CN112766719A - Task allocation method and device - Google Patents
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Abstract
The invention provides a task allocation method and a task allocation device, and belongs to the technical field of cloud computing. The task allocation method comprises the following steps: acquiring a label factor, labels of tasks to be distributed, labels of n IDs to be matched and maturity cardinality of the n IDs to be matched; wherein n is an integer greater than 1; determining decision factors of the n IDs to be matched according to the label factors, the labels of the tasks to be distributed, the labels of the n IDs to be matched and the maturity cardinality of the n IDs to be matched; and distributing the tasks to be distributed to the IDs to be matched corresponding to the minimum decision factors in the n decision factors. The invention can realize automatic distribution of tasks, reasonably arrange production, improve task completion efficiency and reduce project completion time and project cost.
Description
Technical Field
The invention relates to the technical field of cloud computing, in particular to a task allocation method and a task allocation device.
Background
With the continuous development of information technology and internet finance, in order to meet the rapidly changing requirements, project research and development generally turn to an agile research and development mode, requirements are organized according to required dimensions, clarification, coding design, test acceptance and product delivery are achieved, and the delivery of the requirements is achieved in a short time. In current project management practice, a requirement is decomposed into a plurality of tasks, each task comprises three stages of design, coding and test, and the tasks are finally distributed to team design, coding and test personnel to complete. In consideration of the sequentiality of task phases and the existence of dependency relationships among tasks, the task allocation has certain time sequence, so that the task allocation in the field of software development project management is a scheduling problem in essence at present.
In order to complete all the requirements within a specified time, the industry typically determines the scheduling time for each requirement and the designers, coders, and testers to complete the task by means of manual scheduling. The manual production scheduling method mainly has the problems that task scheduling is based on experience, task completion efficiency is low, and project cost is too high.
Disclosure of Invention
The embodiment of the invention mainly aims to provide a task allocation method and a task allocation device, so as to realize automatic allocation of tasks, reasonably arrange production, improve task completion efficiency and reduce project completion time and project cost.
In order to achieve the above object, an embodiment of the present invention provides a task allocation method, including:
acquiring a label factor, labels of tasks to be distributed, labels of n IDs to be matched and maturity cardinality of the n IDs to be matched; wherein n is an integer greater than 1;
determining decision factors of the n IDs to be matched according to the label factors, the labels of the tasks to be distributed, the labels of the n IDs to be matched and the maturity cardinality of the n IDs to be matched;
and distributing the tasks to be distributed to the IDs to be matched corresponding to the minimum decision factors in the n decision factors.
An embodiment of the present invention further provides a task allocation apparatus, including:
the acquisition module is used for acquiring the label factor, the label of the task to be distributed, the labels of the n IDs to be matched and the maturity cardinality of the n IDs to be matched; wherein n is an integer greater than 1;
the decision factor determining module is used for determining n decision factors of the IDs to be matched according to the label factors, the labels of the tasks to be distributed, the labels of the n IDs to be matched and the maturity cardinality of the n IDs to be matched;
and the task distribution module is used for distributing the tasks to be distributed to the IDs to be matched corresponding to the minimum decision factors in the n decision factors.
The embodiment of the present invention further provides a computer device, which includes a memory, a processor, and a computer program stored in the memory and running on the processor, and the processor implements the steps of the task allocation method when executing the computer program.
Embodiments of the present invention further provide a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the steps of the task allocation method.
The task allocation method and device provided by the embodiment of the invention are used for obtaining the label factor, the label of the task to be allocated, the label of the ID to be matched and the maturity cardinal number to determine the decision factor, and allocating the task to be allocated to the ID to be matched corresponding to the minimum decision factor, so that the automatic allocation of the task is realized, the production is reasonably arranged, the task completion efficiency is improved, and the project completion time and the project cost are reduced.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained based on these drawings without creative efforts.
FIG. 1 is a flow chart of a task assignment method in an embodiment of the invention;
FIG. 2 is a flow chart of determining tasks to be assigned in an embodiment of the present invention;
FIG. 3 is a flow chart of determining an ID to be matched in an embodiment of the present invention;
FIG. 4 is a block diagram showing the construction of a task assigning apparatus according to an embodiment of the present invention;
FIG. 5 is a block diagram showing the construction of a task assigning apparatus according to another embodiment of the present invention;
FIG. 6 is a block diagram of a user input module in another embodiment of the invention;
FIG. 7 is a block diagram of a task division module according to another embodiment of the present invention;
FIG. 8 is a block diagram of a result output module according to another embodiment of the present invention;
FIG. 9 is a functional flow diagram of the modules in FIG. 5;
fig. 10 is a block diagram of a computer device in the embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. 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.
