Comprehensive guarantee task personnel evaluation and distribution method, storage medium and electronic equipment

Abstract

The invention discloses a comprehensive guarantee task personnel evaluation and distribution method, a storage medium and electronic equipment, and the method comprises the following steps: dividing task large classes according to the demands of a comprehensive guarantee task, further dividing each task large class into a plurality of sub-tasks, carrying out the collection of the execution condition historical accumulation data of each sub-task, and carrying out the calculation of the data; performing normalization preprocessing on the collected data, calculating and obtaining the average historical execution efficiency of a single person in each sub-task according to the processed historical accumulated data, constructing an efficiency evaluation model, inputting the average historical execution efficiency of the single person in each sub-task, and calculating the efficiency of the single person in each sub-task; and calculating the optimal personnel allocation and outputting the local optimal solution of the personnel allocation through a tabu search algorithm according to the sub-tasks, the corresponding duration of each sub-task and the demand quantity of each sub-task. According to the method, a multi-factor parameter evaluation system is constructed aiming at the characteristics of the comprehensive guarantee task, so that the evaluation result is more objective and accurate.

Description

Technical Field

[0001] The present invention relates to the technical field of resource assessment and allocation, and in particular to a method for assessing and allocating personnel for a comprehensive support task, a storage medium, and an electronic device. Background Art

[0002] Comprehensive support provides comprehensive support for both routine mission exercises and emergency mission execution. Modern comprehensive support encompasses logistical resources such as fuel, equipment, supplies, and ammunition; medical resources such as temporary hospitals, treatment of the wounded and sick, and evacuation of the critically injured; and transportation resources such as water, road, rail, and air transport. Existing comprehensive support task management systems typically record task completion status and time spent through form submissions or rule-based triggering, and then evaluate task execution effectiveness based on single metrics such as task completion rate and time efficiency.

[0003] During the execution of comprehensive support missions, scientific personnel assessment and allocation results can intuitively guide the rapid and impromptu adjustments of support materials and personnel during the mission. They can also be used to review and evaluate the effectiveness of the entire mission after the mission is completed. This is a crucial step in ensuring efficient resource integration and improving the skills and combat effectiveness of mission personnel. Therefore, during the execution of comprehensive support missions, the assessment and allocation of personnel for each task is key to improving the efficiency and effectiveness of mission execution. However, existing assessment and allocation methods often focus on a single task and lack consideration of multi-dimensional objectives, high complexity, and the involvement of multiple resource elements, resulting in insufficient accuracy in personnel assessment and allocation results.

[0004] Therefore, there is an urgent need for a comprehensive support task personnel assessment and allocation method, storage medium and electronic equipment to solve the problem of insufficient accuracy of personnel assessment and allocation results for various tasks in the comprehensive support task. Summary of the Invention

[0005] In view of the deficiencies in the prior art, the present invention provides a comprehensive support task personnel assessment and allocation method, a storage medium and an electronic device to solve the problem of insufficient accuracy of personnel assessment and allocation results for various tasks in the comprehensive support task.

[0006] To achieve the above object, the present invention adopts the following technical solutions:

[0007] A method for evaluating and allocating personnel for comprehensive support tasks, characterized by comprising the following steps:

[0008] According to the needs of the comprehensive support tasks, the tasks are divided into major categories, and each major task category is further divided into several subtasks. Then, the historical accumulated data of the execution of each subtask is collected, the collected data is normalized and preprocessed, and the processed historical accumulated data is used to calculate the average historical execution efficiency of a single person in each subtask. A performance evaluation model is constructed, and the historical execution efficiency of the average single person in each subtask, as well as the corresponding duration of each subtask and the demand for each subtask are input. The optimal personnel allocation is calculated through the taboo search algorithm, and the local optimal solution for personnel allocation is output.

[0009] To optimize the above technical solutions, specific measures taken also include:

[0010] Furthermore, the step of calculating the optimal personnel allocation by the tabu search algorithm further includes the following steps:

[0011] Set personnel allocation constraints and calculation termination rules. The algorithm execution can be terminated early when any of the following conditions are met:

[0012] The first is the number of iterations. When the number of iterations reaches 1000, the algorithm execution is automatically terminated, and the set of executor allocations with the largest evaluation function value is selected from the past 1000 values ​​as the optimal solution for the project. If there are multiple sets of the same maximum evaluation function value, the combination with the smallest sum of the personnel allocation values ​​is selected as the local optimal solution for the project.

[0013] The second is based on the evaluation value principle. When the evaluation value of the evaluation function is greater than the preset value in any algorithm case, the algorithm terminates.

