Work plan drafting device

Abstract

A work plan drafting device (7) comprises: a storage unit that stores a plurality of tasks and task information (task list (D1)) that is related to the tasks; a task bundling unit (3) that performs bundling of the plurality of tasks on the basis of the task information to generate a plurality of task groups, and assigns the same bundling identification number to tasks allocated to the same task group; and a work planning unit (4) that allocates, to the same resource, the tasks to which the same bundling identification number is assigned. The storage unit stores a bundling policy (bundling policy information (D2)) including a constraint condition between the plurality of task groups to be generated, and the task bundling unit (3) generates the task groups on the basis of the bundling policy.

Description

Work planning device

[0001] The present invention relates to a work planning device that creates a work plan while grouping together a plurality of tasks that are to be performed by resources including people and physical materials.

[0002] In recent years, the adoption of field service management (FSM) has been increasing across various industries. FSMs typically include functions for generating tasks, developing resource allocation plans, and managing the progress of actual on-site work. Here, resources refer to individual personnel resources such as workers, teams or business entities composed of multiple personnel resources, and physical resources such as materials. In particular, in the development of work planning, not only manual resource allocation using a user interface (UI) has been adopted, but also resource allocation methods using machine learning and other computational methods have been developed, resulting in a demand for further advancements. In such work planning, tasks are typically handled individually and assigned chronologically to the same or different resources. However, some businesses need to bundle multiple tasks (hereinafter referred to as "bundling") and assign them to the same resource in a sequential manner, thereby reducing travel time, material costs, labor costs, and outsourcing costs associated with the same resources. In addition, particularly when personnel resources are performing multiple tasks, it may be necessary to consider reducing overtime hours for workers and ensuring that they are not solely tasked with unmotivated tasks or heavy work.

[0003] Background art in this technical field is the invention described in Patent Document 1. The abstract of this document states, "A method for workflow assignment is provided, including: determining, for each of a plurality of tasks, one or more task parameters associated with the task; and generating, in response to an actionable event, a workflow in which one or more individuals each perform at least one of the plurality of tasks based on the one or more task parameters."

[0004] Special Publication No. 2022-527961

[0005] Ishii: "Work satisfaction and work difficulty" as seen in a survey of welfare and nursing care sites, Welfare Social Science Lectures, Vol. 1 (2009); Kanaoka: "Job satisfaction and improvement methods among employees of agricultural production corporations," Hokkaido Agricultural Research Center Agricultural Management Research, No. 108, pp. 54-66 (2013); Ohno: "A study on work at a ryokan and work ease / work satisfaction - Based on the opinions of front-line service employees at Ikaho Onsen Ryokan Hotel Tenbo," Journal of the Japan Institute of Tourism Research, Vol. 28, No. 2, pp. 57-67 (2017)

[0006] According to Non-Patent Documents 1 to 3, when allocating tasks to resources, it is important to consider the impact on individual resources, such as the amount and difficulty of the tasks, and the working environment, in addition to the impact on the entire business entity, such as business efficiency and business expenses. According to Patent Document 1, it is possible to create a work plan that allocates each task to a human resource individually, taking into account the priority of the task, the required skills, the time required to perform the task, etc. However, it is difficult to appropriately improve work efficiency, reduce business expenses, improve the working environment, etc., according to the needs of the business or business entity by allocating multiple tasks to the same resource.

[0007] SUMMARY OF THE INVENTION It is therefore an object of the present invention to provide a work planning device that can allocate multiple tasks to the same resource in accordance with the objectives prioritized by the business entity.

[0008] To achieve the above object, the work plan creation device of the present invention is characterized by comprising: a storage unit that stores a plurality of tasks and task information that is information about the tasks; a task bundling unit that generates a plurality of task groups by bundling the plurality of tasks based on the task information and assigns the same bundling identification number to tasks assigned to the same task group; and a work planner that assigns tasks assigned the same bundling identification number to the same resource. Other aspects of the present invention will be described in the embodiments described below.

