Schedule creation device, schedule creation method and program

Abstract

To create an optimal schedule for a user, which corresponds to multiple purposes.SOLUTION: A Pareto solution calculation unit 143 performs multi-objective analysis on a plurality of objective functions whose design variables are information about exercise events, which are specific events to be incorporated into a user's basic schedule, within a range that satisfies constraint conditions of the design variables, and calculates a plurality of Pareto solutions.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present invention relates to a schedule creation device, a schedule creation method, and a program. [Background technology]

[0002] There are known techniques for creating an optimal schedule for a user. For example, Patent Document 1 describes an invention for creating a schedule that allows a user to improve their sleep condition without stress. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2020-201642 A Summary of the Invention [Problem to be solved by the invention]

[0004] The invention described in Patent Document 1 is an invention that creates an optimal schedule with the objective of improving the user's sleep status. However, various objectives other than the above are conceivable for optimizing a schedule. For example, it is conceivable to propose a schedule with the objective of improving obesity prevention, or to propose a schedule with the objective of improving work efficiency.

[0005] The present invention has been made in consideration of the above-mentioned circumstances, and has an object to provide a schedule creation device and the like that can create an optimal schedule for a user that corresponds to a plurality of purposes. [Means for solving the problem]

[0006] In order to achieve the above object, a schedule creation device according to the present invention comprises: The system further includes a Pareto solution calculation means for performing multi-objective analysis on a plurality of objective functions whose design variables are information about specific events to be incorporated into the user's basic schedule, within a range that satisfies the constraint conditions of the design variables, and calculating a plurality of Pareto solutions. Effect of the Invention

[0007] According to the present invention, it is possible to create an optimal schedule for a user that meets multiple objectives. [Brief description of the drawings]

[0008] [Figure 1] 1 is a block diagram of a schedule creation device according to an embodiment of the present invention. [Diagram 2] FIG. 1 is a diagram showing an example of a basic schedule according to an embodiment of the present invention. [Diagram 3] FIG. 13 is a diagram showing an example of an exercise event table according to an embodiment of the present invention. [Figure 4] FIG. 13 is a diagram illustrating an example of a deletion cost table according to the embodiment of the present invention. [Diagram 5] FIG. 13 is a diagram showing an example of an exercise timing table according to an embodiment of the present invention. [Figure 6] FIG. 13 is a diagram for explaining how to obtain a timing score. [Figure 7] FIG. 13 is a diagram showing an example of the distribution of timing scores in one day. [Figure 8] FIG. 11 is a diagram illustrating an example of a constraint condition table according to the embodiment of the present invention. [Figure 9] FIG. 13 is a diagram illustrating an example of an optimization schedule aimed at minimizing deletion costs. [Figure 10] FIG. 13 is a diagram showing an example of an optimized schedule aimed at maximizing the amount of exercise. [Figure 11] FIG. 1 illustrates an example of an optimized schedule aimed at maximizing timing cost. [Figure 12] 11 is a flowchart of a schedule proposal process according to an embodiment of the present invention. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0009] Hereinafter, a schedule creation device, a schedule creation method, and a program according to an embodiment of the present invention will be described with reference to the drawings. In the drawings, the same components are denoted by the same reference numerals.

[0010] A schedule creation device 1 according to an embodiment of the present invention will be described below. The schedule creation device 1 is a device that creates an optimized schedule (optimized schedule) by incorporating an exercise-related event (exercise event) into a basic schedule that indicates a user's daily plans. As shown in FIG. 1, the schedule creation device 1 includes a communication unit 11, an operation unit 12, a display unit 13, a control unit 14, and a storage unit 15.

[0011] The communication unit 11 is an interface for communicating with an external device via a network such as the Internet or short-distance wireless communication, etc. The external device here is, for example, a user's smartphone, a wearable terminal, a PC, etc.

[0012] The operation unit 12 is an input device such as a keyboard, a mouse, etc., and outputs a signal according to an input operation received from a user to the control unit 14. For example, the operation unit 12 receives an input of a basic schedule from the user.

[0013] The display unit 13 is a display device such as a liquid crystal display, and displays various information based on instructions from the control unit 14. For example, the display unit 13 displays a list of optimized schedules.

[0014] The control unit 14 includes a CPU (Central Processing Unit), a ROM (Read Only Memory) that stores programs such as an OS (Operation System), and a RAM (Random Access Memory) that serves as a work area, and controls the entire schedule creation device 1. The control unit 14 also includes, as functional components according to this embodiment, a pre-processing unit 141, a basic schedule acquisition unit 142, a Pareto solution calculation unit 143, an optimized schedule creation unit 144, and a schedule proposing unit 145.

[0015] The pre-processing unit 141 performs pre-processing such as preparing each objective function and each table, which will be described later, required for the Pareto solution calculation unit 143 to perform multi-objective analysis.

[0016] The basic schedule acquisition unit 142 acquires the user's basic schedule. The basic schedule is a schedule that represents the user's basic plans for one day. For example, the user inputs the contents of the basic schedule from the operation unit 12, so that the basic schedule acquisition unit 142 can acquire the basic schedule. Alternatively, the basic schedule acquisition unit 142 may acquire the user's schedule for each day of the most recent week and average these to acquire the basic schedule. Note that the basic schedule may be, for example, a schedule that averages the schedules of multiple users or a virtually created schedule.

[0017] An example of a basic schedule is shown in Figure 2. In this disclosure, a day is divided into 144 10-minute segments, and the basic schedule is represented by events for each segment. Furthermore, exercise events can be incorporated into the basic schedule on a segment-by-segment basis. By incorporating an exercise event, the event in the original basic schedule that occurred at the time of the incorporated exercise event is deleted.

