue, monitors the task execution status and dynamically adjusts the priority of the task queue, can dynamically adjust the priority score of the task according to multi-dimensional factors such as task execution status, delay error, resource demand, etc., realizes real-time dynamic optimization of priority, gives priority to meeting the execution requirements of high-priority tasks, can efficiently generate a priority task queue, and realizes orderly execution of tasks. At the same time, the dynamic adjustment module updates the task queue in real time according to the task execution progress and delay error information, ensures that system resources are always efficiently utilized, thereby greatly improving the task processing efficiency, improving the fairness and timeliness of task scheduling, and can adjust the task priority and resource allocation strategy according to the real-time business needs, meet the task scheduling requirements in complex and changeable business scenarios, ensure the efficient operation of the system in a dynamic environment, ensure that key tasks are completed on time, improve the continuity and stability of business processes, reduce business risks, and solve the problem of how to regulate the priority of the task queue to solve the business impact caused by the preemption of key tasks by low-priority tasks. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 It is a schematic diagram of the process of the present invention; Figure 2 It is a schematic diagram of the connection of the system modules of the present invention. DETAILED DESCRIPTION

[0017] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0018] As shown in the figure, the present invention provides a technical solution: a task processing method using robotic process automation, the method comprising: S1. Evaluate the priority of tasks in the task queue based on preset rules; S2. Sort the evaluation results to generate a priority task queue, including collecting the priority scores of all tasks, generating an initial queue according to the order in which the tasks are created, calculating the optimization consistency of the sorting, and adjusting the order of the task priority queue. The specific formula is: ; Where τ represents the consistency coefficient between the priority evaluation result of the task and the initial sorting, P(i) represents the priority score of task i, P(j) represents the priority score of task j, i, j represent the index of the task in the queue, Q(i) represents the initial order value of task i in the queue, Q(j) represents the initial order value of task j in the queue, sgn represents the symbolic function, and n represents the total number of tasks in the current task queue; S3, allocating execution resources to tasks according to the priority task queue; S4. Monitor the task execution status and dynamically adjust the priority of the task queue.

[0019] In the above implementation, the task processing process is optimized based on the needs of robotic process automation: Task priority assessment (S1): The priority score of each task in the task queue is assessed through preset rules (such as task importance, urgency, resource consumption, etc.) to ensure quantitative priority sorting of tasks.

[0020] Sorting and optimization consistency adjustment (S2): Generate an initial priority queue based on the evaluation results. The initial queue is arranged in the order in which the tasks are created. The consistency coefficient τ is used to evaluate the degree of match between the task priority sorting and the initial order. The relative difference between task i and task j in priority score and initial sorting value is calculated by the symbolic function sgn to evaluate the consistency of the overall sorting. Adjust the task priority sorting based on the calculation results so that the priority order of the task queue is more consistent with the optimization goal.

[0021] Dynamic resource allocation (S3): Automatically perform resource allocation operations based on the adjusted priority task queue to ensure that high-priority tasks are given priority resources, thereby improving task execution efficiency.

[0022] Dynamic monitoring and adjustment (S4): Monitor the execution status of tasks in real time and dynamically adjust the priority of the task queue through a feedback mechanism. For example, if a task encounters a delay or resource conflict, the priority of the task can be re-evaluated and the queue adjusted according to the actual situation.

[0023] Compared with the prior art, this embodiment has the following beneficial effects: by calculating the task priority score and combining it with the initial queue order, the task priority queue is optimized and adjusted, and the accuracy and scientificity of task sorting are improved. Based on the optimized task queue, the reasonable allocation of resources is achieved, ensuring that key tasks are given priority, and effectively improving the overall execution efficiency of the system. By real-time monitoring and feedback of the task execution status, the dynamic adjustment of task priority is achieved, and the adaptability and flexibility of the system are enhanced. By calculating and adjusting the consistency coefficient τ, the rationality of task sorting is ensured, the waste of system resources is reduced, and the stability and efficiency of task execution are improved.

