Work planning device

Abstract

To provide a work planning device capable of allocating a plurality of tasks to the same resource according to a purpose that a business entity regards as important.SOLUTION: A work planning device 7 comprises: a storage unit which stores a plurality of tasks and task information (task list D1) as information related to the tasks; a task bundling unit 3 which bundles the plurality of tasks based upon the task information to create a plurality of task groups, and impart the same bundling identification number to tasks allocated to the same task group; and a work plan unit 4 which allocates the tasks given the same bundling identification number to the same resource. The storage unit stores bundling policy (bundling policy information D2) including restriction conditions among the plurality of created task groups, and the task bundling unit 3 creates task groups based upon the bundling policy.SELECTED DRAWING: Figure 1A

Description

[Technical field]

[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 humans and physical materials. [Background technology]

[0002] In recent years, the introduction of Field Service Management (hereinafter, FSM) has been promoted in various industries. FSM is generally equipped with functions that support task generation, planning of work plans to assign resources, and progress management of actual on-site work. Here, resources refer to a single personnel resource such as a worker, a group, team, or business entity consisting of multiple personnel resources, and physical resources such as materials. In particular, in planning work plans, not only manual resource allocation using a user interface (hereinafter, UI), but also resource allocation using calculations such as machine learning has been developed, and further sophistication is required. In the above-mentioned work plans, tasks are usually handled individually and assigned to the same or different resources in chronological order. On the other hand, some business entities have a need to bundle multiple tasks together (hereinafter, referred to as bundling) in a format similar to subsequent work and assign them to the same resource, thereby reducing travel time, material usage fees, labor costs, work outsourcing costs, etc. related to the same resource. In addition, particularly when personnel resources are performing multiple tasks, it may be necessary to consider reducing overtime hours for workers and to ensure that they are not only given unmotivated tasks or heavy work.

[0003] Background of this technical field is the invention described in Patent Document 1. The abstract of this document states that "a method of 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." [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Special Publication No. 2022-527961 [Non-patent literature]

[0005] [Non-Patent Document 1] Ishii: "Work satisfaction and difficulty as seen in a survey of welfare and nursing care sites," Social Science of Welfare, Vol. 1 (2009) [Non-Patent Document 2] Kanaoka: "Job satisfaction and improvement methods of agricultural production corporation employees", Hokkaido Agricultural Research Center Agricultural Management Research, No. 108, pp. 54-66 (2013) [Non-Patent Document 3] Ohno: "A study on the work of inns and the ease and job satisfaction of working there - Based on the opinions of front-service staff at the Ikaho Onsen Ryokan Hotel Tenbo," Journal of the Japan Tourism Research Association, Vol. 28, No. 2, p. 57-67 (2017) Summary of the Invention [Problem to be solved by the invention]

[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 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 consideration the priority of the task, the necessary skills, the time required for task execution, etc. However, it is difficult to appropriately improve business efficiency, reduce business expenses, improve the working environment, etc., according to the needs of the business or business entity by collectively allocating multiple tasks to the same resource.

[0007] Therefore, an object of the present invention is to provide a work plan planning device that can assign multiple tasks to the same resource according to the objectives that an enterprise prioritizes. [Means for solving the problem]

[0008] In order to achieve the above object, the work plan planning device of the present invention is characterized by comprising: a storage unit that stores a plurality of tasks and task information that is information related to 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 plan unit 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 later. Effect of the Invention

[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. [Brief description of the drawings]

[0010] [Figure 1A] 1 is a block diagram showing functions of a work plan planning device according to an embodiment; [Figure 1B]FIG. 2 is a block diagram showing a computer of the work plan planning apparatus according to the embodiment. [Diagram 2] 11 is a diagram showing an example of a task list among various information stored in a large-capacity storage unit DB; FIG. [Diagram 3] 11 is a diagram showing an example of bundling policy information among various information stored in a large capacity storage unit DB. FIG. [Figure 4] 13 is a flowchart showing a process of a task bundling unit. [Diagram 5] 13 is a diagram showing an example of a task list D1 to which bundling identification numbers have been assigned by processing of a task bundling unit. FIG. [Figure 6] 13 is a flowchart showing a process of a work planning unit. [Figure 7] 13 is a flowchart showing a process of a screen output unit. [Figure 8] FIG. 13 is a diagram showing an example of a screen output by a screen output unit. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[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 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 a chronological order.

