KR20180065840A - Method and apparatus for automatically assigning appropriate personnel - Google Patents

Abstract

Provided are a method to automatically assign an appropriate person in charge and an apparatus thereof, to complete a project at the least cost. According to the present invention, a business assignment apparatus comprises a storage unit and a business scheduling module. The business scheduling module comprises a calculation unit and a backward tracing unit. The calculation unit generates a minimum organization cost to minimize the sum of costs for m projects based on information about ability and cost associated with each of n personnel IDs, and generates at least one minimum organization cost schedule satisfying the minimum organization cost, wherein m is an integer of 1 or more, and each of the m projects includes at least one work, and the at least one work is associated with one of the n personnel IDs. The backward tracing unit backwardly traces the at least one minimum organization cost schedule based on minimization of a standard deviation of the amount of works associated with the n personnel IDs to select an optimal schedule from the at least one organization cost schedule.

Description

[0001] METHOD AND APPARATUS FOR AUTOMATICALLY ALLOCATING APPROPRIATE DISTRIBUTOR [0002]

The present invention relates to business management techniques, and more particularly, to a method and apparatus for automatically assigning appropriate personnel to work performed on a computer-based basis.

Organizational performance managers are concerned with ways to achieve the best performance with the greatest efficiency to improve performance from the perspective of the organization as a whole. When an organization's work is composed of multiple projects and a project contains at least one task, the manager seeks the best performance for the organization's work by assigning the best work to the organization.

Job Assignment Algorithm has been studied for a long time. In particular, the Hungarian method for the assignment problem is known as an algorithm that can solve the minimum / maximum cost matching and assignment problem of the half-graph, and the time complexity is O (N ³ ).

In assigning tasks to members in a real organization, each task has characteristics and the tendencies of the members are different. Furthermore, for organizational permanence, it is necessary to equitize the workload of each member. However, the Hungarian algorithm has a problem that it is difficult to apply it to the reality because there is no consideration of the characteristics of the work, the tendency of the worker of the organization, and / or the workload between the workers.

1. The Hungarian method for the assignment problem, Naval Research Logistics Quarterly Volume 2, Issue 1-2, pages 8397, March 1955

Accordingly, in the present invention, consideration is given to the task orientation and work process characteristics of each individual member, and a suitable person is selected from the viewpoint of the whole organization including the project perspective including the plurality of tasks, Quot;

According to the embodiments of the present invention, a task assignment apparatus that automatically assigns an appropriate task person is provided. The apparatus includes a storage unit and a task scheduling module, wherein the task scheduling module includes an arithmetic unit and a backward tracing unit, and the arithmetic unit calculates information on the abilities and costs associated with each of the n employee IDs And generating at least one minimum organizational cost schedule that meets the minimum organizational cost, wherein m is an integer greater than or equal to 1, and wherein each of the m projects Wherein the at least one task is associated with one of the n employee IDs, and wherein the back-tracking unit is operable to associate the at least one minimum organizational cost schedule with a standard of the workload of the n employee IDs And selecting the optimal schedule among the at least one minimum organizational cost schedule by backtracking based on that the deviation is minimized Rock consists.

In one embodiment, the task scheduling module further includes a preprocessor, wherein the preprocessor calculates a capability value for each of the n employee IDs based on the performance element, the performance factor includes a degree of difficulty, Number of times, novelty, time based throughput, technology based throughput and performance.

In one embodiment, the backtrace may further be configured to determine, for the optimal schedule, the workload for each of the n employee IDs, each achieving costs for the m projects.

In one embodiment, the operation unit calculates the minimum organizational cost and the at least one minimum organizational cost schedule by calculating the cost for m projects in an invasive form with costs for m-1 projects according to the following equation Lt; / RTI >

In one embodiment, the backtrace may calculate in turn the cost of the project including the work associated with the employee ID where the workload of the n employee IDs is close to the average workload.