[0024] S1 includes setting the potential benefits and completion costs of each task, collecting the deadline and opportunity cost rate of the task, estimating the volatility caused by task complexity through historical data, and calculating the priority score of the task. The specific formula is: ; Where P(i) represents the priority score of task i, S represents the expected benefit after the task is completed, K represents the resource consumption or cost required to execute the task, r represents the potential loss ratio caused by failure to complete the task per unit time, t represents time, N(d1) and N(d2) represent the calculation results of probability weights in the task priority evaluation process, d1 and d2 represent the intermediate parameters for calculating the task priority score, i represents the index of the task in the queue, and e represents the base of the natural logarithm; Record all tasks according to their priority scores as input for subsequent sorting.

[0025] In the above implementation, the task priority evaluation rules are further refined: Analysis of potential benefits and costs of tasks: S represents the expected benefits after the completion of the task, which can be estimated based on historical data and forecasting models to reflect the importance of the task. K represents the resource consumption or cost required to execute the task, such as time, labor, equipment occupancy, etc., to measure the resource input of the task.

[0026] Time factor and loss assessment: r is used to represent the loss rate of unfinished tasks per unit time, and e is used to represent the loss rate of unfinished tasks per unit time. −rt Describes the potential loss attenuation caused by the passage of time. The parameter t represents the deadline or remaining available time of the task, reflecting the urgency of the task.

[0027] Volatility and weight calculation: N(d1) and N(d2) are probability weights estimated based on task complexity and historical data volatility, which are calculated using the standard normal distribution function to adjust the priority score. d1 and d2 are used as intermediate parameters in the calculation, combined with the historical execution of the task and volatility risk, to ensure the accuracy of the priority calculation results.

[0028] Priority score calculation: Comprehensive task benefit S, cost K, time impact t, volatility impact N(d1) and N(d2), through the formula Calculates task priority scores.

[0029] Task sorting input: The calculated priority scores P(i) are recorded and sorted to provide input data for the subsequent task sorting adjustment in step S2, ensuring that the task queue is arranged reasonably according to priority.

[0030] Compared with the prior art, this implementation has the following beneficial effects: By introducing the expected benefits, resource costs, time impact and volatility weights of the task, the priority score of the task is accurately calculated to ensure the scientificity and rationality of the priority evaluation. Combined with the deadline t and the loss rate r, the potential losses caused by the incomplete task are evaluated, effectively improving the timeliness of task processing. The volatility risk of complex tasks is evaluated and the weights are adjusted through the probability weights N(d1) and N(d2) to adapt to the complexity and historical performance of different tasks. The priority score can be dynamically adjusted according to real-time data to ensure that the task sorting is more accurate and flexible. The priority score is used as the input for subsequent sorting to improve the efficiency of task processing and resource utilization.

[0031] The calculation formula of the intermediate parameter d1 for calculating the task priority score in S1 is: ; Among them, d1 represents the intermediate parameter for calculating the task priority score, S represents the expected benefit after the task is completed, K represents the resource consumption or cost required to execute the task, r represents the potential loss ratio caused by failure to complete the task per unit time, t represents time, and σ represents the volatility caused by task complexity.

[0032] In the above implementation, the calculation method of the intermediate parameter d1 in the task priority evaluation process is further refined: Expected benefit S and execution cost K: The logarithmic ratio between the task benefit and cost is calculated by ln(S / K) to measure the economic benefit of the task.

[0033] Time impact t: The time variable t is introduced to reflect the timeliness of the task. The closer the task is to the deadline, the greater its impact.

[0034] Loss rate r: represents the potential loss caused by failure to complete a task within a unit of time, and is corrected based on the volatility σ.

[0035] Volatility σ: The degree of uncertainty caused by task complexity. The higher the volatility, the greater the impact on the task priority score.

[0036] Calculation process: First, calculate the logarithmic benefit-cost ratio of the task, ln(S / K), as the basis for the priority score. Second, consider the time factor and loss rate, through the term (r+σ 2 / 2)t to correct the logarithmic return ratio to ensure the sensitivity of the formula to the timeliness and complexity of the task. Finally, the result is normalized by volatility σ and time t to obtain the intermediate parameter d1 of the task.

[0037] Result output: The calculated d1 will be used as the input parameter of the task priority score formula P(i) to further evaluate the priority of the task.