[0012] In FIG. 1B, the computer of the work plan making 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. Here, the storage unit 72 includes a RAM 72a, a ROM 72b, and an HDD 72c (hard disk). 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 (for example, a display device 6, an input device 8). The ROM 72b stores programs and various data executed by the CPU 71 and the DSP 75. The CPU 71 and the DSP 75 realize various functions by executing these programs. Here, the HDD 72c corresponds to a non-volatile large-capacity storage unit DB. Note that this embodiment is not limited to a single device, and may be implemented as a work plan system in which multiple servers and the like are linked together.

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

[0014] The task bundling unit 3 generates a plurality of task groups by bundling a plurality of tasks based on the plurality of tasks and task information (task list D1) that is information related to 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 group based on a bundling policy (bundling policy information D2) that includes constraints between the plurality of task groups to be generated. The task bundling unit 3 executes a mathematical optimization process based on the task information and the bundling policy to generate the task group.

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

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

[0017] The various information held in the non-volatile large-capacity storage unit DB in the work plan planning device 7 in Fig. 1 will be described below. First, an example of a task list D1 is shown in Fig. 2.

[0018] 2 is a diagram showing an example of a task list D1 among various information held in the mass storage unit DB. The task list D1 includes a task identification number D11, a task content D12, a task occurrence location D13, a scheduled task execution period D14, a 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, and any information that can identify the location may be stored. 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 the order of ease as a level of difficulty for each task. The task environment information D16 stores values ​​such as 1 to 5 in the order of poor or dangerous as a value indicating whether the environment for performing the 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 a task related to equipment or a task related to the maintenance of the surrounding environment. It is assumed that various values ​​are stored for the difficulty level and environmental level of 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 for performing the task.

[0021] FIG. 3 is a diagram showing an example of bundling policy information D2 among various information held in the large-capacity storage unit DB. The bundling policy information D2 is information indicating the importance of each index to be emphasized when bundling (for example, weight value D21), and the value of variables that are constraints when bundling (for example, bundling distance D22, number of bundling D23, bundling skill match necessity D24). The indexes include minimizing travel distance, reducing business expenses, averaging resource load, and averaging job satisfaction. That is, the task bundling unit 3 generates an index related to the load on resources when multiple tasks are combined, job satisfaction of personnel resources, or motivation. Job satisfaction refers to the satisfaction and sense of accomplishment related to the task execution of personnel resources. 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, and physical resources such as materials.

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

[0023] This embodiment is not limited to 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 power system field will be described as examples.

[0024] Returning to FIG. 1, various processing functions executed by the CPU 71 will be described. 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 described with reference to FIG.

[0025] Fig. 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 the bundling policy information D2 are input to variables of a 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 indicators, examples of which are shown below. For example, the efficiency of work 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] In addition, for example, by taking the sum of the number of tasks to be bundled and maximizing it, multiple tasks can be performed together, which can reduce business expenditures such as expenses related to physical resources and labor costs related to personnel resources.

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

[0029] Also, for example, by minimizing the total standard deviation of the average of the bundling task difficulty for each bundling task group relative to the average of all tasks, the load and job satisfaction of each resource can be averaged. As mentioned above, job satisfaction refers to the sense of accomplishment and satisfaction associated with the task execution of a human resource, and is assumed here to be felt by executing a task of appropriate difficulty, neither too low nor too high. The difficulty of the bundling tasks is determined by referring to the task difficulty D15.

[0030] Also, for example, by minimizing the standard deviation of the average for each bundling 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 maintained by performing the tasks in a site environment that is not poor. The environmental level of the tasks to be bundled is determined by referring to the task environment information D16.

[0031] The above-mentioned index is an example, and other indexes may be defined. The above-mentioned index is multiplied by a weighting value by referring to the weighting value D21 in the bundling policy information D2, and the whole is summed up to obtain the objective function (if a maximization problem and a minimization problem are mixed, one of them is taken as a negative sign and summed up). This makes it possible to realize optimal bundling according to the business entity's policy. Hereinafter, multiple bundled tasks will be referred to as a task group or a bundling task group.