In one embodiment, the arithmetic unit may be any one of a Hungarian Algorithm, a Genetic Algorithm, a Non-deterministic Polynimial-time hard Algorithm, and a Dynamic Programming Algorithm Lt; / RTI >

In one embodiment, the operation unit may be further configured to receive workload information for at least one of the n employee IDs to generate the minimum organizational cost and the at least one minimum organizational cost schedule.

In one embodiment, the operation unit is further configured to generate, for the m-th project, the minimum organizational cost and the at least one minimum organizational cost schedule, and display an employee ID associated with the jobs contained in the m-th project .

According to embodiments of the present invention, a task assignment method is provided that automatically assigns an appropriate task person. The method includes receiving information about a capability and cost associated with each of the n employee IDs; Generating at least one minimum organizational cost schedule that meets the minimum organizational cost and the minimum organizational cost where the sum of costs for the m projects is minimized based on information about the attributes and costs associated with each of the n employee IDs Wherein each of the m projects includes at least one task, the at least one task is associated with one of the n employee IDs, the at least one minimum organizational cost schedule < RTI ID = 0.0 > Tracing back on the basis that the standard deviation of the workload of the n employee IDs is minimized to thereby select an optimal schedule from among the at least one minimum organizational cost schedule; and, in the optimal schedule, Determining a workload for each of the n employee IDs that each achieves, The steps of generating a minimum organizational cost schedule include a Hungarian Algorithm, a Genetic Algorithm, a Non-deterministic Polynimial-time hard Algorithm, a Dynamic Programming Algorithm, ≪ / RTI >

According to the present invention, the members of the organization take into consideration the individual job characteristics and job processing characteristics, while making the distribution of the work among the workers even more uniform, and in view of the project including the various jobs and the entire organization including the various projects Assign a person to complete the project with minimal cost.

FIG. 1 is a block diagram showing the organization of an organization to which a task assignment apparatus according to an embodiment of the present invention is applied.
FIG. 2 is a diagram illustrating an employee assignment table according to an exemplary embodiment of the present invention. Referring to FIG.
3 is a schematic block diagram illustrating the configuration of a task assignment apparatus according to an embodiment of the present invention.
FIG. 4 is a schematic flow diagram illustrating a process of a task assignment method according to an embodiment of the present invention.

Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings. Hereinafter, when it is determined that there is a possibility that the gist of the present invention may be unnecessarily blurred, a detailed description of known functions and configurations will be omitted. In addition, it should be understood that the following description is only an embodiment of the present invention, and the present invention is not limited thereto.

The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the present invention. For example, an element expressed in singular < Desc / Clms Page number 5 > terms should be understood as including a plurality of elements unless the context clearly dictates a singular value. In addition, in the specification of the present invention, it is to be understood that terms such as "include" or "have" are intended to specify the presence of stated features, integers, steps, operations, components, It is not intended that the use of the term exclude the presence or addition of one or more other features, numbers, steps, operations, components, parts, or combinations thereof.

As used herein, the term " block " or " part " means a functional part that performs at least one function or operation, and may be implemented in hardware or software or a combination of hardware and software. Also, a plurality of 'blocks' or 'sub-units' may be embodied in at least one processor integrated with at least one software module, except for 'blocks' or 'sub-units' that need to be implemented in specific hardware .

In addition, all terms used herein, including technical or scientific terms, unless otherwise defined, have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Commonly used predefined terms are to be interpreted as having a meaning consistent with the contextual meaning of the related art and are not to be construed as being excessively limited or extended unless explicitly defined otherwise in the specification of the present invention You should know.

Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings.

FIG. 1 is a block diagram showing the organization of an organization to which a task assignment apparatus according to an embodiment of the present invention is applied.