[0038] Compared with the prior art, this embodiment has the following beneficial effects: by calculating the intermediate parameter d1, the expected benefit, execution cost, time factor and complexity fluctuation rate of the task are comprehensively considered, making the priority score evaluation more scientific and accurate. 2 / 2)t correction term, so that the time urgency of the task is fully reflected, and tasks that are about to expire or have a strong timeliness can be processed first. The volatility σ is introduced to consider the impact of task complexity and execution uncertainty on priority, ensuring that complex tasks are reasonably evaluated and scheduled. By accurately calculating the intermediate parameter d1, accurate input is provided for the task priority score, thereby optimizing the subsequent task queue sorting and resource allocation process.

[0039] The calculation formula of the intermediate parameter d2 for calculating the task priority score in S1 is: ; Among them, d2 represents the intermediate parameter for calculating the task priority score, d1 represents the intermediate parameter for calculating the task priority score, σ represents the volatility caused by task complexity, and t represents time.

[0040] In the above implementation, the evaluation process of the task priority score is further improved by calculating the intermediate parameter d2: The intermediate parameter d1 is the result obtained based on the above calculation, which comprehensively considers the expected return, execution cost, time factor and volatility of the task.

[0041] The volatility σ reflects the degree of uncertainty caused by the complexity of the task. The higher the volatility, the greater the range of variation in task execution. Indicates the time impact of a task, reflecting the dynamic impact of the complexity of a task on its priority in different time periods. The intermediate parameter d1 is modified to ensure that the calculation result more accurately reflects the dynamic priority of the task. The intermediate parameter d2 deducts the volatility effect from d1 to reflect the priority status of the task at the current time. As an important input parameter in the calculation of the final task priority score, d2 helps optimize task sorting and resource allocation.

[0042] By introducing the volatility correction term , the intermediate parameter d1 is dynamically modified to effectively improve the accuracy of task priority evaluation. Combined with the volatility σ, the impact of task complexity on the priority score is quantified to ensure that tasks with high complexity are reasonably evaluated. Dynamic changes are introduced to reflect the priority adjustment of tasks at different time stages, effectively coping with changes in the timeliness and complexity of tasks. The intermediate parameter d2 is used as the input for priority score calculation, which helps to accurately sort the task queue and allocate resources, improving the execution efficiency of the system.

[0043] S3 includes taking the weighted sum of task priority scores as the goal, maximizing benefits, setting the total amount of resources and the resource requirements of tasks, and solving the optimal resource allocation plan. The specific formula is: maximize:

[0044] The constraints are: ; Where n represents the total number of tasks, i represents the index of the task in the queue, P(i) represents the priority score of task i, and x i represents the resource allocation status of task i, R(i) represents the amount of resources required to complete task i, and R total Represents the total amount of resources that can be allocated to all tasks.

[0045] In the above implementation, resource allocation of tasks is achieved through a mathematical optimization model, which specifically includes the following steps: The priority score P(i) of the task is used as the weight and the resource allocation status xi is used as the decision variable to maximize the system benefit through weighted summation. Objective function It means selecting some tasks for resource allocation, with the goal of completing tasks with high priority scores first within limited resources.

[0046] Indicates that the total amount of all allocated resources cannot exceed the total amount of resources R provided by the system total .

[0047] Represents the resource allocation state constraint. If x i =1, indicating that resources are allocated to task i; if x i =0, indicating that task i is not allocated resources. Under the condition of satisfying the total resource constraint, the objective function is solved through dynamic programming to determine the optimal resource allocation plan. Tasks with high priority and reasonable resource consumption will be allocated resources first, thereby maximizing the overall benefit of the system.

[0048] The solution results include the resource allocation status x of each task i , used to guide resource scheduling and task execution.

[0049] Through mathematical optimization models, limited resources are reasonably allocated based on task priority scores and resource requirements to ensure maximum resource utilization. With task priority scores as weights, resources are allocated to high-priority tasks first, effectively improving the overall benefits of the system. The resource allocation plan can be adjusted in real time according to the dynamic changes of task queues and resource conditions to enhance the flexibility and adaptability of the system. The total amount of resources is limited by constraints, which simplifies the calculation complexity and ensures that the solution of the resource allocation plan is efficient and practical.