[0014] Furthermore, the performance evaluation model is represented by the following function:

[0015]

[0016] Among them, n is the number of task categories divided according to the comprehensive support task requirements, M n is the weight coefficient corresponding to each task category, A is the number of subtasks in the first task category, a is the label of the subtask in the first task category, B is the number of subtasks in the second task category, b is the label of the subtask in the second task category, C is the number of subtasks in the nth task category, c is the label of the subtask in the nth task category, are the corresponding average historical execution efficiency of a single person, as input constants, are the corresponding subtask durations, as input constants, are the corresponding subtask requirements, as input constants, H a 、W b 、Y c are the corresponding number of subtask executors.

[0017] Furthermore, the personnel allocation constraints include:

[0018] H1+H2+...+H a ≤H

[0019] H1,H2,...,H a ∈[0,H]

[0020] W1+W2+...+W b ≤W

[0021] W1,W2,...,W b ∈[0,W]

[0022] Y1+Y2+...+Y c ≤Y

[0023] Y1,Y2,...,Y c ∈[0,Y]

[0024] Among them, H is the total number of logistics personnel available for deployment to the first major task category, which is an input constant; W is the total number of logistics personnel available for deployment to the second major task category, which is an input constant; Y is the total number of logistics personnel available for deployment to the nth major task category, which is an input constant.

[0025] Furthermore, the personnel allocation constraints also include:

[0026]

[0027]

[0028] Furthermore, the algorithm execution includes the following steps:

[0029] Step 1: Set the initial personnel allocation solution [H1,H2,...,H a ,W1,W2,...,W b Y1,Y2,...,Y c ]=[1,1,..,1], set the initial value of the taboo table set to empty, calculate the X function value based on the initial personnel allocation solution, if the termination rule is met, the algorithm terminates and outputs the result; if the termination rule is not met, set the current solution set as the initial solution set, add the initial solution set to the taboo table set, and execute the next step;

[0030] Step 2: Use the traversal method to generate a new solution set for the domain of the initial solution set. If the generated new solution set is in the taboo table, regenerate the new solution set and recalculate the evaluation function value. If the termination rule is met, the algorithm terminates and outputs the result. If the termination rule is not met, compare the evaluation function value calculated for the new solution of this round with the evaluation function value calculated for the current solution set. If the evaluation function value of this round is greater than the evaluation function value of the previous round, update the current solution set to the new solution set of this round. If the evaluation function value of this round is less than or equal to the evaluation function value of the previous round, add the new solution set of this round to the taboo table set.

[0031] Step 3: Repeat step 2 until the termination rule is met.

[0032] Furthermore, the method further includes the following steps: visualizing the output local optimal solution for personnel allocation and displaying the evaluation results in the form of charts or dashboards.

[0033] Furthermore, the major task categories include logistics resource support tasks, medical resource support tasks and transportation resource support tasks.

[0034] Furthermore, a computer-readable storage medium stores a computer program, characterized in that the computer program enables a computer to execute the above-mentioned comprehensive support task personnel assessment and allocation method.

[0035] Furthermore, an electronic device is characterized in that it includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, it implements a comprehensive support task personnel assessment and allocation method as described above.

[0036] The beneficial effects of the present invention are:

[0037] The present invention constructs a multi-factor parameter evaluation system based on the characteristics of comprehensive support tasks, and combines big data analysis technology to mine valuable information from massive historical data, making the evaluation results more objective and accurate. The constructed evaluation model can be customized and adjusted according to the needs of exercises and training, and can adapt to the comprehensive support task effectiveness evaluation in different scenarios and needs. Through an intuitive user interface and rich visualization tools, the user usage threshold is lowered, and the readability and practicality of the evaluation results are improved. The present invention can achieve a comprehensive and objective evaluation of the effectiveness of comprehensive support tasks through scientific data collection, analysis and evaluation model construction, providing strong support for improving the scientificity and effectiveness of comprehensive support work.

[0038] The present invention can calculate the support efficiency of a single task for different types of tasks, such as logistics resource support, medical resource support, transportation resource support, etc. It is guided by the task execution efficiency, such as the number of on-time completions as the numerator and the number of support requirements as the denominator. After arithmetic average calculation, the first-order quantitative evaluation results of each task are obtained; and then a weighted arithmetic average calculation is performed with the templated second-order weight coefficient to quickly obtain the efficiency evaluation results of complex comprehensive support tasks.

