CN110751376B - Work order distribution scheduling method and device, computer equipment and storage medium - Google Patents
Work order distribution scheduling method and device, computer equipment and storage medium Download PDFInfo
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Abstract
The invention provides a work order distribution scheduling method, a work order distribution scheduling device, computer equipment and a storage medium. The method comprises the steps of receiving a work order to be processed submitted by a client; calculating the work order requirement evaluation parameter of the current processing node according to the information of the work order to be processed; acquiring a historical work order processing log; extracting the processing information of a processor from a historical work order processing log; calculating a processor capability evaluation parameter according to the processing information of the processor; determining a first matching degree of the processor and the work order to be processed according to the processor capacity evaluation parameter and the work order requirement evaluation parameter; determining a target processor of the work order to be processed in the plurality of processors according to the first matching degree; and distributing the current processing node of the work order to be processed to the target processor. By the method and the device, flexible allocation of the processing nodes in the work order processing flow can be realized.
Description
Technical Field
The present invention relates to the field of work order processing technologies, and in particular, to a work order allocation scheduling method and apparatus, a computer device, and a storage medium.
Background
The traditional work order transaction system is based on a fixed process model, that is, a fixed process is set for each type of work order, and in the fixed process, the participants are fixed, and the information transmission path is fixed, for example, the process of approval reimbursement includes the following fixed sub-processes: the application submitted by the reimburser, the first review of the department manager A, the second review of the chief deputy B, the examination and approval of the chief manager C and the examination and approval of the financial affairs D are fixed, namely, the processors on each processing node are fixed.
With diversification and complication of work order contents, for example, work orders for analyzing and processing safety entity data, work orders for auditing safety entity data safety, and the like are not only simply approved, but also fixed personnel are still adopted to process work order nodes in such a scene, so that the work order processing efficiency and accuracy are low, and flexible control of the work orders cannot be realized.
Therefore, it is an urgent technical problem in the art to provide a work order allocation scheduling method, apparatus, computer device and storage medium to implement flexible allocation of processing nodes in a work order processing flow.
Disclosure of Invention
The present invention is directed to a method, an apparatus, a computer device, and a storage medium for allocating and scheduling work orders, which are used to solve the above technical problems in the prior art.
In one aspect, the present invention provides a work order allocation scheduling method for achieving the above objectives.
The work order distribution scheduling method comprises the following steps: receiving a to-be-processed work order submitted by a client; calculating the work order requirement evaluation parameter of the current processing node according to the information of the work order to be processed; acquiring a historical work order processing log; extracting processing information of a processor from the historical work order processing log; calculating a processor capacity evaluation parameter according to the processing information of the processor; determining a first matching degree of a processor and the work order to be processed according to the processor capacity evaluation parameter and the work order requirement evaluation parameter; determining a target processor of the work order to be processed in a plurality of processors according to the first matching degree; and distributing the current processing node of the work order to be processed to the target processor.
Further, the information of the work order to be processed includes priority, node type, submission time, waiting time, deadline and return times, the work order requirement evaluation parameter includes importance, difficulty and urgency, and the step of calculating the work order requirement evaluation parameter of the preprocessing node according to the information of the work order to be processed includes: determining the importance according to the priority, wherein the higher the priority, the higher the importance; determining the difficulty level according to the node type, wherein the difficulty levels corresponding to different node types are different; and determining the urgency degree according to the submission time, the waiting time, the deadline and/or the return times, wherein the earlier the submission time, the longer the waiting time, the shorter the deadline and the more the return times, the higher the urgency degree.
Further, the processing information of the processor includes a professional level, a professional type, processed units and processed error units, the processor capacity evaluation parameter includes processing capacity, processing efficiency and error rate, and the step of calculating the processor capacity evaluation parameter based on the processing information includes: determining the processing capacity according to the professional level and the professional type, wherein the higher the processing capacity is, the different professional types have different corresponding processing capacities; determining the processing efficiency according to the processed single quantity and the duration corresponding to the historical work order processing log; determining the error rate based on the processed singles and the singles of processing errors.
Further, the work order to be processed is a work order for processing secure entity data, the information of the work order to be processed includes a virus tag and secure entity data information, the secure entity data information includes an identifier of the secure entity data, a virus group, a keyword, and a security type, and the method further includes: extracting personnel labels of a processor and safety entity data information of the processed historical work order from the historical work order processing log; determining a second matching degree of the processor and the work order to be processed according to the safety entity data information of the historical work order processed by the processor and the safety entity data information of the work order to be processed; determining a third matching degree of the processor and the work order to be processed according to the virus label and the personnel label; wherein the step of determining a target handler of the to-be-processed work order among the plurality of handlers according to the first matching degree comprises: calculating the overall matching degree of the processor and the work order to be processed according to the first matching degree, the second matching degree and the third matching degree; and determining a target processor of the work order to be processed in a plurality of processors according to the overall matching degree.