[0050] In S3, when the resource allocation status x of task i i =1, indicating that task i is assigned resources. i =0, it means that task i has no allocated resources. In the above implementation, the binary decision variable x i Indicates the resource allocation status of the task. The specific principle is as follows: i =1: indicates that the system chooses to allocate resources to task i, and task i enters the execution state. i =0: indicates that the system does not choose to allocate resources for task i, and task i remains waiting or is delayed. and constraints , the system determines the resource allocation status x of each task within the total resource limit i . High-priority tasks (i.e., tasks with a larger P(i)) are allocated resources first, i.e., x i =1 to maximize the system benefit. The resource allocation status of all tasks x i By solving the optimization model, a binary allocation vector X={x1, x2, …, x n}. Where x i = 1 will acquire resources and start execution. i = 0 will wait for resource release or reallocation. i Quantify the task resource allocation status and clearly identify whether a task has been allocated resources, which facilitates system decision-making and management. Based on the task priority score P(i) and resource demand R(i), within the limited resource R total Prioritize resources to key tasks and improve the overall execution efficiency of the system. i ,The system can dynamically adjust the resource allocation of tasks to adapt to different resource requirements and task priority changes.,The binary allocation vector X intuitively displays the task allocation results, making it easier for users to analyze and adjust resource allocation.

[0051] S4 includes the execution progress and delay error of the acquisition task, and describes the law of task priority changing over time. The specific formula is: ; Where P(i) represents the priority score of task i, i represents the index of the task in the queue, e(t) represents the deviation between the expected completion time and the actual completion time during the task execution, k1, k2 represent weight coefficients, and t represents time; The task priority score is dynamically updated according to the above formula, the task priority is recalculated and the task queue order is adjusted.

[0052] In the above implementation, the real-time adjustment of the task priority score is achieved through a dynamic feedback mechanism. The specific principle is as follows: by real-time monitoring of the execution status of the task, the deviation e(t) between the expected completion time and the actual completion time of the collection task is collected. e(t) is a time function that reflects the degree of delay in the task execution process. The greater the delay, the greater the e(t) value. It contains two main influencing factors: Delay error term k1×e(t): It indicates the effect of delay error on the priority of the task. The greater the delay, the more significant the change in priority. Attenuation term k2×P(i): It indicates that the priority of the task gradually decays over time, reflecting the time sensitivity of the task. Calculated by the above formula , and update the current priority score P(i) of the task in real time. According to the updated priority score, reorder the tasks in the task queue to ensure that high-delay tasks or critical tasks are given priority. Implement dynamic adjustment of the task queue to ensure that system resources are allocated to urgent and important tasks first. k1 controls the impact of delay error on the priority score and is dynamically adjusted according to system requirements. k2 controls the decay speed of the priority score to ensure that the task is reduced in priority when it has not been executed for a long time and release system resources. By monitoring the execution progress and delay error of the task in real time, the priority score of the task is dynamically adjusted to ensure the real-time and accuracy of task processing. By introducing the e(t) delay error term, tasks with serious execution delays are discovered and prioritized in a timely manner, thereby improving the overall execution efficiency of the system. According to the dynamically updated priority score, the order of the task queue is readjusted to ensure that system resources are allocated to urgent and important tasks first. Through the decay term k2×P(i), the priority of tasks that have not been executed for a long time is reduced to prevent excessive concentration of resources and optimize system resource scheduling. Through the flexible configuration of the weight coefficient k1 and the decay coefficient k2, it can adapt to different business scenarios and task processing requirements.

[0053] S2 also includes: when P(i)>P(j), sgn(P(i)-P(j))=1, indicating that the priority of task i is higher than that of task j; When P(i)<P(j), sgn(P(i)-P(j))=-1, indicating that the priority of task i is lower than that of task j; When P(i) = P(j), sgn(P(i) - P(j)) = 0, indicating that the priorities of tasks i and j are equal; Where P(i) represents the priority score of task i, P(j) represents the priority score of task j, and sgn represents the sign function.

[0054] In the above implementation, the relative size between the task priority scores P(i) and P(j) is determined by the sign function sgn, and the specific principle is as follows: Definition of the sign function: sgn(P(i) - P(j)) represents the sign of the difference in task priority scores: When P(i) > P(j), the difference is positive, and sgn(P(i) - P(j)) = 1; When P(i) < P(j), the difference is negative, and sgn(P(i) - P(j)) = -1; When P(i) = P(j), the difference is zero, and sgn(P(i) - P(j)) = 0.

