CN110648076A

CN110648076A - Task allocation method, device, equipment and storage medium

Info

Publication number: CN110648076A
Application number: CN201910924588.2A
Authority: CN
Inventors: 徐金红
Original assignee: Suzhou Da Jia Ying Information Technology Co Ltd
Current assignee: Suzhou Da Jia Ying Information Technology Co Ltd
Priority date: 2019-09-27
Filing date: 2019-09-27
Publication date: 2020-01-03

Abstract

The embodiment of the invention discloses a task allocation method, a device, equipment and a storage medium. The method comprises the following steps: determining the quantity of task demands according to the tasks to be processed issued by the target node; determining a target area corresponding to a task to be processed, a target processing node block in the target area and a target processing node in the target processing node block according to the position information of the target node, the position information of each processing node block in each preset area, the processing resource quantity of each processing node, the task demand quantity and the ratio of the processing resource demand quantity and the task quantity of different preset areas; and respectively sending the tasks to be processed to the target processing nodes. According to the technical scheme, the difficulty of executing the tasks to be processed by processing resources in different areas is considered, and the task completion effect of the target processing nodes in different areas is ensured; in case that the processing nodes constitute a block of processing nodes, the problem of task resource imbalance among the processing nodes in the block can also be avoided.

Description

Task allocation method, device, equipment and storage medium

Technical Field

The embodiment of the invention relates to the technical field of information processing, in particular to a task allocation method, a task allocation device, a task allocation equipment and a task allocation storage medium.

Background

In order to meet the demand of labor of the rapidly-developing manufacturing and service industry, in the domestic market in the future, the blue-collar recruitment market will occupy most of the wall of the whole recruitment market.

At present, the large and medium-sized manufacturing industry in the market transfers recruitment pressure to a labor company mainly in cooperation modes of labor dispatching, outsourcing and the like, and the labor company mainly depends on an intermediary mechanism to recruit workers in batches. One important reason why factory recruitment has progressed slowly for many years is that large and medium-sized manufacturing industries are unstable, instantaneous demands are too large (hundreds of people are often), traditional recruitment websites can only provide resumes, and neither intermediaries nor labor companies can complete the conversion process from online to offline, so that only direct supply of people can be relied on for offline channels.

Generally, after receiving the recruitment requirement information of the labor company, the intermediary organization allocates the recruitment task according to the distance between the recruitment enterprise and the offline store through an internal system, and the offline store of the received recruitment task can perform the recruitment work. However, the task allocation method may cause imbalance of task resources among the recruitment stores, especially imbalance of task resources among the geographically adjacent recruitment stores, and the influence of the density and distance of the recruitment stores on the recruitment work is not considered.

Disclosure of Invention

Embodiments of the present invention provide a task allocation method, apparatus, device, and storage medium, so as to optimize a task allocation manner in the prior art, avoid a phenomenon of unbalanced task allocation, and ensure a task completion effect.

In a first aspect, an embodiment of the present invention provides a task allocation method, including:

determining the task demand quantity matched with each task to be processed according to one or more tasks to be processed issued by one or more target nodes;

determining at least one target area corresponding to each task to be processed, at least one target processing node block in the target area and at least one target processing node in the target processing node block according to the position information of the target node, the position information of each processing node block in each preset area, the number of processing resources possessed by each processing node, the number of task demands and the ratio of the number of processing resource demands in different preset areas to the number of tasks; each preset area comprises at least one processing node block, and each processing node block comprises at least one processing node;

and respectively sending each task to be processed to the corresponding target processing node.

In a second aspect, an embodiment of the present invention further provides a task allocation apparatus, including:

the task demand quantity determining module is used for determining the task demand quantity matched with each task to be processed according to one or more tasks to be processed issued by one or more target nodes;

a target processing node determining module, configured to determine, according to the location information of the target node, the location information of each processing node block in each preset region, the number of processing resources possessed by each processing node, the number of task demands, and a ratio of the number of processing resources demanded in different preset regions to the number of tasks, at least one target processing node in at least one target processing node block in at least one target region corresponding to each task to be processed; each preset area comprises at least one processing node block, and each processing node block comprises at least one processing node;

and the task allocation module is used for respectively sending each task to be processed to the corresponding target processing node.

In a third aspect, an embodiment of the present invention further provides a computer device, including a memory, a processor, and a computer program stored on the memory and executable on the processor, where the processor implements the task allocation method according to any embodiment of the present invention when executing the program.

In a fourth aspect, the embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the task allocation method according to any embodiment of the present invention.

In the technical scheme provided by the embodiment of the invention, after a task to be processed issued by a target node is received, the task demand quantity matched with the task to be processed is determined, then each target processing node corresponding to the task to be processed is determined according to the position relationship between the target node and each processing node, the quantity of processing resources possessed by each processing node, the task demand quantity and the ratio of the processing resource demand quantity to the task quantity in different preset areas, and finally the task to be processed is sent to the target processing nodes, so that the processing resources of the target processing nodes execute the task to be processed. According to the technical scheme, the different difficulty degrees of the processing resources in different areas for executing the tasks to be processed are considered, the required number of the tasks is not only referred to when the target processing nodes corresponding to the tasks to be processed are determined, but also the task completion effect of the target processing nodes in different areas is ensured by combining the ratio of the required number to the number of the tasks in different areas; in the above technical solution, after the target processing node block matching the to-be-processed task is determined, the target processing node matching the to-be-processed task is determined from the target processing node block, and in contrast to the technical solution in which the target processing node is determined only according to the absolute distance between the target node and each processing node, when a plurality of processing nodes are close to each other to form a processing node block, the problem that the to-be-processed task of the same target node can only be allocated to a specific processing node, and further the task resources among the processing nodes in the node block are unbalanced can be avoided.

Drawings

FIG. 1 is a flowchart of a task allocation method according to a first embodiment of the present invention;

FIG. 2 is a block diagram of a processing node according to an embodiment of the present invention;

FIG. 3 is a flowchart of a task allocation method according to a second embodiment of the present invention;

FIG. 4 is a schematic structural diagram of a task allocation apparatus according to a third embodiment of the present invention;

fig. 5 is a schematic hardware configuration diagram of a computer device in the fourth embodiment of the present invention.

Detailed Description

The present invention will be described in further detail with reference to the accompanying drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting of the invention. It should be further noted that, for the convenience of description, only some of the structures related to the present invention are shown in the drawings, not all of the structures.

Before discussing exemplary embodiments in more detail, it should be noted that some exemplary embodiments are described as processes or methods depicted as flowcharts. Although a flowchart may describe the operations (or steps) as a sequential process, many of the operations can be performed in parallel, concurrently or simultaneously. In addition, the order of the operations may be re-arranged. The process may be terminated when its operations are completed, but may have additional steps not included in the figure. The processes may correspond to methods, functions, procedures, subroutines, and the like.

Example one

Fig. 1 is a flowchart of a task allocation method according to an embodiment of the present invention, which is applicable to a case where a task to be processed of a target node is allocated to each processing node matched with the target node to complete when a processing node cluster exists.

As shown in fig. 1, the method of this embodiment specifically includes:

s110, determining the task demand quantity matched with each task to be processed according to one or more tasks to be processed issued by one or more target nodes.

The target node refers to a node that issues a task, or is referred to as a main body of the issue task, for example, an enterprise that issues the task, or the like. Processing resources refer to individual resources that perform tasks, such as service personnel. Wherein, the task issued by the target node refers to a task that requires one or more processing resources to complete.