As will be appreciated by one skilled in the art, embodiments of the present invention may be embodied as a system, apparatus, device, method, or computer program product. Accordingly, the present disclosure may be embodied in the form of: entirely hardware, entirely software (including firmware, resident software, micro-code, etc.), or a combination of hardware and software.
In view of the fact that task arrangement in the prior art is empirical, task completion efficiency is low, and project cost is too high, the embodiment of the invention provides a task allocation method, which adopts a mode of allocating tasks one by one and greedy selects optimal matching of tasks through decision factors of tasks and personnel IDs; the task allocation and scheduling are carried out through the date dimension according to the reason that no person is free on the day, the automatic allocation of the tasks can be realized, the production is reasonably arranged, the task completion efficiency is improved, and the project completion time and the project cost are reduced. The present invention will be described in detail below with reference to the accompanying drawings.
FIG. 1 is a flowchart of a task allocation method according to an embodiment of the present invention. As shown in fig. 1, the task allocation method includes:
s101: and acquiring the label factor, the label of the task to be distributed, the labels of the n IDs to be matched and the maturity cardinality of the n IDs to be matched.
Wherein n is an integer greater than 1.
TABLE 1
TABLE 2
TABLE 3
Table 1 is a task map, Table 2 is a person map, and Table 3 is a parameter information table. As shown in tables 1-3, the demand items are broken down into sub-entries, each of which is rendered for task allocation and scheduling. Each sub-entry includes a design task, an encoding task, and a test task. The nature of the "subentry" referred to in the present invention is a design task, a coding task or a test task, and each subentry requires arranging personnel of the corresponding type to complete the design, coding or test of the subentry in sequence.
FIG. 2 is a flow chart of determining tasks to be assigned in an embodiment of the present invention. As shown in fig. 2, determining the task to be assigned includes:
s201: and sequencing the tasks according to the task parameters.
In specific implementation, when the current time is earlier than the start time of the demand item corresponding to the task, the task is not sequenced. Since the scheduling of tasks is determined by the currently assigned staff schedule, the earlier the task is assigned, the earlier the completion time is relatively earlier, all other things being equal. However, each requirement item to which the task belongs has a requirement on the ending time, so that the task with the earlier ending time of the requirement item needs to be distributed in advance, namely the priority of the task is highest. Under the condition that the end time of the demand meeting items is the same, some special tasks are appointed to be completed by appointed personnel (including designers, coders and testers) for the reasons of cultivating certain ability of developers and the like, and the priority of the tasks with characteristic requirements is higher in consideration of the fact that the appointed personnel can be saturated early and cannot be acquired later if the tasks cannot be distributed in advance. Besides the priority requirements, the tasks have the attributes of risk, value and the like, the tasks with high risk and high value need to be matched with the personnel with higher maturity preferentially within the range of distributable personnel through the dimensionalities of personnel level, near-three quarterly assessment average value, defect density and the like, and therefore reasonable distribution of resources is guaranteed to the greatest extent. Thus, all tasks may be initially ordered according to the priority requirements described above. Finally, considering that a plurality of tasks have dependency relationships, namely the coding task completion time of the sub-entry to be satisfied is later than the coding task completion time of the dependent sub-entry, if the dependent task is not scheduled, the scheduling task cannot be guaranteed to satisfy the dependency relationships, so that fine adjustment needs to be performed on the basis of initial sequencing, and the dependent task is advanced. The concrete implementation is as follows: if the initial ordering already meets the requirement of the dependency relationship, no additional adjustment is needed, otherwise, the sequence of the dependent tasks of the tasks is advanced to the front bit of the sub-entry.