[0009] According to the present invention, it is possible to create a work plan that assigns multiple tasks to the same resource in accordance with the objectives that an enterprise prioritizes, such as improving business efficiency, reducing business expenses, and improving the working environment.

[0010] 1 is a block diagram showing functions of a work planning device according to an embodiment; FIG. 2 is a block diagram showing a computer of a work planning device according to an embodiment; FIG. 3 is a diagram showing an example of a task list among various information stored in a mass storage unit DB; FIG. 4 is a diagram showing an example of bundling policy information among various information stored in a mass storage unit DB; FIG. 5 is a flowchart showing processing by a task bundling unit; FIG. 6 is a diagram showing an example of a task list D1 to which a bundling identification number has been assigned by processing by the task bundling unit; FIG. 7 is a flowchart showing processing by a work planning unit; FIG. 8 is a flowchart showing processing by a screen output unit; FIG. 9 is a diagram showing an example of a screen output by the screen output unit;

[0011] Hereinafter, an embodiment of the present invention will be described in detail with reference to the drawings. Fig. 1A is a block diagram showing the functions of a work planning device 7 according to an embodiment. Fig. 1B is a block diagram showing a computer of the work planning device 7 according to an embodiment. The work planning device 7 is a work planning device that links tasks and resources in chronological order.

[0012] In FIG. 1B , the computer of the work plan creation device 7 includes a CPU (Central Processing Unit) 71, a storage unit 72, a communication I / F (Interface) 73, an input / output I / F 74, and a DSP (Digital Signal Processor) 75. The storage unit 72 includes a RAM 72a, a ROM 72b, and a hard disk drive (HDD) 72c. The communication I / F 73 is connected to a communication circuit 76. The input / output I / F 74 is connected to an input / output device 77 (e.g., the display device 6, the input device 8). The ROM 72b stores programs executed by the CPU 71 and the DSP 75, various data, and the like. The CPU 71 and the DSP 75 execute these programs to realize various functions. Here, the HDD 72c corresponds to a non-volatile mass storage unit (DB). Note that this embodiment is not limited to a single device, and may be implemented as a work planning system in which multiple servers, etc., work together.

[0013] The work plan formulation device 7 realized by using a computer has the functions of a task bundling unit 3, a work planner 4, and a screen output unit 5, when the processing contents of the processing unit CPU are expressed in terms of processing functions.

[0014] The task bundling unit 3 generates multiple task groups by bundling multiple tasks based on multiple tasks and task information (task list D1) that is information about the tasks, and assigns the same bundling identification number to tasks assigned to the same task group. The task bundling unit 3 also generates the task groups based on a bundling policy (bundling policy information D2) that includes constraints between the multiple task groups to be generated. The task bundling unit 3 generates the task groups by performing a mathematical optimization process based on the task information and the bundling policy.

[0015] The work planning unit 4 assigns tasks that have the same bundling identification number to the same resource, and also plans for the same resource to execute the tasks in chronological order.

[0016] The work planning device 7 further stores a task list D1 (task information), bundling policy information D2 (bundling policy), and a work planning program Pr in the non-volatile mass storage unit DB.

[0017] The various types of information stored in the nonvolatile mass storage unit DB in the work planning device 7 of Fig. 1 are as follows: First, an example of the task list D1 is shown in Fig. 2.

[0018] 2 is a diagram showing an example of a task list D1 among various information stored in the mass storage unit DB. The task list D1 includes a task identification number D11, task content D12, task occurrence location D13, scheduled task execution period D14, task difficulty level D15, task environment information D16, task type information D17, and skill information D18.

[0019] The task identification number D11 stores a number for uniquely identifying a task. The task content D12 stores the content of the task. The task occurrence location D13 stores information such as latitude and longitude as the location where the task is occurring. Here, the task occurrence location D13 is not limited to latitude and longitude, as long as it stores information that can identify the location. The planned task execution period D14 stores the planned period for executing the task, such as the planned start date of the task or the deadline date of the task.