Further, the overall matching degree S of the processor and the work order to be processed is calculated by adopting the following formula: b1＝A11*K1+(A12+A22)*K2+(A13+A33)*K3，S＝B1*L1+B2*L2+B3L3, wherein A11For the processing capacity to satisfy the value of the difficulty level, A12For the processing power to satisfy the value of the importance, A22For the error rate to satisfy the value of the importance, A13For the processing capacity to satisfy the value of urgency, A33For the error rate to satisfy the value of urgency, B1Is the first degree of matching, B2Is the second degree of matching, B3For the second degree of matching, K1, K2, K3, L1, L2, and L3 are all weights.
Further, the method further comprises: extracting the same type of work order nodes which are processed by the target processor and have the same type as the current node of the work order to be processed from the historical work order processing log, wherein the same type of work order nodes have the same work order requirement evaluation parameters as the current node of the work order to be processed; calculating the average time length of the same type of work single nodes; and sending the average duration to a client submitting the work order to be processed.
Further, when the work order to be processed has a next processing node, the method further comprises: and extracting a cooperative processor with the highest cooperation degree with the target processor from the historical work order processing log so as to distribute the next processing node of the work order to be processed to the cooperative processor.
In one aspect, the present invention provides a work order allocation scheduling apparatus for achieving the above object.
The work order distribution scheduling device comprises: the receiving module is used for receiving the to-be-processed work order submitted by the client; the first calculation module is used for calculating the evaluation parameters required by the work order of the current processing node according to the information of the work order to be processed; the acquisition module is used for acquiring a historical work order processing log; the extraction module is used for extracting the processing information of the processor from the historical work order processing log; the second calculation module is used for calculating a processor capacity evaluation parameter according to the processing information of the processor; the first determining module is used for determining a first matching degree of the processor and the work order to be processed according to the processor capacity evaluation parameter and the work order requirement evaluation parameter; the second determining module is used for determining a target processor of the work order to be processed in a plurality of processors according to the first matching degree; and the distribution module is used for distributing the current processing node of the work order to be processed to the target processor.
To achieve the above object, the present invention also provides a computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the steps of the above method when executing the computer program.
To achieve the above object, the present invention also provides a computer-readable storage medium having stored thereon a computer program which, when being executed by a processor, carries out the steps of the above method.
The invention provides a work order distribution scheduling method, a device, a computer device and a storage medium, when distributing the current processing node of the work order to be processed to a processor, the current processing node is not fixed to a certain processor, but the work order requirement evaluation parameter of the current processing node is calculated according to the information of the work order to be processed, the processing requirement of the current processing node is reflected by the work order requirement evaluation parameter, in addition, a historical work order processing log is obtained, the processing information of the processor is extracted from the historical work order processing log, the capability evaluation parameter of the processor is calculated according to the processing information, the capability evaluation parameter of the processor reflecting the capability of the processor is obtained by processing the actual historical information of the work order, then the first matching degree of the processor and the work order to be processed is determined according to the capability evaluation parameter of the processor and the work order requirement evaluation parameter, when the target processor of the work order to be processed is determined, and determining in the plurality of processors according to the first matching degree, so as to distribute the current processing node of the work order to be processed to the target processor. It can be seen that, with the work order allocation scheduling method provided in this embodiment, the processing node requirement of the work order is abstracted using the work order requirement evaluation parameter, the handler capability is abstracted using the handler capability evaluation parameter, and then the target handler of the current processing node is determined using the matching degree of the work order requirement evaluation parameter and the handler capability evaluation parameter.
Drawings
Fig. 1 is a flowchart of a method for allocating and scheduling work orders according to an embodiment of the present invention;
fig. 2 is a block diagram of a work order allocation scheduling apparatus according to a second embodiment of the present invention;
fig. 3 is a hardware structure diagram of a computer device according to a third embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The invention provides a work order distribution scheduling method, a work order distribution scheduling device, computer equipment and a storage medium. In the work order distribution and scheduling method, after a to-be-processed work order submitted by a client is received, work order requirement evaluation parameters of a current processing node are calculated according to the information of the to-be-processed work order, and the requirement of the current processing node of the to-be-processed work order is identified through the work order requirement evaluation parameters; in addition, a historical work order processing log is obtained, wherein the historical work order processing log comprises the relevant information of the processed work orders, the processing information of a processor is extracted from the historical work order processing log, the capability evaluation parameter of the processor is calculated according to the processing information of the processor, so that the capability evaluation parameter of the processor can be determined through the real historical processing information of the processor, the capability condition of the processor is identified, finally, the matching degree of the processor and the work order to be processed is determined according to the capability evaluation parameter of the processor and the requirement evaluation parameter of the work order, the target processor of the work order to be processed is determined in a plurality of processors according to the matching degree, and the current processing node of the work order to be processed is distributed to the target processor, therefore, the distribution scheduling method of the work order provided by the invention enables the processor of the processing node of the work order to dynamically change, the processing nodes are flexibly distributed, namely, the processing nodes are dynamically distributed to proper processors according to the matching degree of the processing node requirements and the processor capacity, and the efficiency and the accuracy of work order processing are improved.