 According to one embodiment of the present invention, tasks can be divided into units (individual), projects, and organizational units. The organization includes a plurality of projects, and each project can consist of at least one task. The task assignment device can rearrange the unit tasks (tasks), project tasks (projects), and organization tasks (organization) that the organization should deal with to the manager in a necessary perspective in each category. When assigning a unit job (task), an administrator must know who is the employee (employee ID) who can finish the least cost of the job. At this time, it is not necessary to wait for the project ), And how to distribute them so that all participants can perform similarly. Assignment criteria for the entire organization Determine how to allocate the organization's performance and individual performance to maximize performance. In order to allocate work to an employee (employee ID), it is necessary to calculate an employee's ability value. The performance factor of the individual may be considered, but not limited thereto.

1. Difficulty of work

2. Type of operation

3. Number of repetitions of the task

4. Novelty

5. Time base throughput

6. Technology base service throughput

7. Performance

In other words, the ability of the employee to perform a specific task can be calculated in consideration of the work characteristics of each employee and the characteristics of the work process. The ability value is an integer value between 0 and 100, and can be calculated by reflecting the weight on the individual performance element.

FIG. 2 is a diagram illustrating an employee assignment table according to an exemplary embodiment of the present invention. Referring to FIG.

The task allocation table according to the embodiment of the present invention includes information on an employee ID, an operation ID (assignment operation) in which the employee participated, a work amount of the employee, a capability value of the employee, and a cost reflecting the wage of the employee can do. For example, in the data with employee ID 1, the employee performs Job 1 and Job 3, the workload of the employee is 50, the ability is 70, and the cost of the employee is 6000.

The workload is a value between 0 and 100, and can not exceed 100. In addition, it can be assumed that the distribution of workload among employees is assigned evenly to employees as the standard deviation is smaller.

3 is a schematic block diagram illustrating the configuration of a task assignment apparatus according to an embodiment of the present invention.

The task assignment apparatus 300 may include a task assignment scheduling module 310 and a storage unit 320.

The task assignment scheduling module 310 may include a preprocessor 312, an operation unit 314, and a tracing unit 316.

The preprocessing unit 312 calculates a capability value for each of the employee IDs on the basis of the performance element, and the performance element includes the degree of difficulty, type, repetition frequency, novelty, time base processing rate, . For example, if the employee ID (1) has a high degree of difficulty in the past work, the type of work is knowledge-based, the number of repetition is several times, the proportion of new work is high, If the base workload is high and the performance is good, the employee ID (1) will have a high ability. In one embodiment, a numerical value of a specific ability value can be calculated according to the distinction and weight of the performance elements. Those skilled in the art will be able to conceive of a method of calculating the number of abilities in a variety of ways.

The calculation unit 314 calculates a minimum organizational cost that minimizes the sum of the costs for the m projects based on the information about the attributes and cost associated with each of the n employee IDs and at least one minimum organizational cost And may be configured to generate schedules. Wherein m is an integer equal to or greater than one, each of the m projects including at least one task, and the at least one task is associated with one of the n employee IDs.

In one embodiment, the operation unit 314 may perform an operation for the purpose of minimizing the cost for m projects, and the objective function may be defined as follows.

Here, the constraints are as follows.

m: Number of projects

n: Number of employee IDs

x _ij : the participation rate of the employee j on the project i (the total participation rate of the employee j is the workload of the employee j)

a _j : Stats of employee ID j

c _j : Cost of employee ID j

In one embodiment, the computing unit 314 computes the costs for m projects in an invasive form with costs for m-1 projects according to the following equation to calculate the minimum organizational cost and the at least one minimum organizational cost May be further configured to generate schedules.

The arithmetic operation unit 314 performs arithmetic operation using any one of Hungarian Algorithm, Genetic Algorithm, Non-deterministic Polynimial-time hard Algorithm and Dynamic Programming Algorithm .

The computing unit 314 may be further configured to receive workload information for at least one of the n employee IDs to generate the minimum organizational cost and the at least one minimum organizational cost schedule.

The computing unit 314 may be further configured to generate the minimum organizational cost and the at least one minimum organizational cost schedule for the mth project and to display an employee ID associated with the jobs contained in the mth project.