[0020] The task difficulty level D15 stores values ​​such as 1 to 5 in order of ease as a level of difficulty for each task. The task environment information D16 stores values ​​such as 1 to 5 in order of difficulty or danger as a value indicating whether the environment for performing each task is well-maintained or poor (or dangerous). The task type information D17 stores information indicating the classification of the task, such as whether the task is related to equipment or the surrounding environment. It is expected that various values ​​will be stored for the difficulty level and environment classification for each task and the task type depending on the business entity, and is not limited to the above. The skill information D18 stores information indicating the skills required to perform the task.

[0021] FIG. 3 illustrates an example of bundling policy information D2 among various types of information stored in the mass storage unit DB. The bundling policy information D2 includes information indicating the importance of each indicator (e.g., weighting value D21) to be emphasized when bundling, and the values ​​of variables that act as constraints when bundling (e.g., bundling distance D22, number of items to be bundled D23, and whether bundling skill matching is required D24). Indicators include minimizing travel distance, reducing business expenses, averaging resource loads, and averaging job satisfaction. That is, the task bundling unit 3 generates indicators related to the load on resources when combining multiple tasks, the job satisfaction of personnel resources, or their motivation. Job satisfaction refers to the sense of accomplishment and fulfillment felt by personnel resources when performing tasks. As described above, resources refer to a single personnel resource such as a worker, a group, team, or business entity composed of multiple personnel resources, or material resources such as materials.

[0022] The bundling policy information D2 here includes a weighting value D21, a bundling distance D22, a bundling count D23, and a bundling skill match requirement D24. The weighting value D21 stores a weighting value indicating the importance of each index that is emphasized when bundling. The bundling distance D22 stores information on the maximum distance between tasks to be bundled. The bundling count D23 stores information on the maximum number of tasks to be bundled. The bundling skill match requirement D24 stores information on whether the skills required for the tasks to be bundled must match. For example, a value of 1 is stored if a match is required, and a value of 0 is stored if not.

[0023] This embodiment does not limit the content of the tasks to be performed or the fields in which it can be used, but for ease of understanding, equipment maintenance and vegetation management work in the field of power systems will be described as examples.

[0024] 1, we will now explain the various processing functions executed by the CPU 71. First, the task bundling unit 3 is a functional unit that bundles tasks based on a task list D1 and bundling policy information D2, and its processing will be explained with reference to FIG.

[0025] 4 is a flowchart showing the process S30 of the task bundling unit 3. In the first process step S31 of the flow in Fig. 4, input information values ​​from the task list D1 and bundling policy information D2 are input into variables of the mathematical optimization model. As a result, a mathematical optimization model having, for example, the following objective function and constraints is generated.

[0026] (Objective Function) The objective function of the optimization model is generated based on various indices. Examples of indices are shown below. For example, work efficiency can be improved by calculating and minimizing the distance or travel time between tasks to be bundled. The distance between tasks to be bundled is calculated by referring to the task occurrence location D13.

[0027] Furthermore, for example, by maximizing the sum of the number of tasks to be bundled, multiple tasks can be carried out together, which can reduce business expenses such as expenses related to physical resources and personnel costs related to personnel resources.

[0028] Furthermore, for example, by calculating the standard deviation of the number of tasks to be bundled for each bundling task group and minimizing the number of tasks, the load on each resource can be averaged.

[0029] Furthermore, for example, by minimizing the total standard deviation of the average difficulty of each bundled task group relative to the average difficulty of all tasks, the workload and job satisfaction of each resource can be averaged. As mentioned above, job satisfaction refers to the sense of accomplishment and fulfillment felt by personnel resources when performing tasks, and is assumed to be felt by performing tasks of an appropriate level of difficulty, neither too low nor too high. The difficulty of the tasks to be bundled is determined by referring to the task difficulty D15.