For example, the end time of the demand item corresponding to the task is the first priority of the sequencing, and the tasks are firstly sequenced from the morning to the evening according to the end time of the demand item; whether the task has a second priority of the designated personnel for sequencing or not is judged, and when the end time of the demand item is the same, the task of the designated personnel is arranged in front of the task of the unspecified personnel; the personnel level is the third priority of the sequencing, and the tasks are sequenced from high to low according to the personnel level corresponding to the tasks; the last three quarter assessment average values are the fourth priority of the sorting, and the tasks are sorted from high to low according to the last three quarter assessment average values corresponding to the tasks; the defect density is the fifth priority of the sequencing, and the tasks are sequenced from low to high according to the defect density corresponding to the tasks; and finally, judging whether the serial numbers of the dependent sub-items of the sequenced tasks meet the dependency relationship: if the dependencies between tasks are task X → task Y → task Z and the ordered tasks are task Z → task X → task Y, then task X and task Y are placed in front of task Z and task X → task Y → task Z instead.
The software development process has a special requirement that design review needs to be completed uniformly within a certain time, so that all tasks need to be sequenced according to an order without design priority before the tasks are distributed every day, and the design finishing time of all the tasks is ensured to meet the requirement of the design finishing time as far as possible.
S202: and determining the task ranked at the first as the task to be distributed.
When tasks and personnel are allocated through a greedy algorithm, scheduling is required. Scheduling is to perform temporal scheduling according to the actual workload under the condition that the time schedule of the personnel meets the upper limit of the fair workload saturation and the actual workload, so as to obtain the starting time and the ending time of the task to determine the idle personnel (idle ID) of the next task, and the results of the personnel scheduling and the task scheduling are temporarily stored in the memory of the computer. Wherein the common allowance workload saturation is equal to the product of the basic common allowance workload saturation and the development test input ratio corresponding to the personnel ID; the upper limit of the actual workload is equal to the product of the upper limit of the basic workload and the development test investment ratio corresponding to the personnel ID.
Fig. 3 is a flowchart of determining an ID to be matched in the embodiment of the present invention. As shown in fig. 3, determining the ID to be matched includes:
s301: and determining the historical ending time corresponding to each ID according to the historical task starting time corresponding to each ID and the historical actual workload corresponding to each ID.
In one embodiment, the method further comprises: and determining the historical actual workload corresponding to each ID according to the historical decision factor of each ID and the fair workload of each historical task.
In one embodiment, the method further comprises: and determining a historical decision factor of each ID according to the label factor, the labels of the historical tasks, the labels of each ID and the maturity base number of each ID.
In specific implementation, determining the historical decision factor of each ID according to the tag factor, the tags of the historical tasks, the tags of each ID, and the maturity base number of each ID includes:
determining the number of matched IDs and the tags of the historical tasks according to the tags of the historical tasks and the tags of the IDs; and determining the historical decision factors of the IDs according to the label factors, the label matching number of the IDs and the historical tasks and the maturity base number of the IDs.
Wherein the historical actual workload is equal to the product of the historical decision factor and the fair workload of the historical task:
the historical actual workload is equal to the common allowable workload of the historical task multiplied by a historical decision factor;
determining a historical decision factor according to the following formula:
DecisionFactor’(i)＝U(i)×V^(W1’(i)+W2’(i))；
wherein DecisionFactor' (i) is a historical decision factor of the ith ID, U (i) is a maturity base number of the ith ID, V is a tag factor, W1' (i) is the number of matching technical labels of the ith ID and the historical task, W2' (i) is the number of matching of the ith ID with the service tag of the historical task. The common allowance workload can be divided into a design common allowance workload, a coding common allowance workload and a testing common allowance workload according to task types.
According to the formula for determining the historical decision factor and the historical actual workload, under the condition that an ID (personnel ID) is not matched with a technical label of a historical task and a service label of the historical task, the time required for completing the historical task corresponding to the ID is the public allowance workload time of the historical task; if the tags are matched, the historical tasks and the IDs are more adaptive, and the time required for actually completing the tasks is correspondingly reduced according to the value of the decision factor, so that the tasks can be completed more quickly and better, and the project cost is reduced as much as possible.
The time required for completing the historical tasks corresponding to the personnel ID can be determined according to the historical actual workload, the fair workload saturation and the actual workload upper limit corresponding to the ID, and then the historical ending time is determined according to the historical task starting time and the time required for completing the historical tasks corresponding to the ID.
S302: and determining the idle ID according to the historical end time corresponding to each ID.
When the historical end time corresponding to the ID is on the same day, the corresponding fair workload is less than the fair workload saturation, and the corresponding actual workload is less than the actual workload upper limit, it may be determined that the ID is an idle ID.