After the target node issues the tasks to be processed, the operator inputs the relevant information of the tasks to be processed into the task distribution system, wherein the relevant information of the tasks to be processed includes the number of task demands matched with the relevant information, and the number of the task demands specifically refers to the number of subtasks included in the tasks to be processed. For example, when the task to be processed is a recruitment task, the number of task demands matched with the task to be processed refers to the number of recruiters.

S120, determining at least one target area corresponding to each task to be processed, at least one target processing node block in the target area and at least one target processing node in the target processing node block according to the position information of the target node, the position information of each processing node block in each preset area, the number of processing resources possessed by each processing node, the number of required tasks and the ratio of the number of required processing resources in different preset areas to the number of tasks; each preset area comprises at least one processing node block, and each processing node block comprises at least one processing node.

The preset region refers to a region divided according to a preset division standard, and each preset region includes at least one processing node block. The preset partition criteria are not specifically limited in this embodiment, for example, the preset partition criteria may be divided according to a distance between an area and a target node, and assuming that two preset areas are divided, an area within a first preset distance (for example, within 50 km) from the target node may be specifically divided into a first preset area, and an area within a second preset distance (for example, outside 50 km) from the target node may be divided into a second preset area.

A processing node block refers to a block having at least one processing node. When a plurality of processing nodes are distributed in a centralized manner, the processing nodes can be divided into a processing node block.

The processing node refers to a node that provides processing resources for completing a task issued by a target node, such as a company that provides service personnel, and in particular refers to each subsidiary company belonging to the same parent company. The processing nodes are distributed in a distributed manner or in a centralized manner, and are specifically determined according to market demands.

Specifically, before S120, the method further includes: and dividing at least one processing node block into at least one preset area.

Typically, according to the geographical location information of the processing node blocks, a preset area in which each processing node block is located is determined, and the processing node blocks are divided into corresponding preset areas.

Specifically, before S120, the method further includes: at least one processing node is divided into at least one processing node block.

Optionally, the processing node blocks are divided according to the density of the processing nodes, for example, the processing node blocks are divided through a density clustering DBSCAN algorithm. Typically, the processing nodes may be divided according to the density of the processing nodes and the distance between adjacent processing nodes, and processing nodes at different distances are connected in series by means of density clustering to form a processing node block.

As shown in fig. 2, A, B, C, D four processing node clusters, the distance between cluster a and cluster C is smaller than the set threshold, and the distance between cluster a and cluster B is smaller than the set threshold, so that cluster a, cluster B, and cluster C can be divided into one processing node block, but the distance between any one of cluster a, cluster B, and cluster C and cluster D exceeds the set threshold, so that cluster D is not divided into processing node blocks including cluster a, cluster B, and cluster C.

Further, if it is determined that at least one new processing node exists, at least two processing nodes including the at least one new processing node are re-divided into at least one processing node block.

And processing node block division is carried out again each time a new processing node is recorded in the task distribution system. For example, it is automatically checked in the morning every day whether a new processing node is entered, and if so, all the processing nodes are re-partitioned, where the partition of some processing nodes may or may not be changed.

The ratio of the number of processing resources required in the preset area to the number of tasks refers to the number of processing resources required to complete one subtask in the to-be-processed task. Taking the task to be processed as the recruitment task as an example, if the ratio of the number of the processing resources required in a certain preset area to the number of the tasks is 2:1, the number of the processing resources required for recruiting one person in the area is two. Typically, the farther the preset area is from the target node, the greater the ratio of the amount of processing resource required to the amount of tasks.

And determining each target area corresponding to the task to be processed, the target processing node block in the target area and the target processing node in the target processing node block according to the position information of the target node, the position information of each processing node block in each preset area, the processing resource quantity of each processing node block, the processing resource quantity of each processing node, the task demand quantity corresponding to the task to be processed and the ratio of the processing resource demand quantity and the task quantity in different preset areas.

The processing node block comprises a processing node block and a processing node block, wherein the processing node block comprises a plurality of processing nodes, and the processing node block comprises a plurality of processing nodes; the processing resource amount of the preset area is the sum of the processing resource amounts of the processing node blocks included in the preset area.

Further, according to the ratio of the number of processing resources required in different preset areas to the number of tasks and the number of processing resources in each preset area, the number of tasks that can be processed in each preset area can be determined; wherein the number of area processable tasks is used to determine at least one target area in each of the preset areas.

Specifically, the quotient of the number of processing resources in the preset area and the ratio of the number of processing resources required in the preset area to the number of tasks is the number of tasks that can be processed by the area of the preset area. For example, if the number of processing resources in a predetermined area is 60 and the ratio of the required number of processing resources to the number of tasks in the predetermined area is 2:1, the number of tasks that can be processed by the area in the predetermined area is 30. If the quotient value is not an integer, in order to ensure the completion effect of the task to be processed, rounding processing can be performed on the quotient value, and the rounding result of the quotient value is used as the area processable task quantity. For example, if the number of processing resources in the preset area is 59, and the ratio of the number of processing resources required in the preset area to the number of tasks is 2:1, the directly calculated number of area-processable tasks in the preset area is 29.5, and the rounding process is performed on the number of area-processable tasks in the preset area, so that the number of area-processable tasks in the preset area is determined to be 29.

Similarly, the quotient of the processing resource amount of the processing node block and the ratio of the processing resource demand amount to the task amount in the preset area to which the processing node block belongs is the task amount that can be processed by the block of the processing node block; the quotient of the processing resource quantity of the processing node and the ratio of the processing resource demand quantity to the task quantity in the preset area to which the processing node belongs is the task quantity which can be processed by the processing node.

The sum of the number of the tasks which can be processed in the areas of the target areas is greater than or equal to the number of the tasks required by the tasks to be processed, and the distance between each target area and the target node is smaller than the distance between other preset areas and the target node; the sum of the number of the block processable tasks of each target processing node block is greater than or equal to the required number of the tasks to be processed for processing resources, and the distance between each target processing node block and the target node is generally smaller than the distance between other processing node blocks and the target node.

In a target area, all of the processing node blocks may be target processing node blocks, or some of the processing node blocks may be target processing node blocks; in a target processing node block, all of the processing nodes may be target processing nodes, or some of the processing nodes may be target processing nodes.

As an optional implementation manner of this embodiment, at least one target area corresponding to each task to be processed may be determined according to the location information of the target node, the location information of each processing node block in each preset area, the number of processing resources possessed by each processing node, the number of task demands, and a ratio of the number of processing resource demands to the number of tasks in different preset areas, and specifically, the determining step includes:

sequencing all the preset areas from near to far according to the distance from the target node;

sequentially acquiring a preset area as a current processing preset area;

and accumulating the number of the area processable tasks of the current processing preset area into the area processable task statistic value, and taking the current processing preset area as a target area until the area processable task statistic value is greater than or equal to the task required number.

When a task to be processed issued by a target node is received, position information of the target node and position information of each preset region are obtained, distances between the preset regions and the target node are respectively calculated, and the preset regions are sequenced according to the sequence of the distances between the preset regions and the target node from near to far.

Sequentially acquiring a preset area as a current processing preset area, calculating the area processable task number of the current processing preset area according to the ratio of the required number of processing resources to the task number in the current processing preset area and the number of the processing resources of the current processing preset area, accumulating the area processable task number of the current processing preset area into an area processable task statistic value, and simultaneously taking the current processing preset area as a target area.