The traceback unit 316 traverses the at least one minimum organizational cost schedule based on minimization of the standard deviation of the workloads of the n employee IDs to select an optimal schedule among the at least one minimum organizational cost schedule .

The traceback unit 316 may be further configured to determine the workload for each of the n employee IDs, each of which achieves the costs for the m projects, making up the optimal schedule.

The traceback unit 316 may calculate the cost of the project in which the workload of the n employee IDs is included in the work associated with the employee ID nearest to the average workload.

In one embodiment, task assignment scheduling module 310 may include application specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays Microprocessors, microprocessors, microprocessors, microprocessors, and the like.

In one embodiment, task assignment scheduling module 310 may be implemented with firmware / software codes that are executable on a hardware platform that allows at least one function or operation to be performed. The software code may be implemented by software applications written in a suitable programming language. The software code may be stored in its own memory of the task assignment scheduling module 310 or may be stored in a separate storage unit 320 and then called and executed.

The storage unit 320 may be a flash memory type, a hard disk type, a MultiMedia Card (MMC), a card type memory (for example, SD (Secure Digital) card or XD (Random Access Memory), SRAM (Static Random Access Memory), ROM (Read Only Memory), EEPROM (Electrically Erasable Programmable Read-Only Memory), PROM (Programmable Read-Only Memory) A magnetic disk, a magnetic disk, and an optical disk. However, those skilled in the art will recognize that the embodiment of the storage unit 220 is not limited thereto.

FIG. 4 is a schematic flow diagram illustrating a process of a task assignment method according to an embodiment of the present invention.

The method begins with step S410 of generating a minimum organizational cost schedule. In one embodiment, prior to this step, information about the attributes and costs associated with each of the n employee IDs may be input. Further, in one embodiment, the ability values associated with each of the n employee IDs can be calculated by considering the following individual performance factors, but the present invention is not limited thereto.

1. Difficulty of work

2. Type of operation

3. Number of repetitions of the task

4. Novelty

5. Time base throughput

6. Technology base service throughput

7. Performance

In other words, the ability of the employee to perform a specific task can be calculated in consideration of the work characteristics of each employee and the characteristics of the work process. The ability value is an integer value between 0 and 100, and can be calculated by reflecting the weight on the individual performance element.

Step S410 further comprises: determining a minimum organizational cost that minimizes the sum of costs for the m projects based on information about the attributes and cost associated with each of the n employee IDs, and at least one minimum And generating an organization cost schedule. Wherein m is an integer greater than or equal to one, each of the m projects including at least one task, and the at least one task may be associated with one of the n employee IDs. In one embodiment, the step of generating at least one minimum organizational cost schedule comprises the steps of: Hungarian Algorithm, Genetic Algorithm, Non-deterministic Polynimial-time hard Algorithm, Algorithm (Dynamic Programming Algorithm).

Thereafter, step S420 is a step of tracing back at least one minimum organizational cost schedule based on minimization of the standard deviation of the work amounts of n employee IDs, thereby selecting an optimal schedule among at least one minimum organizational cost schedule. At this stage, it is possible to determine the workload for each of the n employee IDs, each of which achieves the costs for m projects, which constitute the optimal schedule. In one embodiment, the workload of n employee IDs can be calculated in turn from the cost of the project that contains the work associated with the employee ID nearest the average workload.

Thereafter, step S430 is to determine the workload for each of the n employee IDs, each of which achieves the costs for the m projects, making up the optimal schedule.

Thereafter, step S440 may be further configured to generate the minimum organizational cost and the at least one minimum organizational cost schedule for the m-th project, and to display the employee ID associated with the jobs contained in the m-th project have.