[0032] (Optimization model constraints) In addition, the constraints of the optimization model are composed of, for example, the following five items. 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 the same resource is moved over a long distance as a result of bundling, 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 bundling quantity D23. This prevents the same resource from using or working for too many consecutive hours, or from being unable to complete all tasks in the bundling group.

[0034] The third is not to bundle tasks that do not overlap at all in the scheduled execution period. The scheduled execution period of a task is referred to as the scheduled execution period D14. This makes it possible to avoid bundling tasks outside of the scheduled execution period.

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

[0036] The fifth rule is not to bundle tasks that do not require the same skills to be performed. For the skills required to perform a task, refer to the skill information D18 and the bundling skill match necessity D24. This makes it possible to avoid tasks being performed by personnel resources that do not have the necessary skills. Note that, depending on the business or business entity, there may be cases where training is provided by having personnel resources that do not have the skills required for a certain task perform the task, in which case there is no need to impose this constraint. In addition, there is no need to impose this constraint when assigning bundling tasks to a group, team, business entity, etc. that is made up of multiple personnel resources.

[0037] The above five constraints are just examples, and may be flexibly changed according to the business entity's policy. In addition, when there is feedback from the work planning unit 4 described later, the values ​​are similarly overwritten into 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 in Fig. 4, optimization calculations (mathematical optimization processing) are 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 the case where there are no tasks to be bundled is also considered to be one of the solutions.

[0039] Next, in process step S33 in Fig. 4, the bundling result calculated in process step S32 is output. Fig. 5 shows an example of the 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 result is 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 of a task that has not been bundled is stored as a bundling identification number that does not overlap with other tasks.

[0041] Also, for example, all task identification numbers of tasks that are in 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-mentioned 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 embodiment will be described assuming an example in which the same bundling identification number is stored for tasks in the same bundling task group, as shown in FIG. 5. The task list to which the above-mentioned bundling identification number D19 has been assigned is input to the work planning unit 4 and the screen output unit 5, which will be described later.

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

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

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

[0045] As in this example, according to this embodiment, the task groups to be assigned can be optimized by considering the relationship between the indices of the task groups assigned to the same resource. That is, the generated task groups satisfy a predetermined relationship with other task groups. Also, FIG. 5 assumes task assignment to a team composed of multiple personnel resources each having different skills.

[0046] Fig. 6 is a flow chart showing the process S40 of the work planning unit 4. In the first process step S41 of the flow of Fig. 6, the bundling identification number D19 (see Fig. 5) is referenced, and an objective function or constraint considering task bundling 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 considering task bundling.

[0047] An example of an objective function or constraint is given 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 makes it possible to create a work plan while bundling as many tasks as possible.

[0048] When the bundling identification number D19 is taken into consideration in the constraints, for example, it is set so that tasks with the same bundling identification number are always assigned to the same resource. This makes it possible to formulate a work plan that holds the output results of the task bundling unit 3. At this time, depending on the output results of the task bundling unit 3, there may be cases where a feasible solution does not exist for the mathematical optimization problem of the work planner 4 (processing step S43, No). In that case, processing step S45 described later is implemented.

[0049] Next, in process step S42 in Fig. 6, optimization calculations are 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 exists (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 does not exist (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 value to be fed back is, for example, the maximum distance between tasks to be bundled, which is a substitute for the bundling distance D22 (see FIG. 3), and is a value smaller than the value set in the mathematical optimization model of the task bundling unit 3. Alternatively, the value to be fed back is, for example, the maximum number of tasks to be bundled, which is a substitute for the number of bundling D23 (see FIG. 3), and is an integer smaller than the value set in the task bundling unit 3. Alternatively, both of the above may be fed back. As a result, task bundling is suppressed, and when the task planning unit 4 re-plans the task, the task bundling result considered as a constraint is relaxed, making it easier to avoid a situation where no feasible solution exists. The above feedback is one example, and is not limited to this as long as the constraint 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 there are no tasks to be bundled in the task bundling unit 3 and no feasible solution exists in the work planning unit 4, the objective function and constraints in the mathematical optimization model such as the traveling salesman problem on which the work planning unit 4 is based are arbitrarily changed, 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 the contents to be displayed on the display device 6, and the 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 contents selected by the operator.