[0039] This invention addresses the problem that existing single-dimensional performance evaluation methods are unsuitable for comprehensive support missions, and the resulting lack of accuracy in comprehensive support mission performance evaluation. This invention can meet the needs of comprehensive support missions with multi-dimensional objectives, high complexity, and involving a large number of resource elements for accurate, comprehensive, and quantitative performance evaluation. This can provide feedback to guide the development of comprehensive support mission training, optimize the allocation of personnel for training and exercise missions, meet the speed, accuracy, and efficiency requirements of comprehensive support missions, and achieve the goals of timely adjustment, intelligent processes, and precise support for comprehensive support missions.

[0040] The present invention is applicable to comprehensive support tasks, and can intuitively guide the on-the-spot rapid adjustment of support materials and support personnel during the execution of the task. At the same time, it can be used to review and evaluate the training effect of the entire task after the comprehensive support task is completed. It can optimize the arrangement of comprehensive support task training subjects, focus on the key points of comprehensive support task training, provide refined management, and improve the level of resource operation and governance. It can provide strong support for the practical development of logistics activities and encourage resources to focus on and operate for war.

[0041] The performance evaluation model based on the comprehensive indicator system of the present invention can play a vital role in the pre-task organization, in-task adjustment and post-task review stages. In the pre-task organization stage, the first-order quantitative evaluation results and second-order weight coefficient configuration of the performance evaluation model can be used to optimize the resources of subtasks / sub-activities in a targeted manner, including redundant configuration of personnel resources and pre-planning and primary-backup configuration of physical resources, in order to achieve better task execution results. In the in-task adjustment stage, the performance evaluation model based on basic data collection and mathematical formula can be used to quickly calculate the quantitative guarantee effectiveness and guide the task organizer to make rapid adjustments to the guarantee resources. In the post-task review stage, the arrangement of subsequent training subjects can be focused on subtasks with low personnel efficiency to improve the overall capabilities of the team. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 This is a flow chart of a comprehensive support task personnel assessment and allocation method proposed by the present invention;

[0043] Figure 2 This is a schematic diagram of the division of a comprehensive support task personnel assessment and allocation method proposed in the present invention. DETAILED DESCRIPTION

[0044] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0045] As attached Figure 1 As shown, a comprehensive support task personnel assessment and allocation method according to an embodiment of the present invention includes the following steps:

[0046] According to the needs of the comprehensive support tasks, the tasks are divided into major categories, and each major task category is further divided into several subtasks. Then, the historical accumulated data of the execution of each subtask is collected, and the collected data is pre-processed with normalization such as outliers and units. The processed historical accumulated data is used to calculate the average historical execution efficiency of a single person in each subtask, and a performance evaluation model is constructed. The historical execution efficiency of the average single person in each subtask, as well as the corresponding duration of each subtask and the demand for each subtask are input. The optimal personnel allocation is calculated through the taboo search algorithm, and the local optimal solution for personnel allocation is output.

[0047] The above-mentioned calculation of the optimal personnel allocation by the tabu search algorithm also includes the following steps:

[0048] Set personnel allocation constraints and calculation termination rules. The algorithm execution can be terminated early when any of the following conditions are met:

[0049] The first is the number of iterations. When the number of iterations reaches 1000, the algorithm execution is automatically terminated, and the set of executor allocations with the largest evaluation function value is selected from the past 1000 values ​​as the optimal solution for the project. If there are multiple sets of the same maximum evaluation function value, the combination with the smallest sum of the personnel allocation values ​​is selected as the local optimal solution for the project.

[0050] The second is based on the evaluation value principle. When the evaluation value of the evaluation function is greater than the preset value 0.99 in any algorithm case, the algorithm terminates.

[0051] The above performance evaluation model is represented by the following function:

[0052]

[0053] In the function representation, n is the number of task categories divided according to the comprehensive support task requirements, M nis the weight coefficient corresponding to each task category, A is the number of subtasks in the first task category, a is the label of the subtask in the first task category, B is the number of subtasks in the second task category, b is the label of the subtask in the second task category, C is the number of subtasks in the nth task category, c is the label of the subtask in the nth task category, are the corresponding average historical execution efficiency of a single person, as input constants, are the corresponding subtask durations, which can be determined according to the training task time requirements and used as input constants. They are the corresponding subtask requirements, which can be determined according to the scale of the training task. As the input constant, H a 、W b 、Y c are the corresponding number of subtask executors.