[0055] Comparison of task priorities: Based on the result of the sign function, quickly determine the priority relationship between task i and task j: Higher priority: If sgn(P(i) - P(j)) = 1, task i has a higher priority than task j.

[0056] Lower priority: If sgn(P(i) - P(j)) = -1, task i has a lower priority than task j.

[0057] Equal priority: If sgn(P(i) - P(j)) = 0, task i and task j have the same priority, and can be sorted according to the task creation time or other auxiliary rules during sorting.

[0058] Task sorting: Based on the comparison results of the sign function of the priority scores P(i), compare all tasks in the task queue pairwise to determine the sorting order of the tasks. The simple calculation of the sign function can improve the efficiency of task priority comparison and ensure that the system quickly completes the sorting adjustment of the task queue.

[0059] Through the sign function sgn(P(i) - P(j)), quickly determine the relative magnitude of the priority scores of two tasks, simplifying the calculation process of task priority comparison. Using the sign function as the comparison basis, the task queue can be efficiently sorted by priority, especially suitable for scenarios with a large number of tasks. When the task priorities are equal (sgn = 0), auxiliary rules (such as task creation order, resource requirements, etc.) can be introduced for sorting to ensure the fairness and reasonableness of task processing. This method is applicable to various task priority sorting requirements, and the priority comparison criteria can be dynamically adjusted according to the actual application scenario to improve the flexibility and adaptability of the system.

[0060] S2 also includes that when Q(i) > Q(j), sgn(Q(i) - Q(j)) = 1, indicating that task i is ranked after task j; When Q(i) < Q(j), sgn(Q(i) - Q(j)) = -1, indicating that task i is ranked before task j; When Q(i) = Q(j), sgn(Q(i) - Q(j)) = 0, indicating that the initial order of task i and task j is the same; Among them, Q(i) represents the initial order value of task i in the queue, Q(j) represents the initial order value of task j in the queue, and sgn represents the sign function.

[0061] In the above embodiment, the initial order values Q(i) and Q(j) of tasks in the queue are compared through the sign function sgn. The specific principle is as follows: Definition of the initial order value: When each task is created or enters the queue, an initial order value Q(i) will be assigned, representing the initial arrangement order of the task in the queue. The initial order value can be based on the creation time of the task or other system-defined order rules.

[0062] Function of the sign function: sgn(Q(i)−Q(j)) is used to compare the initial order of task i and task j: Q(i)>Q(j): It means that task i is ranked after task j, and the result of the sign function is 1. Q(i)<Q(j): It means that task i is ranked before task j, and the result of the sign function is −1. Q(i)=Q(j): It means that task i and task j have the same initial order, and the result of the sign function is 0.

[0063] Comparison and application of the initial order: During the process of task priority sorting, when the priority scores of tasks are equal, the system will compare according to the initial order value Q(i) to ensure that tasks are arranged in the creation order. Through the result of the sign function, the initial order relationship between tasks can be quickly judged, providing an auxiliary judgment basis for task queue sorting.

[0064] Through the sign function sgn(Q(i)−Q(j)), quickly determine the initial order relationship of tasks in the queue, ensuring the stability and consistency of the system's task sorting. When the task priority scores are equal, use the initial order value as an auxiliary sorting criterion to solve the sorting conflict when the priorities are equal and avoid task processing chaos. The calculation of the sign function is simple and can quickly complete the comparison of the initial order of tasks, which is suitable for scenarios with a large number of tasks and improves the efficiency of task sorting. The comparison rule of the initial order ensures the relative order stability of tasks in the system and optimizes the fairness and consistency of task scheduling.