[0030] Furthermore, for example, by minimizing the standard deviation of the average for each bundled task group relative to the average for all tasks, which indicates whether the environment in which the tasks to be bundled are performed is poor, it is possible to average out the load on each resource and manage motivation. Here, motivation refers to the willingness of human resources to perform tasks, and is assumed to be maintained by performing the tasks in a good on-site environment. The environmental level of the tasks to be bundled is determined by referring to the task environment information D16.

[0031] The above-mentioned indices are merely examples, and other indices may be defined. The above-mentioned indices are multiplied by weighting values ​​D21 in the bundling policy information D2, and the results are summed up to obtain the objective function (if a maximization problem and a minimization problem are mixed, one of the problems is added together and the sum is calculated). This makes it possible to achieve optimal bundling in accordance with the business entity's policies. Hereinafter, multiple bundled tasks will be referred to as a task group or a bundled task group.

[0032] (Optimization Model Constraints) The optimization model constraints are composed of, for example, the following five constraints. The first is to limit the maximum distance between the locations where tasks to be bundled occur. The maximum distance between tasks to be bundled is determined based on the bundling distance D22. This makes it possible to prevent situations where bundling would result in the same resource being moved long distances, resulting in inefficient operations.

[0033] The second is to limit the maximum number of tasks that can be bundled into one task. The maximum number of tasks that can be bundled is determined based on the number of tasks to be bundled D23. This prevents the same resource from using or working for too long a continuous period of time, or from being unable to complete all tasks in the bundled group.

[0034] The third is to avoid bundling tasks that do not overlap at all in their scheduled execution periods. The scheduled execution period of a task is determined by referring to the scheduled task execution period D14. This makes it possible to avoid bundling tasks outside of their scheduled execution periods.

[0035] The fourth restriction is to not bundle tasks of a specific classification with tasks of a different specific classification. Task classification is determined by referring to the task type information D17. This makes it possible to prevent the bundling of tasks that are clearly performed by different resources. Note that, depending on the business or business entity, there may be a need to bundle only tasks of a specific classification with tasks of a different specific classification. In such cases, this restriction is not imposed, or a restriction is imposed so that only tasks of that classification can be bundled together.

[0036] The fifth restriction is that tasks that do not require the same skills to be performed should not be bundled. The skills required to perform a task are determined by referencing the skill information D18 and the bundling skill match requirement D24. This makes it possible to avoid tasks being performed by personnel resources who do not have the necessary skills. Note that, depending on the business or business entity, training may be provided by having personnel resources who do not have the necessary skills perform a certain task. In such cases, this restriction does not need to be imposed. Furthermore, this restriction does not need to be imposed when assigning bundling tasks to a group, team, business entity, or the like that is made up of multiple personnel resources.

[0037] The five constraints mentioned above are just examples, and may be flexibly changed according to the business entity's policies. Similarly, when there is feedback from the work planning unit 4 (described later), the values ​​are input by overwriting the variables of the mathematical optimization model. Details of this will be described later in the explanation of the work planning unit 4.

[0038] Next, in processing step S32 of Fig. 4, an optimization calculation (mathematical optimization processing) is performed using the mathematical optimization model generated in processing step S31, and tasks are bundled. This makes it possible to extract tasks that should be assigned to the same resource according to the bundling policy. Note that even if no tasks to be bundled exist, this is still considered a solution.

[0039] Next, in processing step S33 in Fig. 4, the bundling result calculated in processing step S32 is output. Fig. 5 shows an example of output of the bundling result.

[0040] 5 is a diagram showing an example of a task list D1B to which bundling identification numbers have been assigned by process S30 of the task bundling unit 3. The bundling results are output, for example, by adding a column called bundling identification number D19 to the task list D1 (see FIG. 2). For example, the same identification number may be stored in the bundling identification number D19 for tasks in the same bundling task group. In this case, the bundling identification number stored for a task that has not been bundled is a bundling identification number that does not overlap with other tasks.