Wherein the initial value of the area processable task statistic is zero.

Then, sequentially acquiring the next preset area as the current processing preset area until the area processable task statistic value is larger than or equal to the task required number, and at the moment, determining each target area corresponding to the task to be processed.

Further, if the area-processable task statistic is equal to the task required number, each processing node block in the target area is taken as a target processing node block, and each processing node in each processing node block in the target area is taken as a target processing node.

And if the area processable task statistic is larger than the task required quantity, dividing the target area into a confirmed target area and an undetermined target area, wherein the undetermined target area is the target area farthest from the target node. That is, the last determined target area is the pending target area, and the rest target areas are the confirmed target areas.

And taking each processing node block in the confirmation target area as a target processing node block, and taking each processing node in each processing node block in the confirmation target area as a target processing node.

And determining the required quantity of area subtasks corresponding to the undetermined target area according to the difference between the area processable task statistic and the required quantity of tasks and the required quantity of areas of the undetermined target area, and determining at least one target processing node block in the undetermined target area according to the distance between each processing node block in the undetermined target area and the target node and the required quantity of the area subtasks.

Specifically, under the condition that the area processable task statistic is equal to the number of task demands, all processing node blocks in each target area are target processing node blocks corresponding to the tasks to be processed, and all processing nodes in all processing node blocks in each target area are target processing nodes corresponding to the tasks to be processed.

Specifically, when the area processable task statistic is greater than the number of task demands, all processing node blocks in each confirmation target area are target processing node blocks corresponding to the tasks to be processed, and all processing nodes in all processing node blocks in each confirmation target area are target processing nodes corresponding to the tasks to be processed; the processing node blocks in the region to be targeted may be all target processing node blocks or may be partially target processing node blocks, and are related to the required number of regional subtasks in the region to be targeted.

The calculation method of the required quantity of the regional subtasks of the undetermined target region is as follows: firstly, calculating the difference value between the area processable task statistic value and the task required quantity, then calculating the difference value between the area processable task quantity of the undetermined target area and the difference value, wherein the calculation result at the moment is the area subtask required quantity of the undetermined target area.

For example: the target node B issues a task to be processed, and the task demand quantity of the task to be processed is 100. The task allocation system includes 10 processing node blocks, which are Y1 (with the number of processing resources being 40), Y2 (with the number of processing resources being 30), Y3 (with the number of processing resources being 50), Y4 (with the number of processing resources being 20), Y5 (with the number of processing resources being 45), Y6 (with the number of processing resources being 70), Y7 (with the number of processing resources being 40), Y8 (with the number of processing resources being 80), Y9 (with the number of processing resources being 40), and Y10 (with the number of processing resources being 60).

Suppose that: and according to the distance between the target node A and each processing node block, carrying out sorting processing from near to far to obtain sorted processing node blocks Y1, Y2, Y3, Y4, Y5, Y6, Y7, Y8, Y9 and Y10.

The 10 processing nodes are divided into two preset areas, wherein the processing node blocks in the first preset area comprise Y1 and Y2, and the processing node blocks in the second preset area comprise Y3, Y4, Y5, Y6, Y7, Y8, Y9 and Y10.

The ratio of the number of processing resource demands to the number of tasks within the first preset area is 1:1, and the ratio of the number of processing resource demands to the number of tasks within the second preset area is 2: 1.

The processing resource number of the first preset area is the sum of the processing resource numbers of Y1 and Y2, and the processing resource number of the first preset area is calculated to be 70, so that the area processable task number of the first preset area is calculated to be 70 according to the ratio of the processing resource demand number to the task number of the first preset area being 1: 1.

The sum of the processing resource quantities of the second preset areas is Y3, Y4, Y5, Y6, Y7, Y8, Y9 and Y10, and the processing resource quantity of the second preset area is calculated to be 405, so that the area processable task quantity of the first preset area is 202 (the result after rounding) calculated according to the ratio of the processing resource demand quantity to the task quantity in the first preset area being 2: 1.

And accumulating the sorted areas of the preset area to process the number of the tasks until the number of the tasks is more than or equal to 100. The obtained target area is a first preset area and a second preset area, and since the area processable task statistic is 272 (the sum of 70 and 202), and the area processable task statistic 272 is greater than the task required quantity 100, the target area is divided into a confirmed target area and an undetermined target area, that is, the first preset area is the confirmed target area, and the second preset area is the undetermined target area.

Therefore, each processing node block in the first preset area is a target processing node block, and each processing node in each processing node block in the first preset area is a target processing node. That is, Y1 and Y2 are both target processing node blocks, and each processing node in Y1 and Y2 is a target processing node.

The processing node blocks in the pending target area (i.e. the second preset area) may all be target processing node blocks, or may be part of the target processing node blocks, and are related to the required number of the area subtasks in the pending target area. The required quantity of the regional subtasks in the second preset region is as follows: 202- (272) and 100 ═ 30.

And then, determining each target processing node block in the undetermined target area according to the distance between each processing node block in the undetermined target area and the target node and the required quantity of the area subtasks of the undetermined target area.

As an optional implementation manner of this embodiment, at least one target processing node block may be determined in the pending target area according to the distance between each processing node block in the pending target area and the target node and the required number of the subtasks in the area, specifically:

determining the number of tasks which can be processed by each processing node block according to the ratio of the number of processing resource demands in the undetermined target area to the number of tasks and the number of processing resources of each processing node block in the undetermined target area;

sequencing the processing node blocks from near to far according to the distance from the target node;

sequentially acquiring a processing node block as a current processing node block;

and accumulating the block processable task number of the current processing node block into a block processable task statistic value, and taking the current processing node block as a target processing node block until the block processable task statistic value is larger than or equal to the required area subtask number.

Firstly, the block processable task number of each processing node block in the undetermined target area is calculated respectively, specifically, the block processable task number is a quotient of the processing resource number of the processing node block and a ratio of the required processing resource number in the undetermined target area to the task number. For example, if the processing node block has 20 processing resources and the ratio of the required number of processing resources to the number of tasks in the pending target area is 2:1, the number of tasks that can be processed by the block of the processing node block is 10.

Secondly, the distance between each processing node block and the target node is calculated (for example, the distance between each processing node block and the target node is calculated according to the longitude and latitude information of the center point of the processing node block), and each processing node block is sequenced according to the sequence of the distance between each processing node block and the target node from near to far.

Sequentially acquiring a processing node block as a current processing node block, acquiring the block processable task number of the current processing node block, accumulating the block processable task number into a block processable task statistic value, and simultaneously taking the current processing node block as a target processing node block. Wherein the initial value of the block processable task statistic is zero.

And sequentially acquiring the next processing node block as the current processing node block in sequence until the block processable task statistic is greater than or equal to the required number of the regional subtasks of the target region to be determined, and at the moment, determining each target processing node block in the target region to be determined.

Further, if the block processable task statistics are equal to the area subtask requirement number, each processing node in the target processing node block is taken as a target processing node;

and if the block processable task statistics are larger than the required number of the regional subtasks, dividing the target processing node block into a confirmed target processing node block and a pending target processing node block, wherein the pending target processing node block is the target processing node block which is farthest away from the target node in the pending target region. That is, the last determined target processing node block is the pending target processing node block, and the remaining target processing node blocks are the confirmed target processing node blocks.