[0065] A task processing system applying robotic process automation is also provided, which is used to implement the steps of the task processing method applying robotic process automation. The system includes: A priority evaluation module, which is used to evaluate the priorities of tasks in the task queue based on preset rules and generate the priority scores of the tasks; A task sorting module connected to the priority evaluation module, which is used to receive the priority scores of the tasks and sort the evaluation results to generate a priority task queue; A resource allocation module connected to the task sorting module is used to allocate execution resources to tasks according to the generated priority task queue; The task monitoring module connected to the resource allocation module is used to monitor the execution status of the task and collect the task execution progress and delay error information; The dynamic adjustment module connected to the task monitoring module and the task sorting module is used to dynamically adjust the priority of the task according to the delay error information in the task execution status and update the priority task queue.

[0066] In the above implementation, the system realizes automatic processing and dynamic optimization of tasks through the coordinated work of five modules. The specific principles are as follows: The priority evaluation module evaluates the priority of each task in the task queue according to preset rules (such as task importance, resource requirements, deadline, etc.) and generates a priority score P(i). The priority score is an important basis for task sorting and reflects the importance and urgency of the task in the current system.

[0067] The task sorting module receives the task priority scores output by the priority evaluation module, sorts the tasks according to the scores, and generates a priority task queue. The sorting rules judge the task priority relationship and the initial order value based on the symbolic function to ensure that the tasks are arranged in order according to the priority and system rules.

[0068] The resource allocation module allocates execution resources to tasks in turn according to the priority task queue generated by the task sorting module. Resource allocation follows the total resource constraint, maximizes system benefits, and gives priority to meeting the resource requirements of high-priority tasks.

[0069] The task monitoring module monitors the execution status of the task in real time, collects the execution progress and delay error information e(t) of the task, and feeds it back to the dynamic adjustment module. The task monitoring data includes key indicators such as task completion time, execution quality, and resource consumption.

[0070] The dynamic adjustment module receives the delay error information e(t) provided by the task monitoring module, and the priority dynamic update formula described in is: ; The priority score P(i) of the task is dynamically adjusted according to the delay error, and the tasks with serious delays are processed first. The adjusted priority score is passed back to the task sorting module to re-update the sorting of the task queue to ensure the real-time and flexibility of task scheduling.

[0071] Through the collaborative work of five modules, namely priority evaluation, sorting, resource allocation, monitoring and dynamic adjustment, the automation, systematization and modularization of task processing are realized, which is convenient for function expansion and optimization. By real-time monitoring of the execution status of tasks, collecting delay error information, and dynamically adjusting the priority of tasks, it is ensured that high-delay tasks are processed in a timely manner and the efficiency of task execution is improved. Through the resource allocation module, task resources are allocated under the constraint of total resource volume, and the system benefits are maximized based on task priority, which effectively improves resource utilization. Through the interaction between the dynamic adjustment module and the task sorting module, the task queue is updated in real time to ensure the accuracy and timeliness of task scheduling. Through the symbolic function, the priority relationship and initial order value of tasks are quickly judged, the efficiency of task sorting and resource scheduling is improved, and the stable operation of the system in multi-task processing scenarios is ensured.

[0072] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A task processing method using robotic process automation, characterized in that: The method comprises: S1. Evaluate the priority of tasks in the task queue based on preset rules; S2. Sort the evaluation results to generate a priority task queue, including collecting the priority scores of all tasks, generating an initial queue according to the order in which the tasks are created, calculating the optimization consistency of the sorting, and adjusting the order of the task priority queue. The specific formula is: ; Where τ represents the consistency coefficient between the priority evaluation result of the task and the initial sorting, P(i) represents the priority score of task i, P(j) represents the priority score of task j, i, j represent the index of the task in the queue, Q(i) represents the initial order value of task i in the queue, Q(j) represents the initial order value of task j in the queue, sgn represents the symbolic function, and n represents the total number of tasks in the current task queue; S3, allocating execution resources to tasks according to the priority task queue; S4. Monitor the task execution status and dynamically adjust the priority of the task queue.

2. The task processing method using robotic process automation according to claim 1, characterized in that: The S1 includes: Set the potential benefits and completion costs of each task, collect the deadline and opportunity cost rate of the task, estimate the volatility caused by task complexity through historical data, and calculate the priority score of the task. The specific formula is: ; Where P(i) represents the priority score of task i, S represents the expected benefit after the task is completed, K represents the resource consumption or cost required to execute the task, r represents the potential loss ratio caused by failure to complete the task per unit time, t represents time, N(d1) and N(d2) represent the calculation results of probability weights in the task priority evaluation process, d1 and d2 represent the intermediate parameters for calculating the task priority score, i represents the index of the task in the queue, and e represents the base of the natural logarithm; Record all tasks according to their priority scores as input for subsequent sorting.