S303: and selecting n IDs to be matched from the idle IDs according to the requirement parameters corresponding to the tasks to be allocated.
During specific implementation, the requirement parameters corresponding to the tasks include the types of the tasks to be distributed (design tasks, coding tasks or test tasks), whether designers are designated, whether coding personnel are designated, whether test personnel are designated, personnel levels, the average value of examination in three seasons and the defect density requirement. The invention can select the ID meeting the requirement parameters from the idle IDs as the ID to be matched.
For example, the type of the task to be distributed is a design task, a designer is not specified, the personnel level is required to be greater than or equal to level A, the average value of the evaluation in the last three quarters is greater than B, and the defect density is greater than C, the personnel type is selected from the idle IDs as the designer, the personnel level is greater than or equal to level A, and the ID with the average value of the evaluation in the last three quarters greater than B and the defect density greater than C is taken as the ID to be matched. Wherein, the ID to be matched is generally selected from the idle IDs of the current day. And if no idle ID exists on the current day, selecting an ID to be matched from the idle IDs on the next day.
S102: and determining decision factors of the n IDs to be matched according to the label factors, the labels of the tasks to be distributed, the labels of the n IDs to be matched and the maturity cardinalities of the n IDs to be matched.
In one embodiment, S102 includes: determining the matching number of the n IDs to be matched and the labels of the tasks to be allocated according to the labels of the tasks to be allocated and the labels of the n IDs to be matched; and determining decision factors of the n IDs to be matched according to the label factors, the matching number of the n IDs to be matched and the labels of the tasks to be distributed and the maturity cardinality of the n IDs to be matched.
The tags comprise technical tags and service tags, and the matching number of the IDs to be matched and the technical tags of the tasks to be allocated and the matching number of the IDs to be matched and the service tags of the tasks to be allocated can be determined according to the tags of the tasks to be allocated and the tags of the n IDs to be matched.
For a task to be distributed, a plurality of idle persons (adopting employee number (ID) identifiers, namely idle IDs) meeting requirements may exist on the same day, so that optimal matching needs to be performed according to a certain rule, and on the basis of meeting rigidity requirements (such as end time of a demand item, dependency relationship and the like), the actual completion time of the task (the time required for completing the task) is shortened as much as possible, so that the purpose of controlling cost is achieved. The invention defines a technical label and a service label in an input personnel portrait and a task portrait, determines a decision factor through the following formula so as to represent the matching degree of a task and an ID, and a greedy algorithm is used for searching an optimal matching ID to minimize the decision factor, wherein the objective function is as follows:
f＝min DecisionFactor(i),i＝1,2,...,n；
DecisionFactor(i)＝U(i)×V^(W1(i)+W2(i))；
wherein, decisionfactor (i) is a decision factor of the ith ID to be matched, U (i) is a maturity base number of the ith ID to be matched, V is a tag factor, W1(i) The matching number W of the ith ID to be matched and the technical label of the task to be distributed2' (i) is the matching number of the ith ID to be matched and the service label of the task to be distributed。
S103: and distributing the tasks to be distributed to the IDs to be matched corresponding to the minimum decision factors in the n decision factors.
TABLE 4
Table 4 is a task output table. And (3) distributing, namely outputting the Jira task by the sub-entry, and outputting the corresponding ID, the fair workload corresponding to the task and the time for starting the task according to the task type after determining the ID to be matched corresponding to the task to be distributed as shown in the table 4. And according to the flow of the time required for completing the historical task corresponding to the ID, determining the time required for completing the task to be distributed corresponding to the ID to be matched in the same way so as to determine the task completion time.
The execution subject of the task assigning method shown in fig. 1 may be a task assigning apparatus located on a computer. As can be seen from the process shown in fig. 1, the task allocation method according to the embodiment of the present invention obtains the tag factor, the tag of the task to be allocated, the tag of the ID to be matched, and the maturity base number to determine the decision factor, and allocates the task to be allocated to the ID to be matched corresponding to the minimum decision factor, so as to implement automatic allocation of the task, reasonably arrange production, improve task completion efficiency, and reduce project completion time and project cost.