Taking each processing node in the confirmed target processing node block as a target processing node;

and determining the required quantity of block subtasks corresponding to the block of the processing node to be determined according to the difference between the block processable task statistic and the required quantity of the regional subtasks and the processable task quantity of the block of the processing node to be determined, and determining at least one target processing node in the block of the processing node to be determined according to the historical task statistic of each processing node in the block of the processing node to be determined and the required quantity of the block subtasks.

Specifically, under the condition that the block processable task statistic is equal to the required number of the regional subtasks, all processing nodes in each target processing node block are target processing nodes corresponding to the tasks to be processed.

Specifically, under the condition that the block processable task statistic is greater than the required number of the regional subtasks, all processing nodes in each block of the confirmation target processing nodes are target processing nodes corresponding to the tasks to be processed; processing nodes in the block of the processing node to be targeted may all be target processing nodes, or may be part of the target processing nodes, and are related to the required number of block subtasks of the block of the processing node to be targeted.

The required number of the block subtasks of the block of the undetermined target processing node is calculated in the following mode:

firstly, calculating the difference value between the block processable task statistic value and the area subtask required number of the undetermined target area, then calculating the difference value between the block processable task number of the undetermined target processing node block and the difference value, wherein the calculation result at the moment is the block subtask required number of the undetermined target processing node block.

Following the previous example, the calculated block processable task numbers of each processing node block in the second preset area are respectively: the block processable task number of Y3 is 25, the block processable task number of Y4 is 10, the block processable task number of Y5 is 22, the block processable task number of Y6 is 35, the block processable task number of Y7 is 20, the block processable task number of Y8 is 40, the block processable task number of Y9 is 20, and the block processable task number of Y10 is 30.

And accumulating the block processable task number of the sorted processing node blocks until the block processable task number is more than or equal to the area subtask required number 30. The obtained target processing node blocks are Y3 and Y4, and since the block processable task statistic is 35 (sum of 25 and 10), and the block processable task statistic 35 is greater than the area subtask requirement number 30, the target processing node blocks are divided into confirmed target processing node blocks and pending target processing node blocks, that is, Y3 is the confirmed target processing node block, and Y4 is the pending target processing node block.

Thus, each processing node in the target processing node block is confirmed to be a target processing node. That is, each processing node in processing node block Y3 is a target processing node.

The processing nodes in the pending target processing node block (i.e., processing node block Y4) may all be target processing nodes or may be partially target processing nodes, depending on the number of block subtask requirements of the pending target processing node block. The required number of block subtasks of processing node block Y4 is: 10- (35-30) ═ 5.

And then, determining each target processing node in the undetermined target processing node block according to the historical task statistic value of each processing node in the undetermined target processing node block and the required number of block subtasks of the undetermined target processing node block.

As an optional implementation manner of this embodiment, at least one target processing node may be determined in a block of pending target processing nodes according to the size of the historical task statistics of each processing node in the block of pending target processing nodes and the required number of subtasks of the block, specifically:

determining the number of tasks which can be processed by the nodes of each processing node according to the ratio of the number of processing resources required in the undetermined target area to the number of tasks and the number of processing resources of each processing node in the undetermined target processing node block;

sequencing all processing nodes in the undetermined target processing node block from small to large according to historical task statistics; wherein the historical task statistics are updated after the processing node receives the task to be processed;

sequentially acquiring a processing node as a current processing node; and accumulating the node processable task number of the current processing node into a node processable task statistic value, and taking the current processing node as a target processing node until the node processable task statistic value is greater than or equal to the required block subtask number.

And the historical task statistic value of the processing node is the number of the tasks to be processed which are distributed to one processing node in a set time period. Optionally, the starting time point of the set time period is a time when the processing node is divided into one processing node block, and the ending time point is a current time.

According to the historical task statistic value of the processing nodes, the condition that each processing node in the same processing node block is allocated with a task can be analyzed. In order to avoid the phenomenon of unbalanced task allocation of the processing nodes in the same processing node block, in this embodiment, the processing nodes with smaller historical task statistics values in the same processing node block are preferentially allocated with tasks. Each time a processing node is successfully assigned a task, its historical task statistics are updated, e.g., each time a task is successfully assigned, the historical task statistics are incremented by one.

Firstly, the node processable task number of each processing node in the processing node block to be targeted is respectively calculated, specifically, the node processable task number is a quotient of the processing resource number of the processing node and the ratio of the required processing resource number in the processing node to be targeted to the task number. For example, if the number of processing resources provided by a processing node is 10, and the ratio of the number of processing resources required in the pending target area to the number of tasks is 2:1, the number of tasks that can be processed by the node of the processing node is 5.

And secondly, sequencing all processing nodes in the processing node block to be targeted according to historical task statistics from small to large.

Sequentially acquiring a processing node as a current processing node, acquiring the number of tasks which can be processed by the node of the current processing node, accumulating the number of tasks which can be processed by the node into a node-processed task statistic value, and simultaneously taking the current processing node as a target processing node. Wherein the initial value of the task statistic processable by the node is zero.

And sequentially acquiring the next processing node as the current processing node in sequence until the statistics of the tasks which can be processed by the node is greater than or equal to the required number of the block subtasks, and determining each target processing node in the block of the undetermined target processing node.

In the previous example, assume that the processing node block Y4 includes two processing nodes, M1 (the number of processing resources is 10) and M2 (the number of processing resources is 10), which are sorted from small to large according to the historical task statistics into M1 and M2.

The calculated node processable task numbers of the processing nodes in the processing node block Y4 are respectively: the node processable task number of M1 is 5 and the node processable task number of M2 is 5. And accumulating the number of the processing resources in the sorted processing nodes until the number is more than or equal to 5 of the block subtask requirement number, and obtaining a target processing node M1.

Up to this point, the respective target processing nodes corresponding to the to-be-processed task issued by the target node B are obtained, which are all the processing nodes included in Y1, Y2, and Y3, and the processing node M1 included in Y4, respectively. These historical task statistics assigned to the processing nodes of the task to be processed are incremented by one.

In the event that it is determined that there is at least one new processing node, processing node block partitioning is resumed for all processing nodes. After the processing node block is divided again, the processing nodes in each processing node block may or may not be changed.

Further, after the subdivision into at least one processing node block, the method further includes:

if at least one processing node is newly added in the target processing node block, initializing the historical task statistic value of each processing node in the target processing node block.

After the processing node block is divided again, if a processing node is added to a processing node block, which means that at least one processing node originally not belonging to the processing node block is added, which may be a processing node newly recorded by the system, or a processing node originally belonging to another processing node block is added, the historical task statistics of each processing node in the processing node block is initialized, for example, the processing node is set to zero.

S130, each task to be processed is sent to the corresponding target processing node.

After the target processing node corresponding to each task to be processed is determined, the task to be processed is sent to the corresponding target processing node, so that the processing resource of the target processing node executes the task after receiving the task to be processed.

After the to-be-processed task is sent to the corresponding target processing node, the name and the ID of the target processing node can be associated with the to-be-processed task and recorded in the task allocation table.

In the technical scheme provided by the embodiment of the invention, after a task to be processed issued by a target node is received, the task demand quantity matched with the task to be processed is determined, then each target processing node corresponding to the task to be processed is determined according to the position relationship between the target node and each processing node, the quantity of processing resources possessed by each processing node, the task demand quantity and the ratio of the processing resource demand quantity to the task quantity in different preset areas, and finally the task to be processed is sent to the target processing nodes, so that the processing resources of the target processing nodes execute the task to be processed.