3. The task processing method using robotic process automation according to claim 2, characterized in that: The calculation formula of the intermediate parameter d1 for calculating the task priority score in S1 is: ; Among them, d1 represents the intermediate parameter for calculating the task priority score, S represents the expected benefit after the task is completed, K represents the resource consumption or cost required to execute the task, r represents the potential loss ratio caused by failure to complete the task per unit time, t represents time, and σ represents the volatility caused by task complexity.

4. The task processing method using robotic process automation according to claim 2, characterized in that: The calculation formula of the intermediate parameter d2 for calculating the task priority score in S1 is: ; Among them, d2 represents the intermediate parameter for calculating the task priority score, d1 represents the intermediate parameter for calculating the task priority score, σ represents the volatility caused by task complexity, and t represents time.

5. The task processing method using robotic process automation according to claim 1, characterized in that: The S3 includes: Taking the weighted sum of task priority scores as the goal, maximizing benefits, setting the total amount of resources and the resource requirements of tasks, and solving the optimal resource allocation plan, the specific formula is: maximize: , The constraints are: ; Where n represents the total number of tasks, i represents the index of the task in the queue, P(i) represents the priority score of task i, and x i represents the resource allocation status of task i, R(i) represents the amount of resources required to complete task i, and R total Represents the total amount of resources that can be allocated to all tasks.

6. The task processing method using robotic process automation according to claim 5, characterized in that: In S3, when the resource allocation state x of task i i =1, indicating that task i is assigned resources. i When =0, it means that task i has no allocated resources.

7. The task processing method using robotic process automation according to claim 1, characterized in that: The S4 includes: Collect the execution progress and delay error of the task, and describe the law of task priority changing over time. The specific formula is: ; Where P(i) represents the priority score of task i, i represents the index of the task in the queue, e(t) represents the deviation between the expected completion time and the actual completion time during the execution of the task, k1 and k2 represent weight coefficients, and t represents time; The task priority score is dynamically updated according to the above formula, the task priority is recalculated and the task queue order is adjusted.

8. The task processing method using robotic process automation according to claim 1, characterized in that: The S2 further includes: When P(i)>P(j), sgn(P(i)-P(j))=1, indicating that the priority of task i is higher than that of task j; When P(i)<P(j), sgn(P(i)-P(j))=-1, indicating that the priority of task i is lower than that of task j; When P(i) = P(j), sgn(P(i) - P(j)) = 0, indicating that the priorities of tasks i and j are equal; Where P(i) represents the priority score of task i, P(j) represents the priority score of task j, and sgn represents the sign function.

9. The task processing method using robotic process automation according to claim 1, characterized in that: The S2 further includes: When Q(i)>Q(j), sgn(Q(i)-Q(j))=1, indicating that task i is ranked after task j; When Q(i)<Q(j), sgn(Q(i)-Q(j))=-1, indicating that task i is ranked before task j; When Q(i) = Q(j), sgn(Q(i) - Q(j)) = 0, indicating that the initial order of task i and task j is the same; Among them, Q(i) represents the initial order value of task i in the queue, Q(j) represents the initial order value of task j in the queue, and sgn represents the symbol function.

10. A task processing system using robotic process automation, used to implement the steps of the task processing method using robotic process automation according to any one of claims 1 to 9, characterized in that: The system comprises: A priority evaluation module is used to evaluate the priority of tasks in the task queue based on preset rules and generate a priority score for the task; A task sorting module connected to the priority evaluation module is used to receive the priority scores of the tasks and sort the evaluation results to generate a priority task queue; A resource allocation module connected to the task sorting module is used to allocate execution resources to tasks according to the generated priority task queue; The task monitoring module connected to the resource allocation module is used to monitor the execution status of the task and collect the task execution progress and delay error information; The dynamic adjustment module connected to the task monitoring module and the task sorting module is used to dynamically adjust the priority of the task according to the delay error information in the task execution status and update the priority task queue.

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