Labor dispatch outsourcing management and intelligent manpower dispatch outsourcing system

Abstract

The invention relates to the technical field of human resource management, in particular to a labor dispatch outsourcing management and intelligent human dispatch outsourcing system, which comprises a process disassembly module, a condition check module, a capability construction module, a connection screening module and a dispatch adaptation module. According to the method, the post task is subjected to nodal sequence processing, digital expression of the post operation process is realized in combination with action labels and operation stage mapping, deviation nodes in the operation process are identified by means of device numbers and sorting verification of operation sections, and the task process precision and the quality control capability are improved; post boundary condition constraint verification is completed by fusing post equipment permission and an operation section period table, the probability of occurrence of task matching conflicts is remarkably reduced, and the coherence consistency of personnel and post actions is improved by comparing behavior tags with a post action sequence, so that accurate matching and efficient coherence deployment of tasks and personnel are realized, and the task matching efficiency is improved. And the intelligence, the matching degree and the performability of labor dispatching are enhanced.

Description

Technical Field

[0001] This invention relates to the field of human resource management technology, and in particular to a labor dispatch outsourcing management and intelligent human resource dispatch outsourcing system. Background Technology

[0002] Human resource management technology involves the planning, organization, coordination, and control of internal and external human resources, including recruitment, job allocation, performance appraisal, training and development, compensation and benefits, and labor relations management. In particular, the rational management of human resource allocation and employment methods is an important component of achieving optimal human resource allocation. With the diversification of social employment forms and the increasing demand for flexible employment by enterprises, labor dispatch and human resource outsourcing have gradually become important directions in human resource management. Traditional labor dispatch and outsourcing management and human resource dispatch and outsourcing systems refer to a management mechanism in which the demand for personnel is transformed into labor dispatch or outsourcing agreements through third-party intermediaries. The agency then provides temporary, seasonal, or project-based workers to the employers according to the cooperation agreement. This typically involves manual operation combined with electronic spreadsheets to register personnel information, with human resource specialists manually matching dispatch positions. Communication and coordination are carried out by telephone or email, and finally, personnel scheduling and task assignment are completed through paper contracts or simple documents.

[0003] In the current outsourced labor dispatch process, personnel information is generally recorded manually using forms. When matching positions, it mainly relies on the subjective judgment of human resources specialists, lacking systematic process breakdown and data-driven action node analysis. The job requirements and personnel capabilities cannot be compared in a structured way. When faced with a large number of temporary labor needs or complex task arrangements, information omissions, matching deviations, or response delays are likely to occur. Inconsistencies between personnel and job scheduling will lead to repeated communication, task delays, and even labor disputes. Especially in scenarios with high requirements for equipment operation permissions and time restrictions, the failure to verify boundary conditions is more likely to lead to allocation failures or increased operational risks. Summary of the Invention

[0004] The purpose of this invention is to overcome the shortcomings of existing technologies and propose a labor dispatch outsourcing management and intelligent human resource dispatch outsourcing system.

[0005] To achieve the above objectives, the present invention adopts the following technical solution: a labor dispatch outsourcing management and intelligent human resource dispatch outsourcing system includes: The process decomposition module obtains the task details of the labor dispatch positions, reads the task process sequence and action tags, generates a node sequence according to the task process sequence, extracts the equipment number and work section number, performs sorting detection on the work section number and marks process deviation nodes, and generates a job process action sequence table. The condition verification module performs a set operation on the node equipment number and the equipment operation permission list based on the job operation sequence list, performs interval matching judgment on the work section and the section operation time table, marks conflicting nodes, and obtains the job boundary condition mismatch list. The capability building module obtains the capability nodes of outsourced personnel from the outsourced human resources database, extracts the skill level identifier, job tag, work behavior tag and qualification level of each person, filters out the personnel numbers that meet the job requirements and summarizes them to generate a list of personnel numbers that are suitable for the job. The matching module compares the personnel work behavior tags with the job action tags in sequence according to the list of personnel numbers suitable for the job, selects personnel who are fully connected to the task nodes, and establishes a pairing mapping between the job and the personnel to obtain the job personnel node connection pairing group.

[0006] As a further embodiment of the present invention, the job operation sequence list includes a node sequence, process deviation node markers, and an abnormal job list; the job boundary condition mismatch list includes conflict nodes, mismatch cause records, and job number index; the job adaptability personnel number list includes a personnel number set, skill matching degree screening results, and tag overlap statistics; and the job personnel node connection pairing group includes a mapping relationship between job number and personnel number, a fully connected personnel identifier, and a combination of covering tags.

[0007] As a further aspect of the present invention, the process disassembly module includes: The task sequence extraction submodule reads the task process sequence and action tags in sequence according to the task details of the labor dispatch positions, generates a node sequence according to the task process sequence, maps each action tag to the work stage, and extracts the equipment number and work section number to obtain node sequence information. The node deviation marking submodule performs sorting detection on the work section numbering according to the node sequence information, identifies the sequence distribution between each number, and determines whether they are continuous and non-repeating. If there are skipped orders or missing items, the corresponding node is marked as a process deviation node, and the process deviation node information is obtained. The job process generation submodule extracts the corresponding job number based on the process deviation node information, filters all job numbers with deviation nodes, establishes an abnormal job list, and, in conjunction with the task process sequence and action tag matching relationship, organizes the action execution sequence under each job to obtain the job process action sequence table.

[0008] As a further aspect of the present invention, the condition verification module includes: The license matching submodule extracts the equipment number of each action node based on the node information in the job operation sequence table, extracts the equipment operation license list according to the job safety restriction parameters set in the outsourcing agreement, performs a set comparison operation on the equipment number and the equipment code field in the license list, and if the node equipment number is not in the license set, it is marked as equipment license mismatch and the node number is recorded, generating an equipment license conflict list. The time period verification submodule reads the section operation time period table based on the work section number corresponding to the node in the equipment permission conflict list, extracts the allowed work time period for the position, performs interval matching judgment on the planned work time of the current work node, and marks it as a time mismatch node based on the work section number corresponding to the node in the equipment permission conflict list, and generates a time conflict node table. The conflict recording submodule performs node merging processing based on the node numbers in the time conflict node table and the device permission conflict list, establishes a mapping between job number, node number, conflict type and mismatch reason, calculates and obtains the job boundary mismatch degree, and if it is greater than the mismatch degree value set threshold, it is included in the conflict node list and archived, and a job boundary condition mismatch list is established.