[0054] The above-mentioned personnel allocation constraints include:

[0055] H1+H2+...+H a ≤H

[0056] H1,H2,...,H a ∈[0,H]

[0057] W1+W2+...+W b ≤W

[0058] W1,W2,...,W b ∈[0,W]

[0059] Y1+Y2+...+Y c ≤Y

[0060] Y1,Y2,...,Y c ∈[0,Y]

[0061] In the above, H is the total number of logistics personnel available for deployment to the first major task category, which is an input constant, W is the total number of logistics personnel available for deployment to the second major task category, which is an input constant, and Y is the total number of logistics personnel available for deployment to the nth major task category, which is an input constant.

[0062] The above-mentioned personnel allocation constraints also include:

[0063]

[0064] The execution of the above algorithm specifically includes the following steps:

[0065] Step 1: Set the initial personnel allocation solution [H1,H2,...,H a ,W1,W2,...,W bY1,Y2,...,Y c ]=[1,1,..,1], set the initial value of the taboo table set to empty, calculate the X function value based on the initial personnel allocation solution, if the termination rule is met, the algorithm terminates and outputs the result; if the termination rule is not met, set the current solution set as the initial solution set, add the initial solution set to the taboo table set, and execute the next step;

[0066] Step 2: Use the traversal method to generate a new solution set for the domain of the initial solution set. If the generated new solution set is in the taboo table, regenerate the new solution set and recalculate the evaluation function value. If the termination rule is met, the algorithm terminates and outputs the result. If the termination rule is not met, compare the evaluation function value calculated for the new solution of this round with the evaluation function value calculated for the current solution set. If the evaluation function value of this round is greater than the evaluation function value of the previous round, update the current solution set to the new solution set of this round. If the evaluation function value of this round is less than or equal to the evaluation function value of the previous round, add the new solution set of this round to the taboo table set.

[0067] Step 3: Repeat step 2 until the termination rule is met.

[0068] In a further embodiment of this solution, the following step is further included: visualizing the output local optimal solution for personnel allocation and presenting the evaluation results in the form of charts or dashboards. This provides multi-dimensional data analysis and comparison capabilities to help users deeply understand the evaluation results.

[0069] A specific implementation of the method of the present invention is as follows:

[0070] According to the needs of comprehensive support tasks, they are divided into three categories, including logistics resource support tasks, medical resource support tasks and transportation resource support tasks. The skill attributes of each major category of executors should cover the requirements of the diverse sub-tasks under this major category, so that relatively flexible deployment of executors for the same type of tasks can be achieved. For example, after on-the-job screening, on-the-job training and actual combat training, executors of logistics resource support tasks can perform a variety of logistics resource support sub-tasks such as fuel, clothing, food, and ammunition support. It is agreed that within the mission cycle, a single executor can only undertake one logistics resource support sub-task, while a logistics resource support sub-task can be undertaken by multiple executors. The same agreement applies to executors of other types of support tasks.

[0071] As attached Figure 2As shown in the figure, each major task category is further divided into several subtasks, namely, the logistics resource support task is divided into the fuel support subtask personnel efficiency, the clothing support subtask personnel efficiency, the food support subtask personnel efficiency and the ammunition support subtask personnel efficiency; the medical resource support task is divided into the temporary hospital opening subtask personnel efficiency, the wounded and sick treatment subtask personnel efficiency and the seriously injured personnel evacuation subtask personnel efficiency; the transportation resource support task is divided into the water transportation subtask personnel efficiency, the road transportation subtask personnel efficiency, the railway transportation subtask personnel efficiency and the air transportation subtask personnel efficiency.

[0072] Afterward, historical training and exercise mission data was collected to calculate the personnel efficiency of each subtask type. The first type of historical data collected for logistics resource support missions specifically includes the weight of fuel, bedding, and food arriving on time, the amount of ammunition arriving on time; the scheduled execution time for fuel, bedding, food, and ammunition missions; and the actual number of personnel performing these missions. The second type of historical data collected for medical resource support missions specifically includes the number of temporary hospitals opened on time, the number of patients treated on time, and the number of patients evacuated on time. The scheduled execution time for temporary hospital opening, patient treatment, and patient evacuation was also calculated; the actual number of personnel performing these missions. The third type of historical data collected for transportation resource support missions specifically includes the weight of water transport arriving on time, road transport arriving on time, rail transport arriving on time, and air transport arriving on time; the scheduled execution time for water transport, road transport, rail transport, and air transport missions; and the actual number of personnel performing these missions. See Table 1 for details.