TABLE 5
| Numbering | Outputting items | Output information description |
| 1 | Contract pricing | Actual pricing of items |
| 2 | Cost of the project | Actual cost of the project |
Table 5 is a cost output table. As shown in Table 5, the cost of the project is the sum of the human costs required to actually complete all tasks, and if the salary of the personnel is settled daily, the cost of each personnel is calculated by the following formula:
the personnel cost is the unit price of the staff, the time needed for completing the task and the cost of professional managers are divided;
when the cost of the project is less than the contract pricing, the project is profitable, otherwise, the personnel configuration and whether the contract pricing is reasonable need to be considered, and the cost is controlled.
If the task allocation (scheduling) is performed and the scheduling is not successful, the scheduling is required to be processed again after adjustment due to the fact that the number of designers is too small, all design tasks cannot be completed before the design completion time, or the number of encoding testers is too small, so that the tasks cannot be completed before the end time of a demand item, or the degree of saturation of the fair workload is unreasonable in configuration or the upper limit of the actual workload is unreasonable in configuration, and the like.
The specific process of the embodiment of the invention is as follows:
1. and determining the historical actual workload corresponding to each ID according to the historical decision factor of each ID and the fair workload of each historical task.
2. And determining the historical ending time corresponding to each ID according to the historical task starting time corresponding to each ID and the historical actual workload corresponding to each ID.
3. And determining the idle ID according to the historical end time corresponding to each ID.
4. And selecting n IDs to be matched from the idle IDs according to the requirement parameters corresponding to the tasks to be allocated.
5. And sequencing the tasks according to the task parameters, and determining the task sequenced at the first as the task to be distributed.
6. And determining decision factors of the n IDs to be matched according to the label factors, the labels of the tasks to be distributed, the labels of the n IDs to be matched and the maturity cardinality of the n IDs to be matched.
7. And distributing the tasks to be distributed to the IDs to be matched corresponding to the minimum decision factors in the n decision factors.
In summary, in order to solve the problems of uneven work distribution, task mismatching, and excessive project cost caused by waste of time and human resource investment due to manual scheduling in the field of software development project management, the invention provides a task distribution method based on a decision factor and a greedy algorithm. Its advantages are as follows:
1. and a computer means is adopted, task scheduling is automatically completed, and the efficiency is greatly improved.
2. And the optimal matching between the personnel ID and the task is selected based on the algorithm, so that the randomness of manual scheduling is avoided, the rationality of scheduling results is improved, and the project cost is reduced.
Based on the same inventive concept, the embodiment of the invention also provides a task allocation device, and as the principle of solving the problems of the device is similar to the task allocation method, the implementation of the device can refer to the implementation of the method, and repeated parts are not described again.
Fig. 4 is a block diagram showing the structure of a task assigning apparatus according to an embodiment of the present invention. Fig. 5 is a block diagram showing the structure of a task assigning apparatus according to another embodiment of the present invention. Fig. 6 is a block diagram of a user input module according to another embodiment of the present invention. Fig. 7 is a block diagram of a task division module according to another embodiment of the present invention. Fig. 8 is a block diagram of a result output module according to another embodiment of the present invention. FIG. 9 is a functional flow diagram of the modules in FIG. 5. As shown in fig. 4 to 9, the task assigning apparatus includes:
the acquisition module is used for acquiring the label factor, the label of the task to be distributed, the labels of the n IDs to be matched and the maturity cardinality of the n IDs to be matched; wherein n is an integer greater than 1;
the decision factor determining module is used for determining n decision factors of the IDs to be matched according to the label factors, the labels of the tasks to be distributed, the labels of the n IDs to be matched and the maturity cardinality of the n IDs to be matched;
and the task distribution module is used for distributing the tasks to be distributed to the IDs to be matched corresponding to the minimum decision factors in the n decision factors.
In one embodiment, the method further comprises the following steps:
the sequencing module is used for sequencing the tasks according to the task parameters;
and the task to be distributed determining module is used for determining the task which is sequenced in the first order as the task to be distributed.
In one embodiment, the method further comprises the following steps:
the historical ending time determining module is used for determining the historical ending time corresponding to each ID according to the historical task starting time corresponding to each ID and the historical actual workload corresponding to each ID;
the idle ID determining module is used for determining idle IDs according to the historical end time corresponding to each ID;
and the ID selection module to be matched is used for selecting n IDs to be matched from the idle IDs according to the required parameters corresponding to the tasks to be allocated.