[0009] As a further aspect of the present invention, the capability building module includes: The skills stratification submodule is based on the outsourced personnel's ability nodes in the outsourced human resources database. It reads the skill level identifier registered by each outsourced personnel, converts the level identifier content into a unified standard skill code, groups the codes, establishes skill level ranges, classifies personnel numbers according to the range to which the code belongs, completes the mapping between personnel numbers and skill levels, counts the number and distribution of personnel under each skill level, and generates skill level mapping distribution data. The job matching submodule compares the personnel IDs included in the skill level mapping distribution data with the job requirement tags one-to-one, decomposes the job tag items into a refined tag set, compares the number of matches between the personnel tag set and the target job tag set, extracts the total number of work behavior tags and qualification level data for each person, and combines and summarizes the tag matching results, behavior quantity and qualification data to obtain the job tag matching degree result. The adaptive screening submodule, based on the personnel number corresponding to the job tag matching result, compares the number of tag matches, work behavior tags and qualification levels with the skill matching reference standard, filters out personnel numbers that meet the job requirements and summarizes them to obtain a list of personnel numbers suitable for the job.

[0010] As a further aspect of the present invention, the connecting screening module includes: The tag matching submodule extracts the set of work behavior tags for the corresponding personnel and the sequence of action tags for the target position based on the list of personnel numbers suitable for the position. It then splits the behavior tags and action tags into a sequence array, reorders the behavior tags according to the order of the position actions, and performs a sequential comparison to generate a sequence of behavior tag comparison results. The sequence coverage judgment submodule compares the target job action tag length with the continuous coverage length of the personnel behavior tags based on the behavior tag comparison result sequence, detects whether the continuous matching length is equal to the total length of the job action tags, and determines whether its tag index jumps without interruption. It calculates and obtains the action coverage difference value, marks it as a person with full connection of task nodes, and obtains the task node connection matching record. The job mapping generation submodule, based on the personnel numbers that meet the conditions in the task node connection matching record, combines the corresponding job numbers and establishes a number pairing structure, forming a binary mapping relationship between the job number and the personnel number, and obtains the job personnel node connection pairing group.

[0011] As a further aspect of the present invention, the system further includes: The dispatch adaptation module, based on the matching personnel combination in the matching group of conflict nodes and personnel nodes in the job boundary condition mismatch list, filters the job number of the conflict node and associates it with the replaceable personnel number, updates the workflow task allocation and records synchronously, and generates a smart outsourcing solution for labor dispatch. The intelligent outsourcing solution for labor dispatch includes task update mapping records, a list of personnel to replace conflicting positions, and synchronous dispatch records.

[0012] As a further aspect of the present invention, the dispatch adaptation module includes: The job conflict extraction submodule extracts the job number pointed to by the conflict node based on the conflict node information recorded in the job boundary condition mismatch list. It then compares the job number in the conflict node with the job field in the matching group of the job personnel node to identify all job number and personnel number combinations with boundary condition conflicts. Finally, it establishes a mapping between job number and conflicting job-person-job pairing relationship and obtains a conflicting job-person-job mapping list. The replacement personnel identification submodule, based on the job number information listed in the conflict job person-job mapping list, removes the personnel numbers marked as conflicting, filters the set of personnel numbers with the same job number, extracts the behavior tag content and task node information under the corresponding job number, and the task node covers the complete set of personnel numbers to generate a set of personnel numbers that can be replaced for the job. The task mapping update submodule, based on the set of personnel numbers that can be replaced for the job, compares the job numbers of the conflicting nodes and checks whether the replacement personnel have the same task tag structure as the conflicting job numbers. If the tag content is connectable in the task node, the original personnel number bound to the corresponding job is replaced with the recommended number, and the personnel pointing record in the task allocation structure is updated to obtain the intelligent outsourcing solution for labor dispatch.

[0013] Compared with the prior art, the advantages and positive effects of the present invention are as follows: In this invention, job tasks are processed into a node-based sequence, and action tags are combined with work stage mapping to achieve a digital expression of the job operation process. Deviation nodes in the operation process are identified by using equipment numbers and work segment sorting verification, thereby improving the accuracy and quality control of the task process. Job boundary condition constraint verification is completed by integrating job equipment permits and work segment time schedules, which significantly reduces the probability of task matching conflicts. The cross-screening based on skill level, job tag, behavior tag and qualification level improves the suitability of personnel for the job. The consistency of personnel and job actions is improved by comparing behavior tags with job action sequence, thereby achieving accurate matching and efficient coordination of tasks and personnel, and enhancing the intelligence, matching degree and executability of labor dispatch. Attached Figure Description

[0014] Figure 1 This is a system flowchart of the present invention; Figure 2 This is a flowchart of the process breakdown module of the present invention; Figure 3 This is a flowchart of the condition verification module of the present invention; Figure 4 This is a flowchart of the capability building module of the present invention; Figure 5 This is a flowchart of the screening and distribution module of the present invention; Figure 6 This is a flowchart of the dispatch adapter module of the present invention. Detailed Implementation

[0015] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0016] In the description of this invention, it should be understood that the terms "length," "width," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," and "outer," etc., indicating orientation or positional relationships, are based on the orientation or positional relationships shown in the accompanying drawings and are only for the convenience of describing the invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the invention. Furthermore, in the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0017] Please see Figure 1 A labor dispatch outsourcing management and intelligent human resource dispatch outsourcing system includes: The process decomposition module obtains the task details of the labor dispatch positions, reads the task process sequence and action labels, generates a node sequence according to the task process sequence, maps the action labels to the work stages one by one, extracts the equipment number and work section number, performs sorting detection on the work section number to determine whether the number is continuous and non-repeating, if there is a skip or missing item, the corresponding node is marked as a process deviation node (compliant with the quality management system standard), and the position number of the node is recorded in the abnormal position list, generating a job process action sequence table; The condition verification module extracts the equipment operation permit list and the section operation time table based on the equipment number and work area number corresponding to each action node in the job operation sequence table, combined with the job safety restriction parameters (based on occupational safety standards) specified in the outsourcing agreement. It then performs a set operation on the node equipment number and the equipment operation permit list, and performs interval matching judgment on the work area and the section operation time table. If the sets do not overlap or the time periods conflict, the node is marked as a conflict node and the reason for the mismatch is recorded, thus obtaining the job boundary condition mismatch list. The capability building module obtains the capability nodes of outsourced personnel from the outsourced human resources database, extracts the skill level identifier, job tag, work behavior tag and qualification level of each person, classifies the personnel into primary, intermediate and advanced levels according to the skill level identifier, matches the personnel with the job tag one by one according to the job tag, counts the number of work behavior tags and the total number of qualification levels included in each pairing, filters out the personnel who meet the job requirements (in accordance with the International Labour Organization skill classification standard) and numbers them up, and generates a list of personnel numbering suitable for the job. The matching module compares the work behavior tags of personnel with the job action tags in sequence according to the list of personnel numbers suitable for the job, and determines whether there are continuous overlapping combinations. If there are action tags that completely cover the work behavior tags, the corresponding personnel are set as the full matching personnel for the task node, and a pairing mapping is established between the job number and the personnel number to obtain the matching pairing group for job personnel node. The dispatch adaptation module matches personnel from the conflict nodes in the job boundary condition mismatch list with the personnel nodes in the job personnel connection pairing group, filters the job number of the conflict node and associates it with the replacement personnel number, updates the workflow task allocation and records it synchronously, and generates a smart outsourcing solution for labor dispatch.