Specific embodiments of the work order allocation scheduling method, apparatus, computer device and storage medium provided by the present invention will be described in detail below.
Example one
The embodiment of the invention provides a work order distribution and scheduling method, which can dynamically change the processing flow of a work order and dynamically distribute processing nodes to proper processors. Specifically, fig. 1 is a flowchart of a work order allocation scheduling method according to an embodiment of the present invention, and as shown in fig. 1, the work order allocation scheduling method according to the embodiment includes steps S101 to S108.
Step S101: and receiving the work order to be processed submitted by the client.
The work order to be processed may include a plurality of processing nodes, and all the processing nodes and the sequence constitute a processing flow of the work order to be processed.
Step S102: and calculating the work order requirement evaluation parameters of the current processing node according to the information of the work order to be processed.
Optionally, the information of the work order to be processed includes priority, node type, submission time, waiting time, deadline, return times, and the like, and for the work order for processing the secure entity data, the information of the work order to be processed further includes a virus tag and secure entity data information, and the secure entity data information includes an identifier of the secure entity data, a virus group, a keyword, a security type, and the like.
The work order requirement evaluation parameters can quantitatively represent the required processing requirements of the current node of the work order to be processed, and optionally, the work order requirement evaluation parameters include importance, difficulty and urgency.
Further optionally, in step S102, when calculating the work order requirement evaluation parameter according to the information of the work order to be processed, the specifically executed step includes:
the importance level is determined according to the priority level, wherein the higher the priority level is, the higher the importance level is, optionally, different importance levels are set corresponding to different priority levels, for example, the importance level corresponding to the first priority level is 100%, the importance level corresponding to the second priority level is 80%, the importance level corresponding to the third priority level is 60%, and the like.
Determining difficulty degrees according to node types, wherein the difficulty degrees corresponding to different node types are different, optionally, the node types include modified nodes, analyzed nodes, approval nodes and the like, and the difficulty degrees respectively correspond to 50%, 70% and 90%.
The urgency is determined based on the commit time, wait time, deadline, and/or number of retirements, where the earlier the commit time, the longer between waits, the shorter the deadline, the more retirements, the higher the urgency, for example:
urgency (-presentation time) a1+ wait time a2+ (-time) a3+ number of retractions a4,
wherein, a1, a2, a3 and a4 are weights.
Step S103: and acquiring a historical work order processing log.
Wherein, in the process of processing the work order, the work order processing log is recorded. The work order processing log records information of the work order, information of the processor, information of the processing result, and the like. When processing a work order, a processing log of a historical work order may be obtained.
Step S104: the processing information of the processor is extracted from the history work order processing log.
Optionally, the historical work order processed by the same processor is queried in the historical work order processing log, and the processing information of the processor is obtained through the processing history of the processor, specifically, the processing information of the processor includes a professional level, a professional type, a processed single quantity and a processing error single quantity.
Step S105: a processor capability evaluation parameter is calculated based on the processing information of the processor.
The processor capability assessment parameters can quantitatively characterize the processor's processing capability, optionally including processing capability, processing efficiency, and error rate.
Further optionally, in step S105, when the processor capability evaluation parameter is calculated according to the processing information of the processor, the specifically executed step includes:
and determining the processing capacity according to the professional level and the professional type, wherein the higher the professional level is, the higher the processing capacity is, and the processing capacities corresponding to different professional types are different. For example, if the first ability score x corresponding to the first specialty level is x1, the first ability score x corresponding to the second specialty level is x2, the first ability score x corresponding to the third specialty level is x3, x3> x2> x1, the second ability score y corresponding to professional type a is y1, and the second ability score y corresponding to professional type b is y 2: processing capacity ═ x × b1+ y × b 2.
And determining the processing efficiency according to the processed single quantity and the time length corresponding to the historical work order processing log. For example, if the historical work order processing log is a log of the processing work orders in the previous 30 days, and the number of the processed work orders of a certain processor is 60 in the previous 30 days, the processing efficiency of the processor is calculated to be 2 pieces per day.
The error rate is determined based on the processed single quantity and the single quantity of the processing error, for example, in the acquired historical work order processing log, if the processed single quantity of a certain processor is 50 pieces and the single quantity of the processing error is 5 pieces, the error rate of the certain processor is calculated to be 10%.