[0073] Table 1 Personnel efficiency calculation table

[0074]

[0075]

[0076] Let the total number of logistics personnel available for training and exercise deployment be the input constant H. ① The number of personnel to be assigned to the fuel support subtask is the variable to be optimized H1, and let the historical average operating efficiency of the personnel performing the fuel support subtask be the input constant Assume that the specified duration of the fuel supply subtask is an input constant Assume that the fuel supply subtask requires fuel as an input constant ② The number of personnel to be assigned to the equipment support subtask is the variable to be optimized H2, and the historical average operating efficiency of the personnel performing the equipment support subtask is set as the input constant Assume that the specified duration of the equipment support subtask is the input constant Assume that the fuel required by the equipment support subtask is the input constant ③ The number of personnel to be assigned to the food security subtask is the variable to be optimized H3, and the historical average operating efficiency of the personnel who perform the food security subtask is set as the input constant Assume that the duration of the food security subtask is the input constant Assume that the oil required by the food security subtask is the input constant ④ The number of personnel to be assigned to the ammunition support subtask is the variable to be optimized H4, and the historical average operating efficiency of the personnel performing the ammunition support subtask is set as the input constant Assume that the specified duration of the ammunition support subtask is an input constant Assume that the fuel required by the ammunition support subtask is the input constant

[0077] Assume that the total number of medical personnel available for deployment in the training task is the input constant W. ① The number of personnel to be assigned to the temporary hospital opening subtask is the variable to be optimized W1, and the historical average operating efficiency of the personnel performing the temporary hospital opening subtask is the input constant Assume that the duration of the temporary hospital opening subtask is an input constant Assume that the fuel required for the temporary hospital opening subtask is an input constant ② The number of personnel to be assigned to the subtask of treating the wounded and sick is the variable to be solved W2, and the historical average operating efficiency of the personnel performing the subtask of treating the wounded and sick is the input constant Assume that the duration of the wounded and sick treatment subtask is the input constant Assume that the fuel required for the wounded and sick treatment subtask is an input constant ③ The number of personnel to be assigned to the subtask of evacuating seriously injured personnel is the variable to be solved W3, and the historical average operating efficiency of the personnel performing the subtask of evacuating seriously injured personnel is set as the input constant Assume that the duration of the seriously injured personnel evacuation task is an input constant. Assume that the fuel required for the evacuation of seriously injured personnel is an input constant.

[0078] Let the total number of transport personnel available for training and exercise deployment be the input constant Y. ① The number of personnel to be assigned to the water transport subtask is the variable to be optimized Y1, and let the historical average operating efficiency of the personnel performing the water transport subtask be the input constant Assume that the duration of the water transport subtask is the input constant Assume that the fuel required by the water transport subtask is an input constant ② The number of personnel to be assigned to the road transport subtask is the variable to be optimized Y2, and the historical average operating efficiency of the personnel who perform the road transport subtask is set as the input constant Assume that the specified duration of the road transport subtask is the input constant Assume that the fuel required by the road transport subtask is the input constant ③ The number of personnel to be assigned to the railway transport subtask is the variable to be optimized Y3, and the historical average operating efficiency of the personnel who perform the railway transport subtask is set as the input constant Assume that the specified duration of the railway transport subtask is the input constant Assume that the fuel demand of the railway transportation subtask is the input constant ④ The number of personnel to be assigned to the air transport subtask is the variable to be optimized Y4, and the historical average operating efficiency of the personnel performing the air transport subtask is set as the input constant Assume that the duration of the air transport subtask is the input constant Assume that the fuel required by the aviation transport subtask is an input constant

[0079] Construct the performance evaluation objective function:

[0080]

[0081] Among them, M1 is the weight coefficient of the logistics resource support task, M2 is the weight coefficient of the medical resource support task, and M3 is the weight coefficient of the transportation resource support task. About M n The specific value of can be determined by the organizer of the training mission before the training begins. The recommended values ​​are as follows:

[0082] For the logistics resource support task, [M1, M2, M3] = [0.6, 0.2, 0.2] can be initially set as the input constant.

[0083] For the medical resource support task, [M1, M2, M3] = [0.2, 0.6, 0.2] can be initially set as input constants.

[0084] For the transportation resource guarantee task, [M1, M2, M3] = [0.2, 0.2, 0.6] can be initially set as input constants.

[0085] Specifically, weight coefficients are set for logistics resource support tasks, medical resource support tasks, and transportation resource support tasks.

[0086] When the focus of the comprehensive support mission training is the logistics resource support mission, the second-order weight coefficient of the logistics resource support mission (M1) can be set to 0.6, the second-order weight coefficient of the medical resource support mission (M2) can be set to 0.2, and the second-order weight coefficient of the transportation resource support mission (M3) can be set to 0.2.