[0018] The job operation sequence list includes node sequences, process deviation node markers, and a list of abnormal jobs. The job boundary condition mismatch list includes conflict nodes, mismatch cause records, and job number indexes. The job adaptability personnel number list includes a set of personnel numbers, skill matching degree screening results, and tag overlap statistics. The job personnel node connection pairing group includes the mapping relationship between job numbers and personnel numbers, full connection personnel identification, and coverage tag combinations. The intelligent outsourcing solution for labor dispatch includes task update mapping records, a list of personnel to replace conflicting jobs, and synchronous dispatch records.

[0019] Please see Figure 2 The process breakdown module includes: The task sequence extraction submodule reads the task process sequence and action tags in sequence according to the task details of the labor dispatch positions, generates a node sequence according to the task process sequence, maps each action tag to the work stage, and extracts the equipment number and work section number to obtain node sequence information. Based on the process decomposition module's call to the task details of dispatched workers, in actual on-site management, the system automatically extracts daily task details from the job scheduling platform via an interface. The structured fields of the task details include process sequence, action tags, equipment numbers, and work section numbers. For example, if job A01 performs a standard task on July 1st, the system retrieves its task details, displaying process sequences T1, T2, and T3, corresponding action tags "screw fixing," "cable connection," and "line testing," corresponding equipment numbers E01, E02, and E03, and work section numbers 101, 102, and 103. During the reading process, the system first constructs a process sequence according to the order of the task identifiers, generating node sequences 1, 2, and 3. Then, the action tags are converted into standard action codes, and the mapping table between action tags and work stages is called to complete the mapping from action tags to standard work stages P01, P02, and P03. Simultaneously, the original equipment number field is parsed, and multiple equipment numbers are processed using delimiters to form a standard number format array, and the work section number is extracted. Taking job A02 as an example, the original work section data is "201, 203", and the action labels are "spot welding" and "fine milling". In this case, the script needs to identify any skipped sequences between the numbers and record the deviation risk. For non-standard format content in the work section numbers, such as "501; 502; 504", they need to be standardized to be separated by commas and converted into an integer sequence for subsequent judgment. Based on multiple job work samples, a basic job work data table is formed, as shown in the table below: Table 1 Job Information Sheet Job Position Number Work section numbering sequence Process sequence label Equipment number sequence A01 101，102，103 T1, T2, T3 E01, E02, E03 A02 201，203 T1, T2 E04, E05 A03 301，302，303 T1, T2, T3 E06, E07, E08 A04 401，402 T1, T2 E09, E10 A05 501，502，504 T1, T2, T3 E11, E12, E13 As shown in Table 1, the data structure of each job position is clear. After field extraction, a five-element node information set is formed, which includes process sequence, action label, equipment number, and work section number, and then node sequence information is generated.

[0020] The node deviation marking submodule performs sorting detection on the work section numbering according to the node sequence information, identifies the sequence distribution between each number, and determines whether they are continuous and non-repeating. If there are skipped orders or missing items, the corresponding node is marked as a process deviation node, and the process deviation node information is obtained. Based on the node sequence information, the system sorts and judges the work section numbers in each position one by one to identify whether there are skipped or missing items. Taking position A01 as an example, the section numbers are 101, 102, 103. After sorting in ascending order, the difference sequence is [1, 1], which meets the requirement of continuous and non-repeating. The section numbers of position A02 are 201, 203. After sorting, the difference is [2]. The number 202 is skipped in the middle, which is judged as skipped. The section numbers of position A05 are 501, 502, 504. After sorting, the difference sequence is [1, 2]. The number 503 is missing, which is also judged as skipped. The system marks items with a difference greater than 1 in the difference sequence and locates the process label and node position to form a deviation record. The deviation type is judged based on whether the difference is an integer interval: if the difference is 2 and the missing number is the middle value, it is a missing item; if the number sequence is irregular and disordered, it is marked as skipped. In the example, A02 is missing 202. Node T2 is marked as a process deviation node with the deviation type "missing item," and its corresponding job number is recorded in the abnormal job list. The system aggregates all deviation nodes into a deviation record list for subsequent process correlation analysis to obtain process deviation node information.

[0021] The job process generation submodule extracts the corresponding job number based on the process deviation node information, filters all job numbers with deviation nodes, establishes an abnormal job list, and, in conjunction with the task process sequence and action tag matching relationship, organizes the action execution sequence under each job to obtain the job process action sequence table. Based on the process deviation node information, the system filters the job numbers with deviation nodes, obtaining a list of abnormal jobs [A02, A05]. It then retrieves the task details for each job, rereads the action tags and process sequences, and constructs a job-process action mapping. For example, in the task record of job A02, the process sequences T1 and T2 correspond to the action tags "spot welding" and "fine milling," which are standardized and converted into action codes A003 and A005. In job A05, the actions "component docking," "bolt tightening," and "line inspection" are coded as A007, A009, and A011, respectively, forming a structure {job number, process sequence number, action number}, such as A02-T1-A003 and T2-A005. The process action structures of each job are sorted sequentially to match the node sequence, completing the job action path regularization. Finally, the system generates a complete job process action mapping sequence for all abnormal jobs, used for quality tracking and deviation correlation identification, and obtains a job process action sequence table.