Step S106: and determining a first matching degree of the processor and the work order to be processed according to the processor capacity evaluation parameter and the work order requirement evaluation parameter.
Optionally, the processor capability evaluation parameter includes processing capability, processing efficiency and error rate, and the work order requirement evaluation parameter includes importance, difficulty and urgency, where a first matching degree between the processor and the work order to be processed is determined according to whether the processing capability satisfies the importance, whether the processing capability and the processing efficiency satisfy the urgency, and whether the processing capability and the error rate satisfy the importance, specifically, a first matching degree between a processor with large processing capability and a work order to be processed with large difficulty is large, a first matching degree between a processor with large processing capability and high processing efficiency and a work order to be processed with high urgency is large, and a first matching degree between a processor with large processing capability and low error rate and a work order to be processed with high importance is large.
Step S107: and determining a target processor of the work order to be processed in the plurality of processors according to the first matching degree.
Alternatively, the to-be-processed person having the largest first matching degree may be selected among the plurality of processing persons as the target processing person. Optionally, the target handler of the work order to be processed may also be determined in combination with the first matching degree and other conditions, for example, the target handler of the work order to be processed may be determined in combination with the number of work orders that the handler has assigned, specifically, if the handler with the first matching degree ranked in the top 20% and the least number of assigned work orders is determined as the target handler, the assignment of too many work orders to the same handler is avoided; for another example, the target handler of the work order to be processed is determined in combination with the work state of the handler, specifically, if the handler in the working state with the first matching degree closest to the first matching degree is determined as the target handler, the work order is prevented from being allocated to the handler in the rest state.
Step S108: and distributing the current processing node of the work order to be processed to the target processor.
In the method for dispatching work order assignment provided in this embodiment, when allocating the current processing node of the work order to be processed to the processor, the current processing node is not fixed to a certain processor, but the work order requirement evaluation parameter of the current processing node is calculated according to the information of the work order to be processed, the processing requirement of the current processing node is reflected by the work order requirement evaluation parameter, furthermore, a historical work order processing log is obtained, the processing information of the processor is extracted from the historical work order processing log, the processor capability evaluation parameter is calculated according to the processing information, the processor capability evaluation parameter reflecting the capability of the processor is obtained by processing the actual historical information of the work order, then the first matching degree between the processor and the work order to be processed is determined according to the processor capability evaluation parameter and the work order requirement evaluation parameter, so that when the target processor of the work order to be processed is determined, the determination is performed among the plurality of processors according to the first matching degree, thereby allocating the current processing node of the work order to be processed to the target processor. It can be seen that, with the work order allocation scheduling method provided in this embodiment, the processing node requirement of the work order is abstracted using the work order requirement evaluation parameter, the handler capability is abstracted using the handler capability evaluation parameter, and then the target handler of the current processing node is determined using the matching degree of the work order requirement evaluation parameter and the handler capability evaluation parameter.
Optionally, in an embodiment, the to-be-processed work order is a work order for processing the secure entity data, the information of the to-be-processed work order includes a virus tag and secure entity data information, and the secure entity data information includes an identifier of the secure entity data, a virus group, a keyword, and a security type. The virus tags include epidemic virus, Trojan horse virus, colliery virus and the like. A security entity database may be provided for storing the security entity data, and the identifier of the security entity data may be an id of the security entity data in the security entity database. The keywords may be keywords input by the user when submitting the work order to be processed. The work order distribution scheduling method further comprises the following steps: extracting personnel tags of a processor and safety entity data information of the processed historical work order from a historical work order processing log, wherein the personnel tags can comprise epidemic virus experts, Trojan virus experts, database collision virus experts and the like; and determining a second matching degree of the processor and the work order to be processed according to the safety entity data information of the historical work order processed by the processor and the safety entity data information of the work order to be processed, and determining a third matching degree of the processor and the work order to be processed according to the virus tag and the personnel tag.
Based on this, the step of determining the target processor of the work order to be processed among the plurality of processors according to the first matching degree includes: and calculating the overall matching degree of the processor and the work order to be processed according to the first matching degree, the second matching degree and the third matching degree. And determining a target processor of the work order to be processed in the plurality of processors according to the overall matching degree.
By adopting the work order allocation scheduling method provided by the embodiment, when allocating the work order nodes, the second matching degree and the third matching degree are considered at the same time, wherein the second matching degree reflects the similarity between the safety entity data in the historical work order processed by the processor and the safety entity data of the work order to be processed, and the third matching degree reflects the consistency between the processor label and the virus label, so that the current node of the work order to be processed can be allocated to the processor which has processed the similar safety entity data, and the current node of the work order to be processed can be allocated to the processor which is more suitable for the virus label of the work order.