According to the technical scheme, the different difficulty degrees of the processing resources in different areas for executing the tasks to be processed are considered, the required number of the tasks is not only referred to when the target processing nodes corresponding to the tasks to be processed are determined, but also the task completion effect of the target processing nodes in different areas is ensured by combining the ratio of the required number to the number of the tasks in different areas.

In the above technical solution, after the target processing node block matching the to-be-processed task is determined, the target processing node matching the to-be-processed task is determined from the target processing node block, and in contrast to the technical solution in which the target processing node is determined only according to the absolute distance between the target node and each processing node, when a plurality of processing nodes are close to each other to form a processing node block, the problem that the to-be-processed task of the same target node can only be allocated to a specific processing node, and further the task resources among the processing nodes in the node block are unbalanced can be avoided.

It should be noted that the target processing node blocks and/or the target processing nodes corresponding to different to-be-processed tasks issued by different target nodes, which are determined in the present embodiment, are allowed to have a coincidence phenomenon. For example, the target processing nodes corresponding to the to-be-processed tasks issued by the target node a include a, B, c, d, e, f and g, and meanwhile, the target processing nodes corresponding to the to-be-processed tasks issued by the target node B include h, i, j, k, l, g, f and e, that is, the target processing nodes e, f and g may receive a plurality of to-be-processed tasks issued by a plurality of target nodes at the same time, and the processing resources of the target processing nodes e, f and g may process a plurality of to-be-processed tasks issued by a plurality of target nodes at the same time.

Example two

Fig. 3 is a flowchart of a task allocation method according to a second embodiment of the present invention, and the present embodiment provides a specific implementation manner for a specific application scenario, where in the application scenario, a target node is a target plant, a task to be processed is a recruitment order, a processing node is an offline recruitment store, and a processing resource is a recruitment service person. Accordingly, the processing node block is a store block.

In the application scenario, an order distribution system (corresponding to the task distribution system in the first embodiment) can be developed for distributing a recruitment order to an offline recruitment store. The order distribution system distributes an ID to each offline recruitment store and stores the position information (such as longitude and latitude information) of each offline recruitment store. After each offline recruitment store is divided into different store blocks, the position information of each store block (such as the longitude and latitude information of the center point of the store block) can be determined. The store keeper of the offline recruitment store adds the number of the recruitment service personnel (such as the mobile phone number of the recruitment service personnel) in the store, the recruitment service personnel can check the distributed recruitment orders after logging in the system, and the system determines the number of the recruitment service personnel in each offline recruitment store according to the number of the recruitment service personnel accounts of each offline recruitment store.

Meanwhile, the system divides each store block into areas, and different service personnel ratios (the ratio of the required quantity of the recruiting service personnel to the number of the recruiting personnel) are set in different areas. The closer the target factory is to the store block, the smaller the ratio of the service personnel in the area to which the store block belongs, for example, 1:1, and the farther the target factory is from the store block, the larger the ratio of the service personnel in the area to which the store block belongs, for example, 2:1 or 3:1, etc.

Specifically, in the technical solution provided in this embodiment, before determining at least one target area corresponding to each task to be processed, at least one target processing node block in the target area, and at least one target processing node in the target processing node block according to the location information of the target node, the location information of each processing node block in each preset area, the number of processing resources possessed by each processing node, the number of task demands, and a ratio of the number of processing resource demands to the number of tasks in different preset areas, the method further includes:

and judging that the worker delivery grade of the target factory corresponding to each recruitment order is a second grade.

As shown in fig. 3, the method of this embodiment specifically includes:

s210, judging whether the labor conveying level of the target factory is a second level, if so, executing S220, and if not, executing S250.

The target factory refers to a recruitment factory with unstable labor and possibly large instantaneous demand, and issues a recruitment order to a recruitment intermediary by itself or through a labor company when the recruitment is demanded.

And after receiving the recruitment order, the operator of the recruitment intermediary mechanism inputs the recruitment order into the order distribution system so that the order distribution system determines the required quantity of the recruitment service personnel matched with the order according to the recruitment order.

Specifically, the labor transportation grade of the target plant can be determined according to the labor transportation record of the target plant.

As an optional implementation manner of this embodiment, the determining the recruitment transportation level of the target plant corresponding to each recruitment order may specifically be:

sorting the factories according to the size sequence of the total working time of the historical delivery users of each factory in a set time period;

calculating the accumulated total working time corresponding to each factory according to the factory sequencing; wherein the accumulated total job time corresponding to the target plant is a cumulative sum of the total job time of each plant ranked before the target plant and the target plant;

calculating the accumulated sum of the total working hours of the historical delivery users of each factory in the set time period; and judging the recruitment transportation grade of the target factory according to the ratio of the accumulated sum of the accumulated total working hours corresponding to the target factory in the total working hours.

Firstly, counting the personnel who are in the historical delivery users of each factory within a set time period (for example, the last 30 days), respectively calculating the total working time of the historical delivery users of each factory according to the working time of each personnel, and sequencing the factories according to the sequence of the total working time from large to small; then, according to the factory sequencing, accumulating the total working time of all the factories from the factory with the first ranking to the target factory, wherein the accumulated sum is the accumulated total working time of the target factory; and finally, calculating the sum of the total working hours of the historical delivery users of all the factories, and the ratio of the accumulated total working hours of the target factory to the sum of the accumulated total working hours of the target factory to the total working hours, namely the basis for judging the recruitment delivery grade of the target factory.

Further, the employment delivery grade of the target plant may be determined according to the ratio of the cumulative sum of the total working hours of the accumulated total working hours corresponding to the target plant in the total working hours, specifically:

if the ratio of the accumulated total working duration corresponding to the target factory to the sum of the total working duration belongs to a first ratio range, judging that the worker conveying level of the target factory is a first level;

if the ratio of the accumulated total working duration corresponding to the target factory to the sum of the total working duration belongs to a second ratio range, judging that the work transportation grade of the target factory is a second grade;

if the ratio of the accumulated total working duration corresponding to the target factory to the sum of the total working duration belongs to a third ratio range, judging that the recruitment transportation grade of the target factory is a third grade;

wherein, the proportion value included in the first proportion range, the second proportion range and the third proportion range is increased in sequence.

For example, if the ratio of the accumulated total working hours corresponding to the target plant to the accumulated sum of the total working hours is 70% at the top (the first ratio range is 0-70%), the recruitment transportation grade of the target plant is the first grade, and the first grade represents that the number of historical transportation users is large; the proportion of the accumulated total working duration corresponding to the target plant to the accumulated sum of the total working duration is 70% -90% (the second proportion range is 70% -90%), the work delivery grade of the target plant is the second grade, and the second grade represents that the number of historical delivery users is general; and if the occupation ratio of the accumulated total working duration corresponding to the target plant in the total working duration is 10 percent later (the third occupation ratio range is 90-100 percent), the recruitment transportation grade of the target plant is the third grade, and the third grade represents that the number of historical transportation users is small.

For example, by now, there are 1000 on-line members in the offline store historical delivery, and assuming that the average on-duty time of each of the 1000 on-duty members in the last 30 days is 10 days, the total on-duty time sum of the historical delivery users is 1000 × 10 to 10000 days. The 1000 employees are distributed in 5 factories, wherein the total duration of employment of factory X1 is 5000 days, the total duration of employment of factory X2 is 2000 days, the total duration of employment of factory X3 is 1500 days, the total duration of employment of factory X4 is 1000 days, and the total duration of employment of factory X5 is 500 days.