[0041] Alternatively, for example, all task identification numbers of tasks that fall into the same bundling task group may be stored. In this case, nothing is stored in the bundling identification number D19 of tasks that are not bundled. The above-described method of assigning bundling identification numbers is one example, and may be flexibly changed depending on the business, business entity, and work planning method. In the following, an example will be described in which the same bundling identification number is assigned to tasks in the same bundling task group, as shown in FIG. 5. The task list to which the bundling identification number D19 has been assigned is input to the work planning unit 4 and screen output unit 5, which will be described later.

[0042] 5 shows an example of bundling that takes into consideration the task difficulty level D15 and task environment information D16. The average difficulty level of each bundling task group that has been assigned the same bundling identification number, and the average value of the value indicating whether the task implementation environment has deteriorated, are all 3, and it can be seen that there is no variation between each bundling task group (i.e., between each resource to which the tasks in the bundling task group are to be assigned) and that the values ​​are averaged out.

[0043] Specifically, the identification numbers assigned with the bundling identification number 0001 are 00001 and 00002, and when the task difficulty D15 is referenced, the task difficulty values ​​are 2 and 4, with an average value of 3. Similarly, when the task environment information D16 is referenced, the task environment information values ​​are 1 and 5, with an average value of 3.

[0044] Furthermore, the identification numbers assigned with the bundling identification number 0002 are 00003 and 00004, and when task difficulty D15 is referenced, the task difficulty values ​​are 5 and 1, with an average value of 3. Similarly, when task environment information D16 is referenced, the task environment information values ​​are 4 and 2, with an average value of 3.

[0045] As shown in this example, according to this embodiment, the task groups to be assigned can be optimized by taking into account the relationship between the indices of the task groups assigned to the same resource. In other words, the generated task groups satisfy a predetermined relationship with other task groups. Furthermore, Figure 5 assumes task assignment to a team consisting of multiple personnel resources with different skills.

[0046] Fig. 6 is a flowchart showing processing S40 by the work planning unit 4. In the first processing step S41 of the flow in Fig. 6, the bundling identification number D19 (see Fig. 5) is referenced, and an objective function or constraint that takes task bundling into account is set as a sub-problem in a mathematical optimization model such as the traveling salesman problem. This makes it possible to formulate a work plan that takes task bundling into account.

[0047] An example of an objective function or constraint is shown below. When the bundling identification number D19 is taken into consideration in the objective function, for example, it is set to maximize the number of tasks with the same bundling identification number that are assigned to the same resource. This allows a work plan to be created while bundling as many tasks as possible.

[0048] When the bundling identification number D19 is taken into consideration as a constraint, for example, a setting is made so that tasks with the same bundling identification number are always assigned to the same resource. This makes it possible to create a work plan that retains the output results of the task bundling unit 3. In this case, depending on the output results of the task bundling unit 3, there may be no feasible solution to the mathematical optimization problem solved by the work planning unit 4 (processing step S43, No). In this case, processing step S45, described below, is carried out.

[0049] Next, in process step S42 of Fig. 6, an optimization calculation is performed using the mathematical optimization model generated in process step S41. This allows a work plan to be created that takes into account tasks to be assigned to the same resource according to the bundling policy. If a feasible solution is found (process step S43, Yes), the created work plan is input to the screen output unit 5 (described below), and the created work plan is output to the display device 6 (process step S44), and the process ends. On the other hand, if a feasible solution is not found (process step S43, No), process step S45 is performed.

[0050] In processing step S45 of FIG. 6 , a value is fed back to the task bundling unit 3. The fed back value may be, for example, the maximum distance between tasks to be bundled, which serves as a substitute for the bundling distance D22 (see FIG. 3 ), and may be a value smaller than the value set in the mathematical optimization model of the task bundling unit 3. Alternatively, the fed back value may be, for example, the maximum number of tasks to be bundled, which serves as a substitute for the bundling count D23 (see FIG. 3 ), and may be an integer smaller than the value set in the task bundling unit 3. Alternatively, both of the above may be fed back. This suppresses task bundling, and when the task planning unit 4 re-creates a task plan, the task bundling results considered as constraints are relaxed, making it easier to avoid situations where no feasible solution exists. The above feedback is merely an example, and any constraint may be used as long as it suppresses task bundling in the task bundling unit 3.