Further optionally, in an embodiment, the overall matching degree S between the processor and the work order to be processed is calculated by using the following formula: b is1＝A11*K1+(A12+A22)*K2+(A13+A33)*K3，S＝B1*L1+B2*L2+B3L3, wherein A11To satisfy the processing ability with respect to the value of the degree of difficulty, A12To satisfy the value of importance for the processing power, A22For values where the error rate satisfies the importance, A13To meet the value of urgency for processing capacity, A33For the error rate to satisfy the value of urgency, B1Is a first degree of matching, B2Is a second degree of matching, B3For the second degree of matching, K1, K2, K3, L1, L2, and L3 are all weights.
Optionally, in an embodiment, the allocation scheduling method further includes: extracting the same type of work order nodes which are processed by a target processor and have the same type as the current node of the work order to be processed from a historical work order processing log, wherein the same type of work order nodes have the same work order requirement evaluation parameters as the current node of the work order to be processed; calculating the average time length of the same type of work single nodes; and sending the average time length to a client for submitting the work order to be processed.
By adopting the work order allocation scheduling method provided by the embodiment, the average time length of the work order nodes of the same type as the current processing node is sent to the client side for submitting the work order to be processed, so that a user can predict the processing time length of the current processing node.
Optionally, in an embodiment, when the to-be-processed work order has a next processing node, the allocation scheduling method further includes: and extracting the cooperative processor with the highest cooperation degree with the target processor from the historical work order processing log so as to distribute the work order to be processed to the cooperative processors when the work order reaches the next processing node. The cooperation degree can be determined by the number and the accuracy of the same work orders processed by the two processors, and the larger the number of the same work orders processed is, the higher the accuracy is, and the higher the cooperation degree is.
By adopting the work order allocation scheduling method provided in this embodiment, after the target handler of the current processing node is determined, the cooperative handler with the highest degree of cooperation with the target handler is further determined, and the next processing node is allocated to the cooperative handler, thereby improving the processing efficiency of the entire work order.
Example two
Corresponding to the first embodiment, the second embodiment of the present invention provides a work order allocation scheduling apparatus, and reference may be made to the above embodiments for details of some technical features and corresponding technical effects. Fig. 2 is a block diagram of a work order allocation scheduling apparatus according to a second embodiment of the present invention, and as shown in fig. 2, the apparatus includes a receiving module 201, a first calculating module 202, an obtaining module 203, a first extracting module 204, a second calculating module 205, a first determining module 206, a second determining module 207, and an allocating module 208.
The receiving module 201 is configured to receive a work order to be processed submitted by a client; the first calculation module 202 is configured to calculate a work order requirement evaluation parameter of a current processing node according to the information of the work order to be processed; the obtaining module 203 is used for obtaining a historical work order processing log; the first extraction module 204 is used for extracting the processing information of the processor from the historical work order processing log; the second calculation module 205 is used for calculating a processor capability evaluation parameter according to the processing information of the processor; the first determining module 206 is configured to determine a first matching degree between a handler and the work order to be processed according to the handler capability evaluation parameter and the work order requirement evaluation parameter; the second determining module 207 is configured to determine a target handler of the to-be-processed work order among the plurality of handlers according to the first matching degree; the assignment module 208 is configured to assign a current processing node of the work order to be processed to the target processor.
Optionally, in an embodiment, the information of the work order to be processed includes a priority, a node type, a submission time, a waiting time, a deadline, and a number of return times, the work order requirement evaluation parameter includes an importance degree, a difficulty degree, and an urgency degree, and when the first calculation module 202 calculates the work order requirement evaluation parameter according to the information of the work order to be processed, the specifically executed steps include: the importance is determined according to priority, wherein the higher the priority, the higher the importance. And determining the difficulty level according to the node type, wherein the difficulty levels corresponding to different node types are different. The urgency level is determined based on the commit time, wait time, deadline, and/or number of retirements, wherein the earlier the commit time, the longer between waits, the shorter the deadline, the more retirements, the higher the urgency level.
Optionally, in an embodiment, the processing information of the processor includes a professional level, a professional type, a processed unit amount and a unit amount of processing error, the processor capability evaluation parameter includes processing capability, processing efficiency and error rate, and the step performed when the second calculation module 205 calculates the processor capability evaluation parameter according to the processing information includes: and determining the processing capacity according to the professional level and the professional type, wherein the higher the processing capacity is, the different processing capacities corresponding to different professional types are different. And determining the processing efficiency according to the processed single quantity and the time length corresponding to the historical work order processing log. An error rate is determined based on the processed singles and the singles that processed the error.