[0022] Please see Figure 3 The condition verification module includes: The license matching submodule extracts the equipment number of each action node based on the node information in the job operation sequence table, extracts the equipment operation license list according to the job safety restriction parameters set in the outsourcing agreement, performs a set comparison operation on the equipment number and the equipment code field in the license list, and if the node equipment number is not in the license set, it is marked as equipment license mismatch and the node number is recorded, generating an equipment license conflict list. Based on the node information in the job operation sequence table, the system extracts the equipment number of each action node. During operation, the system first reads the node structure under each job position. Taking jobs A02 and A05 as examples, the corresponding node numbers are extracted as N11 and N23 respectively. The system then parses the equipment field referenced by the action node, extracting equipment numbers E04 and E12 respectively. Subsequently, the system reads the outsourcing agreement terms signed by the corresponding job position. The job position safety restriction parameter field contains a list of permitted equipment numbers. This information is read using the job position as an index to retrieve the permitted equipment set. For example, the permitted equipment set for A02 is {E01, E02, E03}, and A0... The set of licensed devices is {E11, E13}. Then, the device numbers from the above nodes are used to construct sets {E04} and {E12} respectively. The system performs a set inclusion relationship check on the two sets, that is, checks whether the node device set is a subset of the licensed set. The result is that neither is true. Therefore, nodes N11 and N23 are marked as device license conflict nodes, and relevant information is recorded in the conflict list. The conflict information includes the job number, node number, device number, list of licensed devices, and corresponding device operation parameters. Parameters such as operation intensity, safety level, and correlation factors are extracted from the job task table and appended to the table, as shown in Table 2. Table 2 Parameter Table for Job Conflict Nodes Job Number Node number Equipment Number List of licensed devices Planned time (minutes) Permitted time period (minutes) Work intensity Security level Correlation factors A02 N11 E04 E01, E02, E03 540 510-570 0.8 4 1.1 A05 N23 E12 E11, E13 600 580-590 0.7 5 0.9 As shown in Table 2, the device numbers associated with nodes N11 and N23 are not included in the list of licensed devices. The system identifies them as nodes with device license conflicts and obtains the list of device license conflicts.

[0023] The time period verification submodule reads the section operation time period table based on the work section number corresponding to the node in the equipment permission conflict list, extracts the allowed work time period for the position, performs interval matching judgment on the planned work time of the current work node, and marks it as a time mismatch node based on the work section number corresponding to the node in the equipment permission conflict list, and generates a time conflict node table. Combining the planned time and allowed work time periods in Table 2, the system compares the time parameters item by item for each job position. For job position A02 node N11, the planned time is 540 minutes, and the corresponding allowed work time period is 510 to 570 minutes. It is determined whether 540 falls within the interval [510, 570], and the conclusion is that it is true, and the node time matches. However, for job position A05 node N23, the planned time is 600 minutes, and the corresponding allowed work time period is 580 to 590 minutes. It is determined whether 600 belongs to the interval [580, 590], and the result is not true, and the node time conflicts. The system uses upper and lower limit comparison logic to judge separately: if the planned time is less than the start time or greater than the end time, it is considered a mismatch, and the corresponding time field and node information are recorded. Finally, a time conflict node set is formed, which only contains N23 with time mismatch, and the time conflict node table is obtained.

[0024] The conflict recording submodule performs node merging processing based on the node numbers in the time conflict node table and the equipment permission conflict list, establishing a mapping between job number, node number, conflict type, and mismatch reason, using the formula: ; The job boundary mismatch degree is calculated. If it exceeds a set threshold, it is added to the conflict node list and archived, thus establishing a job boundary condition mismatch list. Indicates job position Assign task Job boundary mismatch Indicates job position The Middle The device ID value (numerical code) of each node. Indicates task The licensed device number value, Indicates task The corresponding node's security restriction level value, Indicates job position The Middle The physical execution correlation value between the node's action and the device. Indicates job position Planned start time for the corresponding section (unit: minutes). Indicates task The median time point of the permitted work period (in minutes). Indicates task Total permitted working hours (in minutes); Based on the node numbers recorded in the aforementioned equipment license conflict list and time conflict node table, the system integrates the conflict nodes, extracts the parameter values ​​for calculation from the job operation records, and performs job boundary mismatch calculation using a formula, where: :post The Middle The equipment number value corresponding to each node is obtained by parsing the equipment field of each action node in the job operation sequence table to extract the original equipment number. Then, the equipment code is uniformly converted into an integer value (such as E01→101, E12→112) according to the number conversion rules for subsequent difference calculation. :Task The licensed equipment number value is obtained by reading the licensed equipment list field of the task position safety parameters in the outsourcing agreement terms, selecting the set of licensed equipment corresponding to the position, encoding and converting the equipment serial number, and extracting its mean or median as the matching benchmark number; :Task The Middle The safety restriction level value of each node is given by the "Safety Level" field in the job operation specification table. The value range is usually 1-5. The larger the value, the stricter the restriction requirements on equipment operation of the job node. :post The Middle The physical execution correlation factor between the device and the action corresponding to each action node is obtained by statistically analyzing the historical coupling frequency between action type and device type in the job execution data. It represents the core usage degree of the device in that action type, and the value range is generally 0.6–1.2. :post The planned start time of the task is read from the job scheduling system, and the corresponding job execution time field is expressed in minutes. For example, 08:30 is converted to 510 minutes. :Task The median time of the permitted work period is calculated by taking the midpoint value from the upper and lower limits of the permitted time period set in the agreement terms. If the permitted time period is [580, 590] minutes, then... ; :Task The total length of the allowed work period is calculated by subtracting the lower limit from the upper limit of the allowed work period. This ensures that the normalized time difference squared term matches the first half of the dimension, with the unit being minutes.

[0025] Taking node N23 in position A05 as an example for calculation: the device number E12 is coded as 112, and the average code of the permitted devices is set as (E11, E13) = average (111, 113) = 112. Therefore, the difference is 112 - 112 = 0; the security level is 5. The workload intensity is 0.7, the equipment correlation factor is 0.9, and the product is 0.63. Therefore, the result for the first part is... Next, let's look at the time section, the planned time. The allowed time period is 580-590 minutes, corresponding to a median value. Interval width Substituting into , After taking the root, it becomes The final mismatch degree is Assuming the threshold θ is 4.5, determine Since the mismatch is established, node N23 constitutes a job boundary mismatch. The system records the mismatch type as "time conflict" and summarizes the conflict nodes and causes to establish a job boundary condition mismatch list.