[0051] As long as the feedback occurs, the task bundling unit 3 and the work planning unit 4 are repeated to create a work plan that maintains task bundling as much as possible. If the task bundling unit 3 does not have any tasks to bundle and the work planning unit 4 does not have a feasible solution, the objective function and constraints in the mathematical optimization model, such as the traveling salesman problem, that forms the basis of the work planning unit 4 are changed as desired, and the process is restarted from processing step S31. Once the work plan has been created, the process ends and the result is input to the screen output unit 5, which will be described later.

[0052] Fig. 7 is a flowchart showing an example of processing S50 of the screen output unit 5. The screen output unit 5 is a functional unit that selects and displays content to be displayed on the display device 6, and this processing will be explained with reference to Fig. 7. The display device 6 is configured to include, for example, a liquid crystal panel or an organic EL (Electro Luminescence) panel, and displays the display content selected by the operator.

[0053] In the process of the screen output unit 5 in FIG. 7, in processing step S51, a selection input of an item to be displayed on the screen is accepted, and in processing step S52, the selected item is displayed.

[0054] Next, an example of the configuration of the screen 61 in Fig. 8 will be described. Fig. 8 is a diagram showing an example of a screen output by the screen output unit 5. The screen is configured with a plurality of panes (a display content selection pane 62, a result output pane 63) which are small areas divided into the screen. The display content selected by the screen output unit 5 is displayed on the screen 61 displayed on the display device 6.

[0055] The display content selection pane 62 is a display that allows the operator to operate and select the display content to be selected and processed in the screen output unit 5. As a result, the display content selected in the display content selection pane 62 is displayed in the other panes. Selectable factors include a task list including a bundling identification number, a work plan, etc. When one of these items is selected, the selection input of the item to be displayed on the screen is accepted and processed in processing step S51 of the screen output unit 5 in FIG. 15. Thereafter, in processing step S52 of the screen output unit 5 in FIG. 15, a display screen according to the selected content is displayed in the result output pane 63.

[0056] The result output pane 63 displays a task list, which is the output of the task bundling unit 3, and a work plan, which is the output of the work planning unit 4. The task list includes a bundling identification number, which makes it possible to determine with which other tasks each task is bundled, or whether it is bundled with any other tasks at all. The work plan is displayed in the form of, for example, a Gantt chart, which makes it possible to determine which task each resource should perform and when.

[0057] 8, when the resource identification number is 0001, the plan is to execute task identification number 000001 (task 000001) first, followed by task identification number 000002 (task 000002). Also, when the resource identification number is 0002, the plan is to execute task identification number 000003 (task 000003) first, followed by task identification number 000004 (task 000004). In other words, multiple tasks are linked to the same resource based on the bundling identification number, and the same resource is scheduled to execute the tasks in chronological order.

[0058] When developing a business using the work planning device 7 according to this embodiment, several examples are conceivable. For example, a business entity may create a work plan using the work planning device 7 and operate resources based on the work plan. Alternatively, a business entity may create a work plan using the work planning device 7 and request another business entity to carry out work and secure resources based on the work plan.

[0059] Furthermore, for example, a certain business entity may use the work plan creation device 7 to perform only task bundling, and request work planning and work execution from another business entity based on a task list to which a bundling identification number has been assigned. As in the last example, in this embodiment, the functions of the task bundling unit 3 or the work planning unit 4 can be utilized independently by using the bundling identification number as an interface. Therefore, the task bundling unit 3 or the work planning unit 4 can be constructed as separate devices, or one of the functions can be later extrapolated into the same device, making it possible to implement the system in the form of a microservice.