[0087] When the focus of the comprehensive support mission training is the medical resource support mission, the second-order weight coefficient of the logistics resource support mission (M1) can be set to 0.2, the second-order weight coefficient of the medical resource support mission (M2) can be set to 0.6, and the second-order weight coefficient of the transportation resource support mission (M3) can be set to 0.2.

[0088] When the focus of the comprehensive support mission training is the transportation resource support mission, the second-order weight coefficient of the logistics resource support mission (M1) can be set to 0.2, the second-order weight coefficient of the medical resource support mission (M2) can be set to 0.2, and the second-order weight coefficient of the transportation resource support mission (M3) can be set to 0.6.

[0089] Accordingly, users can adjust the distribution of each second-order weight coefficient according to the training task requirements, but they need to meet requirements.

[0090] About Executive Efficiency The specific calculation formula is shown in Table 1, which can be completed in the initialization phase and used as an input constant. It can be determined based on the time requirement of the training mission and used as an input constant. It can be determined based on the scale of the training mission and used as an input constant. Regarding personnel, there are the following constraints:

[0091] H1+H2+H3+H4≤H·······(1)

[0092] H1,H2,H3,H4∈[0,H]·······(2)

[0093] W1+W2+W3≤W·······(3)

[0094] W1,W2,W3∈[0,W]·······(4)

[0095] Y1+Y2+Y3+Y4≤Y·······(5)

[0096] Y1,Y2,Y3,Y4∈[0,Y]·······(6)

[0097] Considering the growth of H, It will be close to 1, and even the calculated value will exceed 1. However, in reality, the number of original materials used for this subtask is usually limited, and during the actual execution of the subtask, when the number of on-time matching requirements reaches the preset number, the delivery of the guaranteed materials will no longer be carried out. Therefore, the following constraints are also set:

[0098]

[0099] Calculate the effectiveness evaluation model for the constraints 1-9 above and find a relatively optimized subtask personnel allocation set within the acceptable time range of the project. Specifically:

[0100] Step 1: Set the initial personnel allocation solution [H1, H2, H3, H4, W1, W2, W3, Y1, Y2, Y3, Y4] = [1, 1, 1, 1, 1, 1, 1, 1, 1] and set the initial value of the taboo table set to empty. Calculate the evaluation function value based on the initial personnel allocation solution. If the termination rule is met, the algorithm terminates and outputs the result. If the termination rule is not met, set the current solution set as the initial solution set, add the initial solution set to the taboo table set, and proceed to the next step.

[0101] Step 2: Use the traversal method to generate a new solution set for the domain of the initial solution set. If the generated new solution set is in the taboo table, a new solution set is generated and the evaluation function value is recalculated. If the termination rule is met, the algorithm terminates and the result is output; if the termination rule is not met, the evaluation function value calculated for the new solution in this round is compared with the evaluation function value calculated for the current solution set. If the evaluation function value of this round is greater than the evaluation function value of the previous round, the current solution set is updated to the new solution set of this round; if the evaluation function value of this round is less than or equal to the evaluation function value of the previous round, the new solution set of this round is added to the taboo table set.

[0102] Step 3: Repeat Step 2 until the termination rule is met.

[0103] Finally, the output local optimal solution for personnel allocation is visualized and the evaluation results are presented in the form of charts or dashboards.

[0104] In view of the characteristics of comprehensive support tasks, the present invention constructs a multi-factor parameter evaluation system, and combines big data analysis technology to mine valuable information from massive historical data, making the evaluation results more objective and accurate. The constructed evaluation model can be customized and adjusted according to the needs of exercises and training, and can adapt to the comprehensive support task effectiveness evaluation of different scenarios and needs. Through an intuitive user interface and rich visualization tools, the user usage threshold is lowered, and the readability and practicality of the evaluation results are improved. The present invention can achieve a comprehensive and objective evaluation of the effectiveness of comprehensive support tasks through scientific data collection, analysis and evaluation model construction, providing strong support for improving the scientificity and effectiveness of comprehensive support work.