[0026] Job boundary mismatch is a comprehensive indicator used to measure whether the equipment usage permissions and work time restrictions of a job during the execution of a specific task node simultaneously meet the requirements of the job outsourcing agreement and safety specifications. This indicator integrates equipment permission deviations and work time conflicts through a unified measurement standard, reflecting the compliance degree of the node under safety boundary conditions. The equipment part measures the degree of numerical difference between the equipment actually used by the job and the prescribed permitted equipment, and adjusts its influence weight according to the correlation strength of safety level and work actions. The time part assesses the degree of deviation between the work time and the permitted time period and normalizes it. The larger the boundary mismatch value formed by the combination of the two parts, the higher the degree of violation of safety boundary constraints in the resource allocation or scheduling of the job at that node. Therefore, the boundary mismatch can be used as a basic criterion for job compliance analysis, conflict determination and scheduling correction.

[0027] The formula's operational logic is based on a joint evaluation mechanism of equipment matching error and operation time deviation. The first part uses difference normalization and weighted product to measure the degree of equipment number mismatch. Specifically, the equipment number difference... This indicates the coding offset between the equipment used in the position and the licensed equipment under the numbering system, quantifying the degree of deviation at the equipment level; through the denominator... Introducing a security level value means that in high-security scenarios, even slight deviations in device serial numbers can be amplified, thus increasing sensitivity; this normalization term is then multiplied by the strength of the physical correlation between the actual actions of the job and the operation of the equipment. This reflects the actual importance of the equipment in specific job actions; a high correlation results in a significant impact from deviations. The above part uses the summation of all nodes to form the overall mismatch degree in the equipment matching dimension, and applies an absolute value operation to prevent deviation signs from canceling each other out. The latter part independently constructs a time deviation item, using planned time. Compared with the median of allowed operation time The square of the difference represents the time offset, which is then divided by the total width of the time period. After normalizing the offset amplitude, the square root is taken to obtain the time mismatch intensity with the same numerical dimension as the first half. The two parts are directly added after the physical meaning is consistent, so as to realize the comprehensive boundary mismatch assessment of the job in the two dimensions of equipment permission and working time.

[0028] Please see Figure 4 The capability building module includes: The skills stratification submodule is based on the outsourced personnel's ability nodes in the outsourced human resources database. It reads the skill level identifier registered by each outsourced personnel, converts the level identifier content into a unified standard skill code, groups the codes, establishes skill level ranges, classifies personnel numbers according to the range to which the code belongs, completes the mapping between personnel numbers and skill levels, counts the number and distribution of personnel under each skill level, and generates skill level mapping distribution data. Based on the outsourced personnel capability nodes in the outsourced human resources database, the skill level identifier field for each person is extracted, and a level mapping standard is established. "Beginner" is mapped to code 1, "Intermediate" to code 2, and "Advanced" to code 3. In the actual sample, personnel R001's skill level is "Beginner" corresponding to code 1, R002 and R004 are "Intermediate" corresponding to code 2, and R003 is "Advanced" corresponding to code 3. Subsequently, a classification operation is performed based on the mapping codes, grouping personnel numbers according to skill level. The system completes the mapping registration between personnel numbers and skill codes, resulting in the following statistical results: the beginner category contains 1 person (R001), the intermediate category contains 2 people (R002 and R004), and the advanced category contains 1 person (R003). A skill level structure table is constructed for subsequent tag matching index operations. The statistical mapping relationship with the personnel number is shown in Table 3. Table 3. Outsourced Personnel Competency Parameters Personnel Number Skill level identifier Job tags Number of behavioral tags Qualification Level R001 primary Repair, electrician 4 2 R002 intermediate Electrical Engineering, Safety 6 4 R003 advanced Welding, Equipment Management 5 5 R004 intermediate Electrician, Equipment Management 3 3 As shown in Table 3, the skill level, job label, number of behavioral labels and qualification level of the four outsourced personnel have been clearly listed. The system completes the matching and distribution of personnel and levels, and obtains the skill level mapping distribution data.

[0029] The job matching submodule compares the personnel IDs included in the skill level mapping distribution data with the job requirement tags one-to-one. It decomposes the job tag items into a refined tag set, compares the number of matches between the personnel tag set and the target job tag set, extracts the total number of work behavior tags and qualification level data for each person, and combines and summarizes the tag matching results, behavior quantity and qualification data to obtain the job tag matching degree result. Based on the personnel IDs contained in the skill level mapping distribution data, the system calls the job label field of the personnel in Table 4 and decomposes each job label into individual label units separated by commas. For example, the label "Electrician, Equipment Management" of R004 is decomposed into "Electrician" and "Equipment Management". This label set is compared one-to-one with the label set "Electrician, Equipment Management" required for the target job. The results show that R004 is a perfect match, R003 matches "Equipment Management", R002 matches "Electrician", and R001 matches "Electrician". The number of matched labels for each person is counted as R004=2, R003=1, R002=1, and R001=1. Then, the number of behavioral labels and the qualification level value are obtained to form a three-item data structure for each person. For example, R004 has 2 matched labels, 3 behavioral labels, and 3 qualification levels. The above three values ​​are input into the structure table and used as reference items for label matching degree judgment. The system stores the label pairing structure according to the personnel ID to obtain the job label matching result.

[0030] The adaptive screening submodule filters out personnel numbers that meet the job requirements based on the personnel number corresponding to the job tag matching results, the number of tag matches, work behavior tags and qualification levels, and compares them with the skill matching reference standards, and summarizes them to obtain a list of personnel numbers that are suitable for the job. Based on the personnel IDs recorded in the job tag matching results, the system reads the number of matching tags, the number of behavioral tags, and the qualification level value item by item. The judgment criteria are set as follows: the number of matching job tags is not less than 1, the number of behavioral tags is within the range of [3, 6], and the qualification level is between [3, 5]. R004 satisfies 2 matching tags, 3 behavioral tags, and 3 qualification level. R003 has 1 matching tag, 5 behavioral tags, and 5 qualification level. R002 has 6 behavioral tags but only 1 matching tag and a qualification level of 4. R001 has 1 matching tag but a qualification level of 2, which is not within the standard range. The system filters personnel IDs based on the combination of the three data conditions and finally determines that R003 and R004 meet all the conditions. The system extracts their IDs to form a set and records them as a list of personnel IDs suitable for the job.