Wherein, the factory with the accumulated total duration in the first 70% of the accumulated sum of the total duration is in the first grade; the factory with the accumulated total duration of employment accounting for 70% -90% of the accumulated total duration of employment in the accumulated sum of the total duration of employment is in a second grade; the percentage of the cumulative total length of stay in the cumulative sum of total lengths of stay in the next 10% of the plants is the third grade.

This yields:

the ratio of the accumulated total duration of employment in the accumulated sum of the total duration of employment at the factory X1 is 5000/10000-50%, and the service delivery grade of the factory X1 is a first grade;

the ratio of the accumulated total working hours of the factory X2 in the accumulated sum of the total working hours is (5000+2000)/10000 is 70%, and the work transportation grade of the factory X2 is a first grade;

the ratio of the accumulated total duration of employment in the accumulated sum of the total duration of employment at the factory X3 is (5000+2000+1500)/10000 is 85%, and the service delivery grade of the factory X3 is a second grade;

the ratio of the accumulated total working hours of the factory X4 in the accumulated sum of the total working hours is (5000+2000+1500+1000)/10000 is 95%, and the recruitment grade of the factory X4 is a third grade;

the ratio of the accumulated total duration of employment in the accumulated sum of the total duration of employment at plant X5 is (5000+2000+1500+1000+500)/10000 is 100%, and the employment delivery grade at plant X5 is the third grade.

Typically, the labor delivery level of each plant may be maintained periodically, e.g., updated once a day, and recorded for storage. And when a recruitment order of the target factory is received, directly inquiring the recruitment and transportation quantity grade of the target factory.

Compared with the technical scheme of determining the recruitment transportation grade of the target plant according to the ranking proportion of the historical recruitment transportation amount of the target plant, the technical scheme of determining the recruitment transportation grade of the target plant has the advantages that: the obtained work conveying grade of the target factory is judged more accurately.

Assuming that the cumulative sum of the total working hours is 10000 days, the cumulative total working hours of the plant X1 is 7000 days, the cumulative total working hours of the plant X2 is 500 days, the cumulative total working hours of the plant X3 is 400 days, the cumulative total working hours of the plant X4 is 300 days … …, if the mining transportation grade of the target plant is determined according to the historical mining transportation quantity ranking proportion, since the plant X2 is ranked as the second historical mining transportation quantity, when the mining transportation grade is determined according to the ranking proportion, the mining transportation grade of the plant X2 is likely to be determined as the first grade, in fact, the historical mining transportation quantity of the plant X2 is not much, and further, the determined mining transportation grade is not accurate. However, according to the above technical solution for determining the industrial transportation level of the target plant, although the rank of the plant X2 is adjacent to the rank of the plant X1 according to the accumulated total working hours, the industrial transportation level of the plant X2 is not the same as the industrial transportation level of the plant X1, and thus the determined industrial transportation level can be more accurately matched with the actual industrial transportation amount.

And S220, determining a total recruitment number matched with each recruitment order according to the one or more recruitment orders released by the one or more target factories.

Wherein the total number of recruits is known information in the recruiting order.

And S230, determining at least one target area corresponding to each recruitment order, at least one target store block in the target area and at least one target offline recruitment store in the target store blocks according to the position information of the target plant, the position information of each store block in each preset area, the number of recruitment service personnel in each offline recruitment store, the total number of the recruitment persons and the ratio of the required number of the recruitment service personnel to the number of the recruitment persons in different preset areas.

Each offline recruitment store in the system is divided into at least one store block in advance, and the number of the recruitment service personnel in one store block is the sum of the recruitment service personnel in each offline recruitment store in the store block. And dividing each store block into different preset areas, wherein the number of the recruitment service personnel in one preset area is the sum of the recruitment service personnel in each offline recruitment store in the preset area.

The off-line recruitment stores in different preset areas are different from the target plant in distance, so that the recruitment service personnel in different preset areas have different difficulty degrees in completing the recruitment orders of the target plant. For example, each of the on-line recruitment service personnel in the off-line recruitment store closer to the target plant may recruit one worker, and every two of the on-line recruitment service personnel in the off-line recruitment store closer to the target plant may recruit one worker. Therefore, the parameter of the ratio of the required quantity of the recruitment service personnel to the number of the recruiters in the preset area is introduced to determine the required quantity of the recruitment service personnel in different preset areas.

Specifically, the number of available recruiters in each preset area, the number of available recruiters in each store block, and the ratio of the required number of the available recruiters to the number of available recruiters in each preset area can be calculated according to the number of the available recruiters in each preset area, the number of the available recruiters in each store block, and the ratio of the required number of the available recruiters to the number of the available recruiters in each preset area, so as to obtain the number of available recruiters in each preset area, the number of available recruiters in each store block, and the number of available recruiters in each store block.

And calculating an ordered list of the preset areas according to the distance between the target factory and each preset area, and then sequentially accumulating the number of the available recruitment persons in each preset area until the total number of the recruitment persons matched with the recruitment order is met, so as to determine each target area corresponding to the recruitment order.

The number of the regional recruiters in the last determined target region (namely the target region to be determined) may be equal to or smaller than the number of the available recruiters in the target region, and the number of the regional recruiters in the other determined target regions is equal to the number of the available recruiters in the target region. And when the number of the regional recruiters in the target region is equal to the number of the regional recruitable persons, all the offline recruiting stores in all store blocks in the target region are target offline recruiting stores.

When the number of regional recruiters in the pending target region is smaller than the number of available regional recruiters, an ordered list of store blocks can be calculated according to the distance between each store block in the target region and the target plant, then the number of available regional recruiters of each store block is accumulated in sequence until the number of regional recruiters in the target region is met, and therefore each target store block in the pending target region is determined.

The number of the block recruiting sub-persons of the target store block determined last in the pending target area (namely the pending target store block) may be equal to the number of the block recruitable sub-persons of the target store block, and may be smaller than the number of the block recruitable sub-persons of the target store block, and the number of the block recruiting sub-persons of the other determined target store blocks is equal to the number of the block recruitable sub-persons of the target store block. And when the number of the sub recruiters in the target store block is equal to the number of available recruiters in the target store block, all the offline recruiting stores in the target store block are the target offline recruiting stores.

When the number of the sub-recruiters in the block of the to-be-determined target store block is less than the number of available recruiters in the block, an ordered list of the off-line recruiting stores can be calculated according to the historical task statistics value of each off-line recruiting store in the block of the target store, the number of the available recruiters of each off-line recruiting store is sequentially accumulated until the number of the sub-recruiters in the block of the target store block is met, and therefore each target off-line recruiting store in the block of the to-be-determined target store is determined.

At this time, the system may return the determined name and ID of the target offline recruitment store to a front-end display interface of the system so that the operator can see to which offline recruitment stores the recruitment order should be sent.

And S240, respectively sending each recruitment order to the corresponding target offline recruitment store.

And automatically associating and sending each recruitment order and the ID of the corresponding target offline recruitment store by the system, and recording the association and the sending in an order distribution table. And after the recruitment service personnel of the recruitment store are logged in the system, the recruitment order of the corresponding target factory can be received, and the recruitment work can be carried out according to the recruitment order.

It is worth pointing out that when the target offline recruitment store corresponding to the recruitment order of the target plant a coincides with the target offline recruitment store corresponding to the recruitment order of the target plant B, the recruitment orders of the target plant a and the target plant B can be simultaneously viewed and the recruitment work can be simultaneously carried out for the target plant a and the target plant B after the recruitment service personnel login system of the coinciding target offline recruitment store.