[0105] The method of the present invention can be used to calculate the support effectiveness of a single task for different types of tasks, such as logistics resource support, medical resource support, and transportation resource support. It is guided by the efficiency of task execution, such as taking the number of on-time completions as the numerator and the number of support requirements as the denominator. After arithmetic average calculation, the first-order quantitative evaluation results of each task are obtained; and then a weighted arithmetic average calculation is performed with the templated second-order weight coefficient to quickly obtain the effectiveness evaluation results of complex comprehensive support tasks. With the accumulation of task support data and the increase in training organizers with rich practical experience, the allocation of training execution personnel can iteratively develop in the direction of integrating historical data and expert experience, rather than simply initializing personnel allocation based on reference experience. Specifically, by integrating massive historical data, establishing an evaluation model to correct the optimal value of experience, and adding manual corrections by training experts, an effectiveness evaluation model for different key training tasks can be constructed, and scientific and reasonable personnel allocation can be explored and studied in order to achieve better training goals.

[0106] The system architecture design of the method of the present invention mainly includes a data acquisition layer, a data analysis layer, an evaluation model layer and a user interaction layer.

[0107] Data collection layer: responsible for collecting and summarizing data on the completion of comprehensive support tasks. Data calculation layer: perform normalization preprocessing and preliminary calculations on the collected data such as outliers and units, and calculate the historical average operating efficiency of personnel in the form of historical statistical data. The specific calculation method is shown in the appendix of Chapter 8, which provides historical experience data support for the subsequent optimization of personnel allocation and improvement of performance evaluation results. Evaluation model layer: This layer quantifies the performance evaluation model, sets the evaluation function, and uses the taboo search algorithm to obtain the local optimal solution for personnel allocation within the complexity and time range that the engineering project can accept. User interaction layer: provides an intuitive user interface to display evaluation results and visual reports for easy user understanding and analysis. At the same time, it receives user feedback and instructions to achieve the interactivity and flexibility of the system.

[0108] Data collection and integration utilizes APIs and other methods to collect mission-related data. The collected data is cleaned and integrated to ensure data quality and consistency. This system optimizes the scheduling of comprehensive support mission training subjects, focuses on key areas of comprehensive support mission exercises, improves management refinement, and enhances resource management. This system provides strong support for the operationalization of logistics activities and ensures that resources are focused on and operated for combat.

[0109] Through automated data collection, the present invention can accurately collect various types of data generated during the execution of comprehensive support tasks, avoiding errors and delays in traditional data collection; at the same time, the data analysis layer can quickly process and analyze these data, greatly improving the evaluation efficiency and accuracy; through a multi-strategy performance evaluation model, it can provide more comprehensive and objective evaluation results by integrating multiple aspects, helping decision makers to fully understand the execution of comprehensive support tasks and conduct comprehensive and objective evaluations; it can promptly discover problems and anomalies in the task execution process as needed, thereby adjusting strategies in a timely manner, reducing unnecessary losses, and improving the efficiency and success rate of task execution; it can provide decision makers with optimization suggestions for resource allocation based on historical data and evaluation results, so that resources can be more reasonably allocated to various tasks, improving resource utilization efficiency, and optimizing resource allocation; decision makers can make more scientific and reasonable decisions based on the evaluation reports and data visualization results provided by the system, thereby reducing the risk of decision-making; the built-in evaluation model supports customization and adjustment, and can flexibly adapt to comprehensive support tasks of different types and needs, expanding the application scope of the system and having strong adaptability.

[0110] In another embodiment, the present invention provides a computer-readable storage medium storing a computer program, wherein the computer program enables a computer to execute the above-mentioned method for evaluating and assigning personnel for a comprehensive support task.

[0111] In another embodiment, the present invention proposes an electronic device comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements a comprehensive support task personnel assessment and assignment method as described above.

[0112] In the embodiments disclosed herein, computer storage media can be tangible media that can contain or store programs for use by or in conjunction with an instruction execution system, device, or apparatus. Computer storage media can include, but are not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or equipment, or any suitable combination of the foregoing. More specific examples of computer storage media can include electrical connections based on one or more lines, portable computer disks, hard disks, random access memories (RAM), read-only memories (ROM), erasable programmable read-only memories (EPROM or flash memory), optical fibers, portable compact disk read-only memories (CD-ROMs), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0113] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed in this application can be implemented in electronic hardware or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0114] The above are merely preferred embodiments of the present invention. The scope of protection of the present invention is not limited to the above embodiments. All technical solutions based on the principles of the present invention are within the scope of protection of the present invention. It should be noted that for those skilled in the art, various improvements and modifications that do not depart from the principles of the present invention should be considered within the scope of protection of the present invention.