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

[0054] Next, a configuration example of the screen 61 in FIG. 8 will be described. 8 is a diagram showing an example of a screen output by the screen output unit 5. The screen is composed of 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 a 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 by 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 these items are 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 that is the output of the task bundling unit 3, and a work plan that is the output of the work plan unit 4. The task list includes a bundling identification number, which makes it possible to determine which other tasks each task is bundled with, or whether each task is not bundled with any other tasks. 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 000002 (task 000002) after executing the task identification number 000001 (task 000001). Also, when the resource identification number is 0002, the plan is to execute 000004 (task 000004) after executing the task identification number 000003 (task 000003). In other words, the plan is to link multiple tasks to the same resource based on the bundling identification number, and have the same resource execute the tasks in chronological order.

[0058] When developing a business using the work plan creation device 7 according to the present embodiment, several forms are possible. For example, a business entity may create a work plan using the work plan creation device 7, and operate resources based on the work plan. Also, for example, a certain business entity may create a work plan using the work plan creation device 7 and request another business entity to carry out work and secure resources based on the work plan.

[0059] Also, for example, a certain business entity may use the work plan creation device 7 to perform only task bundling, and may request another business entity to plan a work or perform a work 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 plan unit 4 can be used independently by using the bundling identification number as an interface. Therefore, the task bundling unit 3 or the work plan unit 4 can be constructed as separate devices, or one of the functions can be extrapolated later to 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 embodiment, and includes various modified examples. For example, the above-described embodiment has been described in detail to clearly explain the present invention, and is not necessarily limited to those having all of the configurations described. It is possible to replace a 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. In addition, it is also possible to add, delete, or replace a part of the configuration of each embodiment with another configuration.

[0061] The above configurations, functions, processing units, processing means, etc. may be realized in part or in whole by hardware such as an integrated circuit. The above configurations, functions, etc. may be realized by software by a processor interpreting and executing a program that realizes each function. Information such as the program, table, file, etc. that realizes each function can be stored in a recording device such as a memory, a hard disk, or an SSD (Solid State Drive), or 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 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 may be considered that almost all components are connected to each other. [Explanation of symbols]

[0063] 3 Task bundling section 4. Work Planning Department 5. Screen output section 6 Display device 7 Work planning device 8 Input Devices 61 screens 62 Display Content Selection Pane 63 Results Output Pane D1 Task list (task information) D1B Task List (after bundling identification number is assigned) D11 Task identification number D12 Task Contents D13 Task occurrence location D14 Task implementation 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 bundlings D24 Bundling Skill Match Required

Claims

1. A storage unit that stores a plurality of tasks and task information that is information related 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; A work planning unit that assigns tasks to which the same bundling identification number is assigned to the same resource. A work planning device comprising:

2. The work plan planning device according to claim 1 , The storage unit stores a bundling policy including constraints between a plurality of task groups to be generated; The task bundling unit generates the task group based on the bundling policy. A work planning device comprising:

3. The work plan planning device according to claim 2, The task bundling unit executes a mathematical optimization process based on the task information and the bundling policy to generate the task group. A work planning device comprising:

4. The work plan planning device according to claim 1 , The task bundling unit generates an index relating to a load on resources when a plurality of tasks are combined, a job satisfaction of human resources, or a motivation. A work planning device comprising:

5. The work plan planning device according to claim 3, 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. The work plan planning device according to claim 3, If the task planning unit is unable to output a feasible solution, it feeds back that fact to the task bundling unit and adds constraints to the mathematical optimization problem. A work planning device comprising:

7. The work plan planning device according to claim 3, 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. A work planning device comprising:

8. The work plan planning device according to claim 3, The task bundling unit averages the load on the resources by minimizing the sum of standard deviations of the averages of the difficulties of the tasks to be bundled for each task group relative to the average of all tasks. A work planning device comprising:

9. The work plan planning device according to claim 3, The task bundling unit averages the load on the resource by minimizing a standard deviation of an average for each task group with respect to an average of all tasks, regarding a value indicating whether or not the environment in which the tasks to be bundled are performed is poor. A work planning device comprising:

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

11. A work planning device that bundles a plurality of tasks and generates a plurality of task groups, The generated task group satisfies a predetermined relationship with other task groups. A work planning device comprising:

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