[0031] Please see Figure 5 The connecting screening and distribution module includes: The tag matching submodule extracts the set of work behavior tags for the corresponding personnel and the sequence of action tags for the target position based on the list of personnel numbering for the job. It then splits the behavior tags and action tags into a sequence array, reorders the behavior tags according to the order of job actions, and performs a sequential comparison to generate a sequence of behavior tag comparison results. Based on the personnel ID list for job suitability, the system extracts the behavioral tag sequence for each personnel and the action tag sequence for their corresponding job. The two sets of tags are then decomposed into sequential list structures, with behavioral tags serving as the source sequence and job action tags as the target sequence. The system compares each tag item in both sequences one by one according to its index position, marking each item for a match and constructing a comparison state mapping structure. For example, personnel P001 has behavioral tags of [Power On, Inspection, Maintenance, Power Off] and job action tags of [Power On, Inspection, Maintenance, Power Off]. The sequences are completely identical, all four tags match, and the index positions are identical. A one-to-one correspondence was established, recording 4 consecutive matching tags and 1 starting point. The behavior tags for P002 are [Power on, Inspection, Maintenance, Power off], and the action tags are [Power on, Inspection, Maintenance, Power off]. "Inspection" did not match "Inspection," while the other three matched, with two segments being "Power on" and "Maintenance-Power off." Therefore, the number of consecutive segment starting points is 2, and the number of tags is 3. This comparison process was performed on all personnel, and the matching length and number of matching starting points were counted. These were combined with the total number of action tags for each position and recorded in the structure table to generate a sequence of behavior tag comparison results. The comparison data results are shown in Table 4. Table 4. Job Movement Connection Data Table Personnel Number Job Number Behavioral label sequence Job Action Sequence Number of consecutive matching tags Number of consecutive matching starting points Total number of job action tags P001 J01 [Power on, Inspection, Repair, Power off] [Power on, Inspection, Repair, Power off] 4 1 4 P002 J01 [Power on, inspect, repair, power off] [Power on, Inspection, Repair, Power off] 3 2 4 P003 J02 [Inspection, equipment debugging, operation] [Inspection, equipment debugging, operation] 2 1 3 P004 J02 [Inspection, Repair] [Inspection, Repair] 2 1 2 The sequence coverage judgment submodule, based on the behavior tag matching result sequence, compares the length of the target job action tag with the continuous coverage length of the personnel behavior tags, checks whether the continuous matching length is equal to the total length of the job action tags, and determines whether its tag index jumps without interruption, using the formula: ; The calculation obtains the action coverage difference value, marks it as a fully connected person for the task node, and obtains the task node connection matching record. Personnel Action coverage difference value, This refers to the number of tags in the personnel behavior tags that continuously match the job action tags. This represents the number of starting points for the continuous segment. Total length of job action labels; Based on the comparison results in Table 4, extract the number of consecutive matching tags for each person. Number of consecutive matching starting points Total number of job action tags Substitute this value into the coverage deviation calculation formula for calculation.

[0032] Taking P004 as an example, , , Substitute the values ​​and calculate as follows: The first item is The second item is ,sum ; Take P001 again. , , ,but: The first item is The second item ,have to ; The calculation results for all personnel are as follows: P001: ; P002: ; P003: ; P004: ; The system sets the coverage error judgment threshold to 0.1 (its value is set based on the minimum significant deviation limit between the proportion of the longest continuous non-jumping segment in the job action label sequence and the complete coverage value; that is, when the number of consecutive matching labels is exactly the same as the number of job action labels, and there are no multi-starting point jump behaviors, the action coverage difference value approaches 0, while when there are breakpoints, jumps, or omissions, the value will shift rapidly). Therefore, the system selects the complete coverage standard of task sequence length q=4 as a reference, and determines the maximum deviation value of two people having one break or insufficient coverage in four label matching as the comparison baseline, and then based on common behavior sequences... The statistical proportion of the maximum number of jump segment starting points does not exceed 20% of the total sequence. 0.08 is set as the basic unit offset, and then it is floated up to 0.1 as the upper limit for judgment. This threshold will decrease as the total number of job action tags increases. Because the longer the action sequence, the smaller the allowable jump ratio, this setting is based on the job tag structure as the core constraint to ensure that the judgment scale is consistent and has a controllable tolerance range in different job scenarios. Only when the coverage difference is less than this threshold is it judged as a fully connected person for the task node. None of the above 4 people meet the conditions, so the system has not yet marked the fully connected state, recorded the coverage deviation value of each person, and obtained the task node connection matching record.

[0033] The action coverage difference value is an indicator used to measure the degree of difference between the sequence of work behavior labels of outsourced personnel and the sequence of action labels of target positions in terms of content coverage and sequential coherence. Specifically, it reflects whether personnel have the ability to perform all the actions required for the position completely and continuously. The coverage part represents whether the behavior labels include all the action labels of the position, while the difference part reflects whether the coverage appears in a continuous and non-jumping manner. When the behavior labels can completely cover the action labels of the position and there is no break or rearrangement in the order, the difference value is zero, indicating complete connection. If there are missing labels, misaligned order, or skipped matching, the difference value will increase. In job matching, this value can be used to identify suitable personnel who can complete all the specified operations without interruption in the execution process. It is the core judgment basis for job node allocation and behavior ability assessment.

[0034] The formula's operational logic aims to comprehensively measure the degree of sequential coverage and completeness deviation between outsourced personnel's behavioral labels and job action labels. Its construction method employs a summation structure of two sub-items: the first item... This indicates the degree of jump in the occurrence of the matched fragment in the behavior label, where This represents the total number of consecutively matched tags. This represents the starting point number of these segments. The larger the difference between the two values, the more matches there are, but the worse the continuity. This is determined by comparing the total length of the job action labels. Normalization, converting to dimensionless jumps, the second term Used to measure the deviation in the completeness of behavioral labels covering job action labels, when When the value is zero, it indicates complete coverage and zero deviation. The larger the value, the less complete the behavior label coverage. Over- or under-coverage situations are handled uniformly by using absolute values, and the sum of the two values ​​is ultimately taken as the overall action coverage difference. This structure does not introduce complex nonlinear factors such as multiplication or square roots in its calculations. It is an evaluation method based on a linear combination of proportional offset and jump degree, which facilitates the determination of job connection under a unified scale.