In one embodiment, the method further comprises the following steps:
and the historical actual workload determining module is used for determining the historical actual workload corresponding to each ID according to the historical decision factor of each ID and the fair workload of each historical task.
In one embodiment, the method further comprises the following steps:
and the historical decision factor determining module is used for determining the historical decision factor of each ID according to the label factor, the label of the historical task, the label of each ID and the maturity base number of each ID.
In one embodiment, the decision factor determining module includes:
the first tag matching number determining unit is used for determining the matching number of the n IDs to be matched and the tags of the tasks to be allocated according to the tags of the tasks to be allocated and the tags of the n IDs to be matched;
and the decision factor determining unit is used for determining the decision factors of the n IDs to be matched according to the label factors, the number of the n IDs to be matched, the labels of the tasks to be distributed and the maturity cardinality of the n IDs to be matched.
In one embodiment, the historical decision factor determination module includes:
a second tag matching number determining unit, configured to determine, according to the tags of the historical tasks and the tags of the IDs, the number of tags matching between each ID and a historical task;
and the historical decision factor determining unit determines the historical decision factor of each ID according to the label factor, the number of the labels matched with each ID and the historical task and the maturity base number of each ID.
As shown in fig. 5 to 9, in practical applications, the task assigning apparatus includes: the system comprises a user input module, a task division module and a result output module.
The user input module comprises an acquisition module, and specifically comprises a task portrait configuration unit, a personnel portrait configuration unit and a parameter information configuration unit.
The task image configuration unit is used for inputting a task image table.
The person portrait configuration unit is used for inputting a person portrait table.
The parameter information configuration unit is used for inputting a parameter information table.
The task division module comprises a task preprocessing unit and a strategy execution unit.
The task preprocessing unit comprises a sequencing module and a task to be distributed determining module.
The strategy execution unit comprises a history ending time determination module, an idle ID determination module, an ID selection module to be matched, a history actual workload determination module, a history decision factor determination module and a decision factor determination module.
The result output module is used for outputting the results of the personnel scheduling and the task scheduling stored in the computer memory according to a certain format, and comprises a Jira task output unit and a cost output unit.
The Jira task output unit comprises a task distribution module used for outputting the Jira tasks, and the Jira tasks comprise data in a task output table.
The cost output unit is used for outputting the cost and contract pricing of the item.
As shown in fig. 9, the functions of the modules in fig. 5 are as follows:
1. the user input module obtains a task sketch table, a personnel sketch table and a parameter information table.
2. The task division module sorts all tasks according to parameters such as end time of a demand item, personnel level, defect density and the like, the sorting priority is reduced in sequence, and time sequence requirements and high-value requirements are guaranteed to be realized preferentially; and then based on the decision factor, selecting the optimal ID of the task to be distributed through a greedy algorithm.
3. And judging whether a task which is not scheduled exists or not.
4. And if no idle ID exists in the current day, selecting an ID to be matched from the idle IDs in the next day, and entering the task division module again for optimized division and matching.
5. And if all the tasks are scheduled, the result output module outputs a Jira task output table and a cost output table to the user.
To sum up, the task allocation device of the embodiment of the present invention obtains the tag factor, the tag of the task to be allocated, the tag of the ID to be matched, and the maturity base number to determine the decision factor, and allocates the task to be allocated to the ID to be matched corresponding to the minimum decision factor, so as to achieve automatic allocation of the task, reasonably arrange production, improve task completion efficiency, and reduce project completion time and project cost.
The embodiment of the invention also provides a specific implementation mode of computer equipment, which can realize all the steps in the task allocation method in the embodiment. Fig. 10 is a block diagram of a computer device in an embodiment of the present invention, and referring to fig. 10, the computer device specifically includes the following:
a processor (processor)1001 and a memory (memory) 1002.
The processor 1001 is configured to call a computer program in the memory 1002, and when the processor executes the computer program, the processor implements all the steps in the task allocation method in the above embodiments, for example, when the processor executes the computer program, the processor implements the following steps:
acquiring a label factor, labels of tasks to be distributed, labels of n IDs to be matched and maturity cardinality of the n IDs to be matched; wherein n is an integer greater than 1;
determining decision factors of the n IDs to be matched according to the label factors, the labels of the tasks to be distributed, the labels of the n IDs to be matched and the maturity cardinality of the n IDs to be matched;
and distributing the tasks to be distributed to the IDs to be matched corresponding to the minimum decision factors in the n decision factors.