And S250, executing an order distribution scheme matched with the employment conveying grade according to the employment conveying grade of the target factory.

The present embodiment proposes only an order allocation scheme for a target plant with an industrial transportation level being the second level, and the order allocation scheme for a target plant with another industrial transportation level is not particularly limited.

For the sake of brevity, the present embodiment is not explained in detail herein, and reference is made to the aforementioned embodiments for further description.

According to the technical scheme, when the worker conveying type of the target plant is the second type, if the target area matched with the target plant recruitment order is determined, and the number of available recruiters in the target area is larger than the number of regional recruiters needing to recruit the target area, partial target store blocks are determined in the target area according to the distance between each store block in the target area and the target plant; and if the number of available recruiting persons in the block of the target store block is greater than the number of sub-persons of block recruiting persons needing to recruit the target store block, determining partial target processing nodes in the target store block according to the historical task statistics value of each offline recruiting store in the target store block.

Compared with the technical scheme that the target offline recruitment stores are determined according to the absolute distance between the target factory and each offline recruitment store, each offline recruitment store is divided into areas, the preset area of the distributed orders is determined firstly, then the store areas of the distributed orders are determined in the preset area, and the offline recruitment stores of the distributed orders are determined in the store areas again.

EXAMPLE III

Fig. 4 is a schematic structural diagram of a task allocation apparatus according to a third embodiment of the present invention, which is applicable to a case where a task to be processed of a target node is allocated to each processing node matched with the target node to be completed when a processing node cluster exists.

As shown in fig. 4, the task assigning apparatus specifically includes: a task demand number determination module 310, a target processing node determination module 320, and a task assignment module 330. Wherein the content of the first and second substances,

a task demand quantity determining module 310, configured to determine, according to one or more to-be-processed tasks issued by one or more target nodes, a task demand quantity matched with each to-be-processed task;

a target processing node determining module 320, configured to determine, according to the location information of the target node, the location information of each processing node block in each preset region, the number of processing resources possessed by each processing node, the number of task demands, and a ratio of the number of processing resources demanded in different preset regions to the number of tasks, at least one target processing node in at least one target processing node block in at least one target region corresponding to each to-be-processed task; each preset area comprises at least one processing node block, and each processing node block comprises at least one processing node;

the task allocation module 330 is configured to send each to-be-processed task to the corresponding target processing node.

According to the technical scheme, the different difficulty degrees of the processing resources in different areas for executing the tasks to be processed are considered, the required number of the tasks is not only referred to when the target processing nodes corresponding to the tasks to be processed are determined, but also the task completion effect of the target processing nodes in different areas is ensured by combining the ratio of the required number to the number of the tasks in different areas; in the above technical solution, after the target processing node block matching the to-be-processed task is determined, the target processing node matching the to-be-processed task is determined from the target processing node block, and in contrast to the technical solution in which the target processing node is determined only according to the absolute distance between the target node and each processing node, when a plurality of processing nodes are close to each other to form a processing node block, the problem that the to-be-processed task of the same target node can only be allocated to a specific processing node, and further the task resources among the processing nodes in the node block are unbalanced can be avoided.

Further, the above apparatus further comprises: the processable task calculating module is used for determining the processable task quantity of each preset area according to the ratio of the required quantity of the processing resources in different preset areas to the task quantity and the quantity of the processing resources in each preset area;

wherein the area processable task number is used for determining at least one target area in each preset area.

Further, the target processing node determining module 320 is specifically configured to sort the preset regions from near to far from the target node;

sequentially acquiring a preset area as a current processing preset area;

and accumulating the area processable task number of the current processing preset area into an area processable task statistic value, and taking the current processing preset area as a target area until the area processable task statistic value is greater than or equal to the task required number.

Specifically, the target processing node determining module 320 includes: a target processing node first determination unit, a target area determination unit, a target processing node second determination unit, and a target processing node block first determination unit, wherein,

a target processing node first determination unit configured to, if the area-processable task statistic is equal to the task required number, take each processing node block in the target area as a target processing node block, and take each processing node in each processing node block in the target area as a target processing node;

a target area determining unit, configured to divide the target area into a confirmed target area and an undetermined target area if the area-processable task statistics are greater than the number of task demands, where the undetermined target area is the one that is farthest from the target node;

a second determination unit of target processing nodes, configured to take each processing node block in the confirmation target area as a target processing node block, and take each processing node in each processing node block in the confirmation target area as a target processing node;

a target processing node block first determining unit, configured to determine, according to a difference between the area processable task statistic and the task required number and an area processable task number of the to-be-determined target area, an area subtask required number corresponding to the to-be-determined target area, and determine at least one target processing node block in the to-be-determined target area according to a distance between each processing node block in the to-be-determined target area and the target node and the area subtask required number.

Further, the target processing node block first determining unit is specifically configured to:

Specifically, the target processing node determining module 320 includes: a target processing node third determination unit, a target processing node block first determination unit, a target processing node fourth determination unit, and a target processing node fifth determination unit, wherein,

a third determination unit of target processing nodes, configured to take each processing node in the block of target processing nodes as a target processing node if the block processable task statistic is equal to the required number of area subtasks;

a target processing node block first determining unit, configured to divide the target processing node block into a confirmed target processing node block and an undetermined target processing node block if the block processable task statistics are greater than the area subtask required number, where the undetermined target processing node block is one of the target processing node blocks that is farthest from the target node in the undetermined target area;

a target processing node fourth determination unit configured to determine each processing node in the confirmation target processing node block as a target processing node;

a fifth determining unit of the target processing node, configured to determine, according to the difference between the block processable task statistics and the area subtask required number and the processable task number of the block of the to-be-determined target processing node, the block subtask required number corresponding to the block of the to-be-determined target processing node, and determine at least one target processing node in the block of the to-be-determined target processing node according to the size of the historical task statistics of each processing node in the block of the to-be-determined target processing node and the block subtask required number.

Further, the target processing node fifth determining unit is specifically configured to:

Specifically, the above apparatus further comprises: and the processing node block dividing module is used for dividing at least one processing node into at least one processing node block before determining at least one target processing node in at least one target processing node block corresponding to each task to be processed according to the target node and the position information of each processing node block, the number of processing resources possessed by each processing node and the required number.

Further, the above apparatus further comprises: a processing node block repartitioning module to repartition at least two processing nodes including at least one new processing node into at least one processing node block if it is determined that the at least one new processing node exists.

Further, the above apparatus further comprises: and the historical task statistic initialization module is used for initializing the historical task statistics of each processing node in the target processing node block if at least one processing node is newly added in the target processing node block after the processing node block is re-divided into at least one processing node block.

Specifically, the target node is a target factory, the task to be processed is a recruitment order, the processing node is an offline recruitment store, and the processing resource is a recruitment service person.

Further, the above apparatus further comprises: and the recruitment transportation level judgment module is used for judging that the recruitment transportation level of the target plant corresponding to each recruitment order is a second level before determining at least one target processing node in at least one target processing node block in at least one target area corresponding to each task to be processed according to the position information of the target node, the position information of each processing node block in each preset area, the number of processing resources possessed by each processing node, the number of required tasks and the ratio of the number of required processing resources to the number of tasks in different preset areas.

Further, the employment conveying grade judging module is specifically configured to:

calculating the accumulated sum of the total working hours of the historical delivery users of each factory in the set time period;

and judging the recruitment transportation grade of the target factory according to the ratio of the accumulated sum of the accumulated total working hours corresponding to the target factory in the total working hours.