[0060] The present invention is not limited to the above-described embodiments and includes various modifications. For example, the above-described embodiments have been described in detail to clearly explain the present invention, and are not necessarily limited to those including all of the described configurations. It is possible to replace part of the configuration of one embodiment with the configuration of another embodiment, and it is also possible to add the configuration of another embodiment to the configuration of one embodiment. Furthermore, it is also possible to add, delete, or replace part of the configuration of each embodiment with other configurations.

[0061] The above-described configurations, functions, processing units, processing means, etc. may be implemented in part or in whole by hardware such as an integrated circuit. The above-described configurations, functions, etc. may also be implemented by software, with a processor interpreting and executing a program that implements each function. Information such as the program, table, and file that implements each function can be stored in a recording device such as a memory, a hard disk, or an SSD (Solid State Drive), or on a recording medium such as a flash memory card or a DVD (Digital Versatile Disk).

[0062] In each embodiment, the control lines and information lines shown are those that are considered necessary for the explanation, and not all control lines and information lines in the product are necessarily shown. In reality, it can be considered that almost all components are interconnected.

[0063] 3 Task bundling section 4 Work planning section 5 Screen output section 6 Display device 7 Work plan drafting device 8 Input device 61 Screen 62 Display content selection pane 63 Result output pane D1 Task list (task information) D1B Task list (after bundling identification number is assigned) D11 Task identification number D12 Task content D13 Task occurrence location D14 Planned task execution period D15 Task difficulty D16 Task environment information D17 Task type information D18 Skill information D19 Bundling identification number D2 Bundling policy information (handling policy) D21 Weighting value D22 Bundling distance D23 Number of bundles D24 Need for bundling skill match

Claims

1. A work planning device comprising: a memory unit that stores a plurality of tasks and task information that is information relating to the tasks; a task bundling unit that generates a plurality of task groups by bundling the tasks based on the task information and assigns the same bundling identification number to tasks assigned to the same task group; and a work planning unit that assigns tasks assigned the same bundling identification number to the same resource.

2. A work planning device as described in claim 1, characterized in that the memory unit stores a bundling policy including constraints between multiple task groups to be generated, and the task bundling unit generates the task groups based on the bundling policy.

3. A work planning device according to claim 2, characterized in that the task bundling unit generates the task group by executing a mathematical optimization process based on the task information and the bundling policy.

4. A work planning device as described in claim 1, characterized in that the task bundling unit generates an index relating to the load on resources when multiple tasks are combined, the job satisfaction of human resources, or motivation.

5. A work planning device as described in claim 3, characterized in that the task bundling unit maximizes the number of tasks having the same bundling identification number that are linked to the same resource as an objective function of mathematical optimization.

6. A work planning device as claimed in claim 3, characterized in that, when the work planning unit is unable to output a feasible solution, it feeds back this fact to the task bundling unit and adds constraints to the mathematical optimization problem.

7. A work planning device as described in claim 3, wherein the task bundling unit averages the load on the resources by taking a standard deviation for the number of tasks to be bundled for each task group and minimizing the number of tasks.

8. A work planning device as described in claim 3, characterized in that the task bundling unit averages the load on the resources by minimizing the sum of standard deviations of the average difficulty of each task group relative to the average difficulty of all tasks for the tasks to be bundled.

9. A work planning device as described in claim 3, characterized in that the task bundling unit averages the load on the resources by minimizing the standard deviation of the average for each task group relative to the average for all tasks, for a value indicating whether the environment in which the tasks to be bundled are performed is poor or not.

10. A work planning device that bundles a plurality of tasks to generate a plurality of task groups, comprising: a memory unit that stores a bundling policy including constraints between the plurality of task groups to be generated; and a task bundling unit that generates the plurality of task groups so as to satisfy the bundling policy.

11. A work planning device that bundles a plurality of tasks to generate a plurality of task groups, wherein the generated task groups satisfy a predetermined relationship with other task groups.

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