[0035] The job mapping generation submodule matches the personnel numbers that meet the conditions in the task node connection matching record, combines the corresponding job numbers and establishes a number pairing structure to form a binary mapping relationship between the job number and the personnel number, and obtains the job personnel node connection pairing group. Based on the coverage difference value in the task node connection matching record, a judgment is made by comparing it with the system-set threshold of 0.1. If a person's coverage difference value is... If the condition is less than 0.1, then the number is paired with the job number and stored in the job task mapping field table. In this round of data, none of the personnel V meet the set standard, so no pairing binding record is generated. The system records an empty pairing structure output and obtains the job personnel node connection pairing group.

[0036] Please see Figure 6 The dispatch adaptation module includes: The job conflict extraction submodule extracts the job number pointed to by the conflict node based on the conflict node information recorded in the job boundary condition mismatch list. It then compares the job number in the conflict node with the job field in the matching group of the job personnel node to identify all job number and personnel number combinations with boundary condition conflicts. Finally, it establishes a mapping between job number and conflicting job-person-job pairing relationship and obtains a conflicting job-person-job mapping list. Based on the conflict node information recorded in the job boundary condition mismatch list, the job number field corresponding to each conflict node is extracted and uniquely organized to obtain a set of unique job numbers for all job configuration anomalies. The combination relationship between job numbers and personnel numbers recorded in the job personnel node connection pairing group is then called. From this structure, all records whose job numbers belong to the aforementioned unique set are filtered out. Further determination is made as to whether the corresponding personnel are conflicting personnel. The determination is based on whether the personnel are marked as unable to form a stable matching relationship with the job under the job node due to factors such as behavior tags not meeting continuous matching or missing tag content. If the judgment result is a conflicting person, the job number and its corresponding personnel number are jointly registered in the mapping data structure between job and conflicting person. For example, if job J01 is marked as having an abnormal inspection order in the mismatch list, and the personnel P001 bound in its pairing group has a missing behavior tag "shutdown" action, and its consecutive matching number is 2 and the tag completeness is 0.65, then this person is determined to be a conflicting person-job combination. Job number J01 and personnel number P001 are mapped as a set of records to the conflict mapping list. Continue to traverse other conflict node information to complete the structure construction and obtain the conflicting job-person-job mapping list.

[0037] The replacement personnel identification submodule is based on the job number information listed in the conflict job person-job mapping list. It removes the personnel numbers that have been marked as conflicting, filters the set of personnel numbers with the same job number, extracts the behavior tag content and task node information under the corresponding job number, and the task node covers the complete set of personnel numbers to generate a set of personnel numbers that can be replaced for the job. Based on the job number field listed in the conflicting job-person-job mapping list, job numbers are extracted one by one, and all personnel numbers marked as conflicting are removed from the job-person node connection pairing group. Personnel records with the same job number but not marked as conflicting are retained. For the retained personnel numbers in these records, data fields such as label coverage, consecutive match count, action node count, and label match completeness are extracted as key factors in determining their suitability. Subsequently, a multi-dimensional reference standard is constructed, and feature comparisons are performed on each record among the retained personnel. The judgment criteria are whether the label coverage is not less than 0.85, whether the consecutive match count is not less than 75% of the action node count, and whether the label match completeness is higher than 0.80. A coverage less than 0.7 is considered low, and more than 0.85 is considered high. For label match completeness, less than 0.6 is considered low, and more than 0.8 is considered high. An example is shown below: Table 5 Examples of Job Substitution Adaptability Job Number Personnel Number Tag coverage Number of consecutive matches Number of action nodes Tag matching completeness Are they conflict participants? J01 P001 0.75 2 4 0.65 yes J01 P005 0.92 4 4 0.88 no J02 P002 0.68 1 3 0.60 yes J02 P006 0.85 3 4 0.80 no J03 P003 0.90 4 4 0.95 no As shown in Table 5, in job J01, the label coverage rate of P005 is 0.92, the number of consecutive matches is 4, and the label matching completeness is 0.88, all of which are higher than the preset judgment interval standard, and it is marked as a replaceable person. Similarly, in job J02, the label coverage rate of P006 is 0.85, the number of matches is 3, and the completeness is 0.80, which also meets the replacement condition. After the system records the above personnel information, it generates a set of replaceable personnel numbers for each job according to the job number.

[0038] The task mapping update submodule, based on the set of personnel IDs that can be replaced for a position, compares the position IDs of conflicting nodes and searches whether the replacement personnel have the same task tag structure as the conflicting position IDs. If the tag content is connectable in the task node, the original personnel ID bound to the corresponding position is replaced with the recommended ID, and the personnel pointing record in the task allocation structure is updated to obtain the intelligent outsourcing solution for labor dispatch. Based on the recommended personnel numbers in the set of replaceable personnel numbers, each personnel number is compared with its position number field and intersected with conflicting position numbers. If the position number bound to the recommended personnel number is equal to or contains the conflicting position number, it is marked as a replaceable combination. The original personnel numbers in each replaceable combination are replaced by the recommended personnel numbers in the personnel field of the node in the workflow task structure. At the same time, the corresponding records of task numbers and personnel numbers in the task mapping relationship table are updated synchronously. After the update, the structural combination relationship between position numbers and updated personnel numbers is constructed. The updated structural data of all conflicting positions are integrated and output in a unified dispatch task mapping structure document format to obtain the intelligent outsourcing solution for labor dispatch.

[0039] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention in any other way. Any person skilled in the art may make changes or modifications to the above-disclosed technical content to create equivalent embodiments that can be applied to other fields. However, any simple modifications, equivalent changes, and modifications made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the protection scope of the present invention.

Claims

1. A labor dispatch outsourcing management and intelligent human dispatch outsourcing system, characterized in that, The system comprises: The process disassembly module obtains the labor dispatch post execution task details, reads the task procedure sequence and action label, generates node sequence according to the task procedure sequence, extracts the equipment number and work section number, performs sequence detection on the work section number and marks the process deviation node, and generates the post procedure action sequence list; The condition checking module performs set operation on the node equipment number and the equipment operation permission list according to the post procedure action sequence list, performs interval matching judgment on the work section and the section operation time period table, marks the conflict node, and obtains the post boundary condition mismatch list; The ability construction module extracts the skill level identifier, post label, work behavior label and qualification level of each personnel from the outsourcing personnel ability node in the outsourcing human resource database, filters the personnel number meeting the post requirements and summarizes, and generates the post adaptive personnel number list; The connection screening module compares the personnel work behavior label and the post action label according to the post adaptive personnel number list, screens the task node full connection personnel, and establishes the pairing mapping between the post and the personnel, to obtain the post personnel node connection pairing group.