Claims

1. A method for evaluating and allocating personnel for comprehensive support tasks, characterized in that: The steps include: According to the needs of comprehensive support tasks, tasks are divided into major categories, and each major task category is further divided into several sub-tasks. The historical accumulated data of the execution of each sub-task is collected, and the collected data is normalized and pre-processed. The processed historical accumulated data is used to calculate the average historical execution efficiency of a single person in each sub-task, and a performance evaluation model is constructed. The historical execution efficiency of the average single person in each sub-task, as well as the corresponding duration of each sub-task and the demand for each sub-task are input. The best personnel allocation is calculated through the taboo search algorithm, and the local optimal solution for personnel allocation is output.

2. A comprehensive support task personnel assessment and allocation method according to claim 1, characterized in that: The method of calculating the optimal personnel allocation by using the taboo search algorithm also includes the following steps: Set personnel allocation constraints and calculation termination rules. The algorithm execution can be terminated early when any of the following conditions is met: The first is the number of iterations. When the number of iterations reaches 1000, the algorithm execution is automatically terminated, and the set of executor allocations with the largest evaluation function value is selected from the past 1000 values ​​as the optimal solution for the project. When there are multiple identical maximum values ​​of the evaluation function, the combination with the smallest sum of the personnel allocation values ​​is selected as the local optimal solution for the project. The second is based on the evaluation value principle. When the evaluation value of the evaluation function is greater than the preset value in any algorithm case, the algorithm terminates.

3. A comprehensive support task personnel assessment and allocation method according to claim 2, characterized in that: The performance evaluation model is represented by the following function: Where n is the number of major task categories divided according to the comprehensive support task requirements, M n is the weight coefficient corresponding to each task category, A is the number of subtasks in the first task category, a is the label of the subtask in the first task category, B is the number of subtasks in the second task category, b is the label of the subtask in the second task category, C is the number of subtasks in the nth task category, c is the label of the subtask in the nth task category, are the corresponding average historical execution efficiency of a single person, as input constants, are the corresponding subtask durations, as input constants, are the corresponding subtask requirements, as input constants, H a , W b , Y c are the corresponding number of subtask executors.

4. A comprehensive support task personnel assessment and allocation method according to claim 3, characterized in that: The personnel allocation constraints include: H1+H2+...+H a ≤H H1,H2,...,H a ∈[0,H] W1+W2+...+W b ≤In W1,W2,...,W b ∈[0,W] Y1+Y2+...+Y c ≤Y Y1,Y2,...,Y c ∈[0,Y] Among them, H is the total number of logistics personnel available for deployment to the first major task category, which is an input constant, W is the total number of logistics personnel available for deployment to the second major task category, which is an input constant, and Y is the total number of logistics personnel available for deployment to the nth major task category, which is an input constant.

5. A comprehensive support task personnel assessment and allocation method according to claim 4, characterized in that: The personnel allocation constraints also include:

6. A comprehensive support task personnel assessment and allocation method according to claim 5, characterized in that: The algorithm execution includes the following steps: Step 1: Set the initial personnel allocation solution [H1,H2,...,H a ,W1,W2,...,W b Y1,Y2,...,Y c ]=[1,1,..,1], set the initial value of the taboo table set to empty, calculate the X function value according to the initial personnel allocation solution, if the termination rule is met, the algorithm terminates and outputs the result; if the termination rule is not met, set the current solution set to the initial solution set, add the initial solution set to the taboo table set, and execute the next step; Step 2: Use the traversal method to generate a new solution set for the domain of the initial solution set. If the generated new solution set is in the taboo table, regenerate the new solution set and recalculate the evaluation function value; if the termination rule is met, the algorithm terminates and outputs the result; if the termination rule is not met, compare the evaluation function value calculated by the new solution of this round with the evaluation function value calculated by the current solution set. If the evaluation function value of this round is greater than the evaluation function value of the previous round, update the current solution set to the new solution set of this round; if the evaluation function value of this round is less than or equal to the evaluation function value of the previous round, add the new solution set of this round to the taboo table set; Step 3: Repeat step 2 until the termination rule is met.

7. A comprehensive support task personnel assessment and allocation method according to claim 1, characterized in that: The method also includes the following steps: visualizing the output local optimal solution of personnel allocation and displaying the evaluation results in the form of charts or dashboards.

8. A comprehensive support task personnel assessment and allocation method according to claim 1, characterized in that: The major categories of tasks include logistics resource support tasks, medical resource support tasks and transportation resource support tasks.

9. A computer-readable storage medium storing a computer program, characterized in that: The computer program enables a computer to execute a comprehensive support task personnel assessment and assignment method as described in any one of claims 1-8.

10. An electronic device, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, a method for evaluating and allocating personnel for a comprehensive support task as described in any one of claims 1 to 8 is implemented.

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