Specifically, if the ratio of the accumulated total working duration corresponding to the target plant to the sum of the total working duration belongs to a first ratio range, judging that the work transportation grade of the target plant is a first grade;

The task allocation device can execute the task allocation method provided by any embodiment of the invention, and has corresponding functional modules and beneficial effects for executing the task allocation method.

Example four

Fig. 5 is a schematic diagram of a hardware structure of a computer device according to a fourth embodiment of the present invention, and as shown in fig. 5, the computer device includes:

one or more processors 410, one processor 410 being exemplified in FIG. 5;

a memory 420;

the computer device may further include: an input device 430 and an output device 440.

The processor 410, the memory 420, the input device 430 and the output device 440 in the computer apparatus may be connected by a bus or other means, and fig. 5 illustrates the connection by a bus as an example.

The memory 420, which is a non-transitory computer-readable storage medium, may be used for storing software programs, computer-executable programs, and modules, such as program instructions/modules corresponding to a task allocation method in an embodiment of the present invention (for example, the task requirement number determination module 310, the target processing node determination module 320, and the task allocation module 330 shown in fig. 4). The processor 410 executes various functional applications and data processing of the computer device by executing software programs, instructions and modules stored in the memory 420, namely, a task allocation method of the above-described method embodiments.

The memory 420 may include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area may store data created according to use of the computer device, and the like. Further, the memory 420 may include high speed random access memory, and may also include non-transitory memory, such as at least one magnetic disk storage device, flash memory device, or other non-transitory solid state storage device. In some embodiments, memory 420 may optionally include memory located remotely from processor 410, which may be connected to the terminal device via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.

The input device 430 may be used to receive input numeric or character information and generate key signal inputs related to user settings and function control of the computer apparatus. The output device 440 may include a display device such as a display screen.

EXAMPLE five

An embodiment of the present invention further provides a storage medium containing computer-executable instructions, which when executed by a computer processor, perform a method for task allocation, the method including:

Optionally, the computer-executable instructions, when executed by a computer processor, may be further configured to implement a technical solution of a task allocation method provided in any embodiment of the present invention.

From the above description of the embodiments, it is obvious for those skilled in the art that the present invention can be implemented by software and necessary general hardware, and certainly, can also be implemented by hardware, but the former is a better embodiment in many cases. Based on such understanding, the technical solutions of the present invention may be embodied in the form of a software product, which can be stored in a computer-readable storage medium, such as a floppy disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a FLASH Memory (FLASH), a hard disk or an optical disk of a computer, and includes several instructions for enabling a computer device (which may be a personal computer, a server, or a network device) to execute the methods according to the embodiments of the present invention.

It should be noted that, in the embodiment of the task allocation apparatus, the included units and modules are merely divided according to functional logic, but are not limited to the above division as long as the corresponding functions can be implemented; in addition, specific names of the functional units are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present invention.

It is to be noted that the foregoing is only illustrative of the preferred embodiments of the present invention and the technical principles employed. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, although the present invention has been described in greater detail by the above embodiments, the present invention is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present invention, and the scope of the present invention is determined by the scope of the appended claims.

Claims

1. A task allocation method, comprising:

2. The method of claim 1, further comprising: determining the number of tasks capable of being processed in each preset area according to the ratio of the number of processing resource demands in different preset areas to the number of tasks and the number of processing resources in each preset area;

3. The method of claim 2, wherein determining at least one target area corresponding to each task to be processed according to the location information of the target node, the location information of each processing node block in each preset area, the number of processing resources possessed by each processing node, the number of task demands, and a ratio of the number of processing resource demands to the number of tasks in different preset areas comprises:

sequencing the preset areas from near to far according to the distance from the target node;

sequentially acquiring a preset area as a current processing preset area;

4. The method of claim 3, wherein determining at least one target processing node block in at least one target area corresponding to each to-be-processed task according to the location information of the target node, the location information of each processing node block in each preset area, the amount of processing resources possessed by each processing node, the number of task demands, and a ratio of the number of processing resource demands to the number of tasks in different preset areas comprises:

if the area-processable task statistic is equal to the task required number, taking each processing node block in the target area as a target processing node block, and taking each processing node in each processing node block in the target area as a target processing node;

if the area processable task statistic is larger than the task required quantity, dividing the target area into a confirmed target area and an undetermined target area, wherein the undetermined target area is the target area which is farthest away from the target node;

taking each processing node block in the confirmation target area as a target processing node block, and taking each processing node in each processing node block in the confirmation target area as a target processing node;

5. The method of claim 4, wherein determining at least one target processing node block in the pending target area based on a distance between each processing node block in the pending target area and the target node and the required number of subtasks for the area comprises:

6. The method of claim 5, wherein determining at least one target processing node in at least one target processing node block in at least one target area corresponding to each to-be-processed task according to the location information of the target node, the location information of each processing node block in each preset area, the amount of processing resources possessed by each processing node, the number of task demands, and a ratio of the number of processing resource demands to the number of tasks in different preset areas comprises:

if the block processable task statistics are equal to the regional subtask required number, taking each processing node in the target processing node block as a target processing node;

if the block processable task statistics are larger than the required number of the regional subtasks, dividing the target processing node block into a confirmed target processing node block and a pending target processing node block, wherein the pending target processing node block is the target processing node block which is farthest away from the target node in the pending target region;

7. The method of claim 6, wherein determining at least one target processing node in the block of pending target processing nodes based on the size of historical task statistics for each processing node in the block of pending target processing nodes and the number of block subtask requirements comprises:

sequentially acquiring a processing node as a current processing node;

and accumulating the node processable task number of the current processing node into a node processable task statistic value, and taking the current processing node as a target processing node until the node processable task statistic value is greater than or equal to the required block subtask number.

8. The method according to claim 1, before determining at least one target processing node in at least one target processing node block corresponding to each of the tasks to be processed according to the location information of the target node and each processing node block, the amount of processing resources provided by each processing node, and the required amount, further comprising:

at least one processing node is divided into at least one processing node block, and the at least one processing node block is divided into at least one preset area.

9. The method of claim 8, further comprising:

if it is determined that at least one new processing node exists, at least two processing nodes including the at least one new processing node are re-divided into at least one processing node block.

10. The method of claim 9, further comprising, after the repartitioning into at least one processing node block:

11. The method of claim 1, wherein the target node is a target plant, the task to be processed is a recruitment order, the processing node is an offline recruitment store, and the processing resource is a recruitment service personnel.

12. The method of claim 11, further comprising, before determining at least one target processing node in at least one target processing node block in at least one target area corresponding to each of the tasks to be processed according to the location information of the target node, the location information of each processing node block in each preset area, the amount of processing resources provided by each processing node, the number of tasks required, and a ratio of the number of processing resource required to the number of tasks in different preset areas, the method further comprising:

13. The method of claim 12, wherein determining the recruitment transportation grade for the target facility for each of the recruitment orders comprises:

14. The method of claim 13, wherein determining the recruitment transportation level of the target plant based on the cumulative sum of the total length of employment corresponding to the target plant comprises:

15. A task assigning apparatus, comprising:

16. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor when executing the program implements a method as claimed in any one of claims 1 to 14.

17. A computer-readable storage medium, on which a computer program is stored, which program, when being executed by a processor, carries out the method of any one of claims 1 to 14.