2. The managed workforce outsourcing and intelligent human workforce deployment system of claim 1, wherein, The post procedure action sequence list includes node sequence, process deviation node marking and abnormal post list, the post boundary condition mismatch list includes conflict node, mismatch reason record and post number index, the post adaptive personnel number list includes personnel number set, skill matching degree screening result and label coincidence statistical data, and the post personnel node connection pairing group includes post number and personnel number mapping relationship, full connection personnel identifier and covering label combination.

3. The managed workforce solution and intelligent human outsourcing system of claim 1, wherein, The process disassembly module comprises: The task sequence extraction submodule reads the task procedure sequence and action label in sequence according to the labor dispatch post execution task details, generates node sequence according to the task procedure sequence, and maps each action label and work stage one by one, while extracting the equipment number and work section number to obtain node sequence information; The node deviation marking submodule performs sequence detection on the work section number according to the node sequence information, identifies the sequence distribution between each number, judges whether it is continuous and non-repetitive, and if there is a sequence jump or missing item, marks the corresponding node as a process deviation node to obtain process deviation node information; The post procedure generation submodule extracts the post number corresponding to the process deviation node information, screens all post numbers with deviation nodes, establishes an abnormal post list, and arranges the action execution sequence under each post according to the matching relationship between the task procedure sequence and the action label to obtain the post procedure action sequence list.

4. The managed workforce outsourcing and intelligent human workforce deployment system of claim 1, wherein, The condition checking module comprises: The permission matching submodule extracts the equipment number of each action node based on the node information in the post procedure action sequence list, extracts the equipment operation permission list according to the post safety limit parameters set in the outsourcing agreement terms, performs set comparison operation on the equipment number and the equipment code field in the permission list, and if the node equipment number is not in the permission set, marks it as equipment permission inconsistent and records the node number to generate the equipment permission conflict list; The time period checking submodule reads the section operation time period table based on the job section number corresponding to the node in the equipment permission conflict list, extracts the post allowed operation time period, and performs interval matching judgment on the current operation node plan operation time. If the operation time period is not in the allowed time period interval, the node is marked as a time mismatch node, and a time conflict node table is generated; The conflict record submodule performs node merging processing according to the time conflict node table and the node number in the equipment permission conflict list, establishes the mapping of post number, node number, conflict type and mismatch reason, calculates the post boundary mismatch degree, and if it is greater than the mismatch degree value setting threshold, it is listed in the conflict node list and archived, and a post boundary condition mismatch list is established.

5. The managed workforce outsourcing and intelligent human workforce deployment system of claim 1, wherein, The capability building module comprises: The skill stratification submodule reads the skill level identifier registered by each outsourcing personnel based on the outsourcing personnel capability node in the outsourcing human resource database, converts the level identifier content into a unified standard skill code, and performs grouping processing on the code to establish a skill level interval. According to the interval to which the code belongs, the personnel number is classified, the corresponding mapping of the personnel number and the skill level is completed, the number and distribution state of personnel under each skill level are counted, and skill level mapping distribution data is generated; The post matching submodule compares the personnel number included in the skill level mapping distribution data with the post demand label one by one, decomposes the post label item into a refined label set, compares the matching number between the personnel label set and the target post label set, extracts the total number of work behavior labels and qualification level data of each personnel, and combines and summarizes the label matching result, the number of behaviors and the qualification data to obtain a post label matching degree result; The adaptive screening submodule compares the label matching number, work behavior label and qualification level with the skill matching reference standard according to the personnel number corresponding to the post label matching result, screens personnel numbers that meet the post requirements and summarizes them to obtain a post adaptive personnel number list.

6. The managed workforce outsourcing and intelligent human workforce deployment system of claim 1, wherein, The connection screening module comprises: The label matching submodule extracts the work behavior label set of the corresponding personnel and the target post action label sequence according to the post adaptive personnel number list, uniformly splits the behavior label and the action label into a sequence array, reorders the behavior label according to the post action order, and performs sequential comparison to generate a behavior label comparison result sequence; The sequence coverage judgment submodule compares the target post action label length and the personnel behavior label continuous coverage length based on the behavior label comparison result sequence, detects whether the continuous matching length is equal to the total length of the post action label, judges whether the label index is discontinuous and jumps, calculates the action coverage difference value, marks the task node full-connection personnel, and obtains the task node connection matching record; The post mapping generation submodule combines the corresponding post number and establishes a number pairing structure according to the personnel number that meets the condition in the task node connection matching record, forms a binary mapping relationship between the post number and the personnel number, and obtains a post personnel node connection pairing group.

7. The managed workforce solution and intelligent human outsourcing system of claim 1, wherein, The system further comprises: The dispatch adaptation module screens the post number of the conflict node according to the matching personnel combination in the matching personnel group in the post boundary condition mismatch list and the connection and pairing group of the post personnel node, associates the replaceable personnel number, updates the workflow task allocation and synchronously records, generates the intelligent outsourcing scheme of labor manpower dispatch, and the intelligent outsourcing scheme of labor manpower dispatch includes task update mapping record, conflict post replacement personnel list, and synchronous dispatch record. The dispatch adaptation module includes:

8. The managed workforce outsourcing and intelligent human workforce deployment system of claim 7, wherein, The post conflict extraction submodule extracts the post number pointed by the conflict node according to the conflict node information recorded in the post boundary condition mismatch list, combines the post number and personnel number combination recorded in the connection and pairing group of the post personnel node, compares the post number in the conflict node with the post field in the pairing group for matching, identifies all the post number and personnel number combinations with boundary condition conflicts, and establishes the mapping of the post number and the conflict person-post pairing relationship, obtains the conflict post person-post mapping list, and extracts the behavior label content and task node information under the corresponding post number. The replacement personnel identification submodule excludes the personnel number marked as conflict based on the post number information in the conflict post person-post mapping list, screens the personnel number set with the same post number, extracts the behavior label content and task node information under the corresponding post number, and the task node covers the complete personnel number set to generate the replaceable personnel number set of the post. The task mapping update submodule checks whether the replacement personnel has the same task label structure as the conflict post number according to the replaceable personnel number set of the post, replaces the original binding personnel number of the corresponding post with the recommended number if the label content has the connectable nature in the task node, updates the content of the personnel pointing record in the task allocation structure, and obtains the intelligent outsourcing scheme of labor manpower dispatch. ​

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