To sum up, the computer device of the embodiment of the present invention obtains the tag factor, the tag of the task to be allocated, the tag of the ID to be matched, and the maturity base number to determine the decision factor, and allocates the task to be allocated to the ID to be matched corresponding to the minimum decision factor, so as to achieve automatic allocation of the task, reasonably arrange production, improve task completion efficiency, and reduce project completion time and project cost.
An embodiment of the present invention further provides a computer-readable storage medium capable of implementing all the steps in the task allocation method in the foregoing embodiment, where the computer-readable storage medium stores a computer program, and the computer program, when executed by a processor, implements all the steps in the task allocation method in the foregoing embodiment, for example, when the processor executes the computer program, the processor implements the following steps:
acquiring a label factor, labels of tasks to be distributed, labels of n IDs to be matched and maturity cardinality of the n IDs to be matched; wherein n is an integer greater than 1;
determining decision factors of the n IDs to be matched according to the label factors, the labels of the tasks to be distributed, the labels of the n IDs to be matched and the maturity cardinality of the n IDs to be matched;
and distributing the tasks to be distributed to the IDs to be matched corresponding to the minimum decision factors in the n decision factors.
To sum up, the computer-readable storage medium of the embodiment of the present invention obtains the tag factor, the tag of the task to be allocated, the tag of the ID to be matched, and the maturity base number to determine the decision factor, and allocates the task to be allocated to the ID to be matched corresponding to the minimum decision factor, so as to achieve automatic allocation of the task, reasonably arrange production, improve task completion efficiency, and reduce project completion time and project cost.
The above-mentioned embodiments are intended to illustrate the objects, technical solutions and advantages of the present invention in further detail, and it should be understood that the above-mentioned embodiments are only exemplary embodiments of the present invention, and are not intended to limit the scope of the present invention, and any modifications, equivalent substitutions, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.
Those of skill in the art will further appreciate that the various illustrative logical blocks, units, and steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both. To clearly illustrate the interchangeability of hardware and software, various illustrative components, elements, and steps have been described above generally in terms of their functionality. Whether such functionality is implemented as hardware or software depends upon the particular application and design requirements of the overall system. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present embodiments.
The various illustrative logical blocks, or elements, or devices described in connection with the embodiments disclosed herein may be implemented or performed with a general purpose processor, a digital signal processor, an Application Specific Integrated Circuit (ASIC), a field programmable gate array or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof designed to perform the functions described herein. A general-purpose processor may be a microprocessor, but in the alternative, the processor may be any conventional processor, controller, microcontroller, or state machine. A processor may also be implemented as a combination of computing devices, e.g., a digital signal processor and a microprocessor, a plurality of microprocessors, one or more microprocessors in conjunction with a digital signal processor core, or any other similar configuration.
The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. A software module may be stored in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art. For example, a storage medium may be coupled to the processor such the processor can read information from, and write information to, the storage medium. In the alternative, the storage medium may be integral to the processor. The processor and the storage medium may reside in an ASIC, which may be located in a user terminal. In the alternative, the processor and the storage medium may reside in different components in a user terminal.
In one or more exemplary designs, the functions described above in connection with the embodiments of the invention may be implemented in hardware, software, firmware, or any combination of the three. If implemented in software, the functions may be stored on or transmitted over as one or more instructions or code on a computer-readable medium. Computer-readable media includes both computer storage media and communication media that facilitate transfer of a computer program from one place to another. Storage media may be any available media that can be accessed by a general purpose or special purpose computer. For example, such computer-readable media can include, but is not limited to, RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to carry or store program code in the form of instructions or data structures and which can be read by a general-purpose or special-purpose computer, or a general-purpose or special-purpose processor. Additionally, any connection is properly termed a computer-readable medium, and, thus, is included if the software is transmitted from a website, server, or other remote source via a coaxial cable, fiber optic cable, twisted pair, Digital Subscriber Line (DSL), or wirelessly, e.g., infrared, radio, and microwave. Such discs (disk) and disks (disc) include compact disks, laser disks, optical disks, DVDs, floppy disks and blu-ray disks where disks usually reproduce data magnetically, while disks usually reproduce data optically with lasers. Combinations of the above may also be included in the computer-readable medium.
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