Optionally, in an embodiment, the to-be-processed work order is a work order for processing the secure entity data, the information of the to-be-processed work order includes a virus tag and secure entity data information, and the secure entity data information includes an identifier of the secure entity data, a virus group, a keyword, and a security type, and the apparatus further includes: the system comprises a second extraction module, a third determination module and a fourth determination module, wherein the second extraction module is used for extracting the personnel label of the processor and the safety entity data information of the processed historical work order from the historical work order processing log, the third determination module is used for determining the second matching degree of the processor and the work order to be processed according to the safety entity data information of the historical work order processed by the processor and the safety entity data information of the work order to be processed, and the fourth determination module is used for determining the third matching degree of the processor and the work order to be processed according to the virus label and the personnel label. The second determining module 207 is further configured to calculate an overall matching degree between the processor and the work order to be processed according to the first matching degree, the second matching degree and the third matching degree when determining the target processor of the work order to be processed, and then determine the target processor of the work order to be processed among the multiple processors according to the overall matching degree.
Optionally, in an embodiment, the overall matching degree S between the handler and the work order to be processed is calculated by using the following formula: b is1＝A11*K1+(A12+A22)*K2+(A13+A33)*K3，S＝B1*L1+B2*L2+B3L3, wherein A11To satisfy the processing ability with respect to the value of the degree of difficulty, A12To satisfy the value of importance for the processing power, A22To satisfy the value of importance for the error rate, A13To meet the value of urgency for processing capacity, A33For the error rate to satisfy the value of urgency, B1Is a first degree of matching, B2Is a second degree of matching, B3For the second degree of matching, K1, K2, K3, L1, L2, and L3 are all weights.
Optionally, in an embodiment, the apparatus further includes: the system comprises a third extraction module, a calculation module and a sending module, wherein the third extraction module is used for extracting a work order which is processed by a target processor and has the same type as a work order to be processed from a historical work order processing log, the work order which has the same type as the work order to be processed has the same evaluation parameters as the work order of the work order to be processed, the calculation module is used for calculating the average duration of the work orders which have the same type, and the sending module is used for sending the average duration to a client side for submitting the work order to be processed.
Optionally, in an embodiment, when the work order to be processed has a next processing node, the apparatus further includes: and the fourth extraction module is used for extracting the cooperative processor with the highest cooperation degree with the target processor from the historical work order processing log so as to enable the work order to be processed to be distributed to the cooperative processors when reaching the next processing node.
EXAMPLE III
The third embodiment further provides a computer device, such as a smart phone, a tablet computer, a notebook computer, a desktop computer, a rack server, a blade server, a tower server or a rack server (including an independent server or a server cluster composed of multiple servers) capable of executing programs, and the like. As shown in fig. 3, the computer device 01 of the present embodiment at least includes but is not limited to: a memory 011 and a processor 012, which are communicatively connected to each other via a system bus, as shown in fig. 3. It is noted that fig. 3 only shows the computer device 01 having the component memory 011 and the processor 012, but it is to be understood that not all of the shown components are required to be implemented, and that more or fewer components may be implemented instead.
In this embodiment, the memory 011 (i.e., a readable storage medium) includes a flash memory, a hard disk, a multimedia card, a card-type memory (e.g., SD or DX memory, etc.), a Random Access Memory (RAM), a Static Random Access Memory (SRAM), a read-only memory (ROM), an electrically erasable programmable read-only memory (EEPROM), a programmable read-only memory (PROM), a magnetic memory, a magnetic disk, an optical disk, and the like. In some embodiments, the storage 011 can be an internal storage unit of the computer device 01, such as a hard disk or a memory of the computer device 01. In other embodiments, the memory 011 can also be an external storage device of the computer device 01, such as a plug-in hard disk, Smart Media Card (SMC), Secure Digital (SD) Card, Flash memory Card (Flash Card), etc. provided on the computer device 01. Of course, the memory 011 can also include both internal and external memory units of the computer device 01. In this embodiment, the memory 011 is generally used to store an operating system installed in the computer device 01 and various application software, such as a program code of the work order allocation scheduling apparatus in the second embodiment. Further, the memory 011 can also be used to temporarily store various kinds of data that have been output or are to be output.
The processor 012 may be a Central Processing Unit (CPU), a controller, a microcontroller, a microprocessor, or other data Processing chip in some embodiments. The processor 012 is generally used to control the overall operation of the computer device 01. In this embodiment, the processor 012 is configured to run a program code stored in the memory 011 or process data, for example, a work order allocation scheduling method.
Example four
The present embodiments also provide a computer-readable storage medium, such as a flash memory, a hard disk, a multimedia card, a card-type memory (e.g., SD or DX memory, etc.), a Random Access Memory (RAM), a Static Random Access Memory (SRAM), a read-only memory (ROM), an electrically erasable programmable read-only memory (EEPROM), a programmable read-only memory (PROM), a magnetic memory, a magnetic disk, an optical disk, a server, an App application store, etc., on which a computer program is stored, which when executed by a processor, implements corresponding functions. The computer-readable storage medium of this embodiment is used to store a work order allocation scheduling apparatus, and when executed by a processor, the method for allocating and scheduling a work order of the first embodiment is implemented.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
The above-mentioned serial numbers of the embodiments of the present invention are only for description, and do not represent the advantages and disadvantages of the embodiments.
Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner.
The above description is only a preferred embodiment of the present invention, and is not intended to limit the scope of the present invention, and all equivalent structures or equivalent processes performed by the present invention or directly or indirectly applied to other related technical fields are also included in the scope of the present invention.
Claims (9)
1. A work order distribution scheduling method is characterized by comprising the following steps:
receiving a to-be-processed work order submitted by a client, wherein the to-be-processed work order is a work order for processing safety entity data;
calculating the work order requirement evaluation parameter of the current processing node according to the information of the work order to be processed, wherein the information of the work order to be processed comprises a virus label and safety entity data information, and the safety entity data information comprises the identification, virus group, key words and safety type of the safety entity data;
acquiring a historical work order processing log;
extracting processing information of a processor from the historical work order processing log;
calculating a processor capacity evaluation parameter according to the processing information of the processor;
determining a first matching degree of a processor and the work order to be processed according to the processor capacity evaluation parameter and the work order requirement evaluation parameter;
extracting personnel labels of a processor and safety entity data information of the processed historical work orders from the historical work order processing log;
determining a second matching degree of the processor and the work order to be processed according to the safety entity data information of the historical work order processed by the processor and the safety entity data information of the work order to be processed;
determining a third matching degree of the processor and the work order to be processed according to the virus label and the personnel label;
calculating the overall matching degree of the processor and the work order to be processed according to the first matching degree, the second matching degree and the third matching degree;
determining a target processor of the work order to be processed in a plurality of processors according to the overall matching degree; and
and distributing the current processing node of the work order to be processed to the target processor.
2. The method according to claim 1, wherein the information of the work order to be processed includes priority, node type, submission time, waiting time, deadline, and number of returns, the evaluation parameters of the work order include importance, difficulty, and urgency, and the step of calculating the evaluation parameters of the work order of the currently processed node according to the information of the work order to be processed includes:
determining the importance according to the priority, wherein the higher the priority is, the higher the importance is;
determining the difficulty level according to the node type, wherein the difficulty levels corresponding to different node types are different;
and determining the urgency degree according to the submission time, the waiting time, the deadline and/or the return times, wherein the earlier the submission time, the longer the waiting time, the shorter the deadline, the more the return times, and the higher the urgency degree.
3. The method according to claim 2, wherein the processing information of the processor includes a professional level, a professional type, a processed unit amount, and a unit amount of processing error, the processor capability evaluation parameter includes a processing capability, a processing efficiency, and an error rate, and the step of calculating the processor capability evaluation parameter based on the processing information includes:
determining the processing capacity according to the professional level and the professional type, wherein the higher the professional level is, the higher the processing capacity is, and the different professional types have different corresponding processing capacities;
determining the processing efficiency according to the processed single quantity and the duration corresponding to the historical work order processing log;
determining the error rate based on the processed singles and the singles of processing errors.
4. The work order distribution scheduling method of claim 3, wherein the overall matching degree S between the processor and the work order to be processed is calculated by adopting the following formula:
B1＝A11*K1+(A12+A22)*K2+(A13+A33)*K3
S＝B1*L1+B2*L2+B3*L3
wherein A is11For the processing power to satisfy the value of the difficulty level, A12For the processing power to satisfy the value of the importance, A22For the error rate to satisfy the value of the importance, A13For the processing capacity to satisfy the value of urgency, A33For the error rate to satisfy the value of urgency, B1Is the first degree of matching, B2Is the second degree of matching, B3For the second degree of matching, K1, K2, K3, L1, L2, and L3 are all weights.
5. The method of claim 1, further comprising:
extracting the same type of work order nodes which are processed by the target processor and have the same type as the current node of the work order to be processed from the historical work order processing log, wherein the same type of work order nodes have the same work order requirement evaluation parameters as the current node of the work order to be processed;
calculating the average time length of the same type of work single nodes;
and sending the average duration to a client submitting the work order to be processed.
6. The method of claim 1, wherein when the work order to be processed has a next processing node, the method further comprises:
and extracting the cooperative processor with the highest cooperation degree with the target processor from the historical work order processing log so as to distribute the next processing node of the work order to be processed to the cooperative processor.