As will be appreciated by those skilled in the art, the present invention is not limited to the examples described herein, but may be variously modified, rearranged and replaced without departing from the scope of the present invention. For example, the various techniques described herein may be implemented in hardware or software, or a combination of hardware and software. Thus, certain aspects or portions of an analysis machine for software safety analysis in accordance with the present disclosure may be implemented with one or more computer programs executable by a general purpose or special purpose microprocessor, micro-controller, or the like. A computer program according to an embodiment of the present invention may be stored in a storage medium readable by a computer processor or the like such as a nonvolatile memory such as EPROM, EEPROM, flash memory device, a magnetic disk such as an internal hard disk and a removable disk, CDROM disks, and the like. Also, the program code (s) may be implemented in assembly language or machine language, and may be implemented in a form that is transmitted over electrical wiring or cabling, optical fiber, or any other form of transmission medium.

Although an exemplary embodiment of a method for automatically assigning an appropriate task person is mainly described herein with reference to various drawings, other similar embodiments may be used. And all changes and modifications that fall within the true spirit and scope of the present invention are intended to be embraced by the following claims.

Claims (10)

As a task assignment device,
Storage, and
A task scheduling module,
The task scheduling module includes an operation unit and backward tracing,
Wherein the calculation unit is configured to calculate a minimum organizational cost that minimizes the sum of costs for the m projects based on the information about the attributes and costs associated with each of the n employee IDs and at least one minimum organizational cost schedule Wherein each of the m projects includes at least one task, and the at least one task is associated with one of the n employee IDs,
Wherein the backtracking unit is configured to backtrack the at least one minimum organizational cost schedule based on minimizing the standard deviation of the workload associated with the n employee IDs to select an optimal schedule among the at least one organizational cost schedule. Task assignment device. The method according to claim 1,
The task scheduling module may further comprise a preprocessor,
Wherein the preprocessing unit calculates a capability value for each of the n employee IDs on the basis of the performance element, and the performance element includes a difficulty level, a type, a repetition number, a novelty, a time base based throughput, Includes a task assignment device. The method according to claim 1,
Wherein the backtracking unit is further configured to determine, in the optimal schedule, a workload for each of the n employee IDs, each of which achieves costs for the m projects. The method according to claim 1,
The operation unit is further configured to generate the minimum organizational cost and the at least one minimum organizational cost schedule by calculating the cost for m projects in an invasive form with costs for m-1 projects according to the following equation , Task assignment device.

The method according to claim 1,
Wherein the backward tracking unit sequentially counts the cost of the project including the work associated with the employee ID whose workload of the n employee IDs is close to the average workload. The method according to claim 1,
The operation unit may be operated using any one of Hungarian Algorithm, Genetic Algorithm, Non-deterministic Polynimial-time hard Algorithm and Dynamic Programming Algorithm A task allocation device, further configured. The method according to claim 6,
Wherein the operation unit is further configured to receive workload information for at least one of the n employee IDs to generate the minimum organizational cost and the at least one minimum organizational cost schedule. 5. The method of claim 4,
Wherein the operation unit is further configured to generate the minimum organizational cost and the at least one minimum organizational cost schedule for the mth project and to display an employee ID associated with the jobs contained in the mth project. As a task assignment method,
receiving information on the ability and cost associated with each of the n employee IDs;
Generating at least one minimum organizational cost schedule that meets the minimum organizational cost and the minimum organizational cost where the sum of costs for the m projects is minimized based on information about the attributes and costs associated with each of the n employee IDs Wherein m is an integer greater than or equal to one, each of the m projects including at least one task, the at least one task associated with one of the n employee IDs,
Tracing back the at least one minimum organizational cost schedule based on minimizing the standard deviation of the workloads of the n employee IDs to select an optimal schedule among the at least one organizational cost schedule;
Determining an amount of work for each of the n employee IDs achieving costs for the m projects, respectively, in the optimal schedule,
The step of generating the at least one minimum organizational cost schedule may comprise the steps of: generating a Hungarian Algorithm, a Genetic Algorithm, a Non-deterministic Polynimial-time hard Algorithm, a Dynamic Programming Algorithm ). ≪ / RTI > 20. A computer-readable medium having recorded thereon a program, the program comprising instructions, and wherein the instructions, when executed by a computer, perform the method of claim 9.

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