7. A work order distribution scheduling device, comprising:
the system comprises a receiving module, a processing module and a processing module, wherein the receiving module is used for receiving a to-be-processed work order submitted by a client, and the to-be-processed work order is a work order for processing safety entity data;
the first calculation module is used for calculating the work order requirement evaluation parameter of the current processing node according to the information of the work order to be processed, wherein the information of the work order to be processed comprises a virus label and safety entity data information, and the safety entity data information comprises an identifier, a virus group, a keyword and a safety type of the safety entity data;
the acquisition module is used for acquiring a historical work order processing log;
the extraction module is used for extracting the processing information of the processor from the historical work order processing log;
the second calculation module is used for calculating a processor capacity evaluation parameter according to the processing information of the processor;
the first determining module is used for determining a first matching degree of the processor and the work order to be processed according to the processor capacity evaluation parameter and the work order requirement evaluation parameter;
the second extraction module is used for extracting the personnel label of the processor and the safety entity data information of the processed historical work order from the historical work order processing log;
a third determining module, configured to determine a second matching degree between the processor and the work order to be processed according to the safety entity data information of the historical work order processed by the processor and the safety entity data information of the work order to be processed;
a fourth determining module, configured to determine a third matching degree between the handler and the work order to be processed according to the virus tag and the staff tag; the second determining module is used for calculating the overall matching degree of the processor and the work order to be processed according to the first matching degree, the second matching degree and the third matching degree, and determining a target processor of the work order to be processed in a plurality of processors according to the overall matching degree; and
and the distribution module is used for distributing the current processing node of the work order to be processed to the target processor.
8. A computer arrangement comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the steps of the method of any of claims 1 to 6 when executing the computer program.
9. A computer-readable storage medium having stored thereon a computer program, characterized in that: the computer program when executed by a processor implements the steps of the method of any one of claims 1 to 6.
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| CN114493376B (en) * | 2022-04-02 | 2022-06-28 | 广州平云小匠科技有限公司 | Task scheduling management method and system based on work order data |
Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103699969A (en) * | 2013-12-20 | 2014-04-02 | 北京大唐融合通信技术有限公司 | Work order distributing method and device |
| CN103778005A (en) * | 2014-01-27 | 2014-05-07 | 北京网秦天下科技有限公司 | Automatic task allocation method and device |
| CN105354762A (en) * | 2015-11-11 | 2016-02-24 | 国网山东省电力公司电力科学研究院 | Work order identification and distribution system and method of electricity customer service business |
| CN106682743A (en) * | 2016-12-15 | 2017-05-17 | 南京南瑞信息通信科技有限公司 | Operation and maintenance work order scheduling management method and system in electric power telecommunication field |
| CN106910007A (en) * | 2017-01-18 | 2017-06-30 | 上海爱韦讯信息技术有限公司 | The method and system of automatic distribution examination task |
| CN107943697A (en) * | 2017-11-23 | 2018-04-20 | 中国平安人寿保险股份有限公司 | Problem distribution method, device, system, server and computer-readable storage medium |
| CN109767289A (en) * | 2018-12-15 | 2019-05-17 | 深圳壹账通智能科技有限公司 | Order smart allocation method, apparatus, computer equipment and storage medium |
| CN109993542A (en) * | 2017-12-28 | 2019-07-09 | 青岛日日顺电器服务有限公司 | A kind of method, apparatus, server and storage medium for assigning work order |
| CN110264036A (en) * | 2019-05-10 | 2019-09-20 | 阿里巴巴集团控股有限公司 | Method for scheduling task and device |
-
2019
- 2019-09-27 CN CN201910923085.3A patent/CN110751376B/en active Active
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103699969A (en) * | 2013-12-20 | 2014-04-02 | 北京大唐融合通信技术有限公司 | Work order distributing method and device |
| CN103778005A (en) * | 2014-01-27 | 2014-05-07 | 北京网秦天下科技有限公司 | Automatic task allocation method and device |
| CN105354762A (en) * | 2015-11-11 | 2016-02-24 | 国网山东省电力公司电力科学研究院 | Work order identification and distribution system and method of electricity customer service business |
| CN106682743A (en) * | 2016-12-15 | 2017-05-17 | 南京南瑞信息通信科技有限公司 | Operation and maintenance work order scheduling management method and system in electric power telecommunication field |
| CN106910007A (en) * | 2017-01-18 | 2017-06-30 | 上海爱韦讯信息技术有限公司 | The method and system of automatic distribution examination task |
| CN107943697A (en) * | 2017-11-23 | 2018-04-20 | 中国平安人寿保险股份有限公司 | Problem distribution method, device, system, server and computer-readable storage medium |
| CN109993542A (en) * | 2017-12-28 | 2019-07-09 | 青岛日日顺电器服务有限公司 | A kind of method, apparatus, server and storage medium for assigning work order |
| CN109767289A (en) * | 2018-12-15 | 2019-05-17 | 深圳壹账通智能科技有限公司 | Order smart allocation method, apparatus, computer equipment and storage medium |
| CN110264036A (en) * | 2019-05-10 | 2019-09-20 | 阿里巴巴集团控股有限公司 | Method for scheduling task and device |
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