[0018] Returning to FIG. 1, the Pareto solution calculation unit 143 performs multi-objective analysis on multiple objective functions each having a different objective for optimizing the basic schedule, with information about each exercise event to be incorporated into the user's basic schedule (event ID of each exercise event to be incorporated, incorporation time, exercise duration) as design variables, and calculates multiple Pareto solutions. The Pareto solution calculation unit 143 is an example of a Pareto solution calculation means in the present disclosure. Here, the exercise events that can be incorporated into the basic schedule are only those that are registered in advance in the exercise event table 151 shown in FIG. 3. In this figure, the event ID is identification information that indicates the type of exercise event. In this embodiment, the multiple objective functions that are the subject of the multi-objective analysis are the following (1) to (4). (1) Objective function aimed at minimizing the deletion cost (hereinafter, the deletion cost calculation function) (2) Objective function for maximizing the user's exercise amount (hereinafter, exercise amount calculation function) (3) Objective function aimed at minimizing the burden on users (hereafter referred to as the burden calculation function) (4) Objective function aimed at maximizing the movement timing score (hereinafter, timing score calculation function) Each of the above objective functions (1) to (4) will be described in detail below.

[0019] (1) Deletion cost calculation function The deletion cost calculation function is a function that calculates the cost associated with the deletion of an event in the basic schedule due to the incorporation of an exercise event into the user's basic schedule. In this embodiment, the deletion cost table 152 shown in FIG. 4 sets a deletion cost per 10 minutes (one frame) for each type of event to be deleted. In addition, in this deletion cost table 152, the more difficult an event is to delete in terms of the user's daily life, the higher the deletion cost is set. In addition, in the deletion cost table 152, the deletion cost "cannot be deleted" means that the event cannot be deleted. For example, suppose that the incorporation of an exercise event into the basic schedule results in the deletion of one hour (six frames) of the event "free time" and 30 minutes (three frames) of the event "housework". In this case, the deletion cost calculation function calculates the deletion cost as 5×6+90×3=300.

[0020] The smaller the deletion cost, the more the exercise event has been incorporated into the original basic schedule in a manner that is reasonable for the user. One of the goals of schedule optimization is to create an optimized schedule that incorporates exercise events so as to minimize the deletion cost.

[0021] (2) Momentum calculation function The exercise amount calculation function is a function that calculates the amount of exercise of a user that increases by incorporating an exercise event into a basic schedule. In this embodiment, a numerical value that indicates the amount of exercise when the exercise event is performed for 10 minutes (one period) is set for each exercise event by the exercise event table 151 shown in FIG. 3. For example, assume that the exercise event "walking" is incorporated for one hour and the exercise event "brisk walking" is incorporated for 30 minutes into a basic schedule. In this case, the exercise amount calculation function calculates the amount of exercise as 0.5×6+0.7×3=5.1.

[0022] Increasing the amount of exercise a user does is effective in terms of preventing obesity, adult diseases, etc. One of the goals of schedule optimization is to create an optimized schedule that incorporates exercise events that maximize the amount of exercise.

[0023] (3) Burden calculation function The workload calculation function is a function that calculates the physical workload of the user that increases as a result of incorporating an exercise event into the basic schedule. In this embodiment, a numerical value that indicates the physical workload of the user when performing each exercise event for 10 minutes (one session) is set for each exercise event in the exercise event table 151 shown in FIG. 3. For example, assume that the basic schedule includes an exercise event "walking" for one hour and an exercise event "brisk walking" for 30 minutes. In this case, the exercise amount calculation function calculates the workload as 1×6+2×3=12.

[0024] Reducing the physical burden on a user is useful in terms of reducing the user's fatigue, preventing injuries, etc. One of the goals of schedule optimization is to create an optimized schedule that incorporates exercise events so as to minimize the burden on the user.

[0025] (4) Timing score calculation function The timing score calculation function is a function for calculating a timing score indicating an evaluation of the timing of an exercise event to be incorporated into a basic schedule. In this embodiment, an exercise timing table 153 shown in FIG. 5 is set in order to calculate a timing score. The exercise timing table 153 is a table including a center time, an effective time width, and a score value. The timing score when an exercise event is incorporated into a center time is the score value, and the timing score is distributed in the form of a normal distribution having an effective time width with this score value as a peak. A positive score value indicates that the timing of incorporating an exercise event is good, and a negative score value indicates that the timing of incorporating an exercise event is bad. For example, from the first entry of the exercise timing table 153 shown in FIG. 5, a timing score between 4:00 and 10:00, three hours before and after the 7:00 cancellation, can be obtained as shown in the graph in FIG. 6. The timing scores are obtained for all entries registered in the exercise timing table 153, and the timing scores are summed up for each hour, so that the distribution of the daily timing scores (timing score distribution) corresponding to the basic schedule can be obtained as shown in FIG. 7. The timing score calculation function refers to the timing score distribution obtained in this manner, calculates a timing score for each exercise event to be incorporated into the basic schedule from the timing (incorporation time) of the exercise event to be incorporated, and then adds these up to obtain the overall timing score.

[0026] For example, it is known that exercising just before going to bed disturbs sound sleep. Also, exercising just before or just after a meal is not recommended in terms of the burden it places on the stomach and intestines. On the other hand, exercising in the morning, at night, or three hours before going to bed is known to be good for the body in terms of calorie consumption and sound sleep. One of the goals of schedule optimization is to create an optimized schedule that incorporates exercise events at times that maximize the timing score.

[0027] The objective functions (1) to (4) described above all use information about the exercise events to be incorporated into the basic schedule (event ID indicating the type of each exercise event to be incorporated, incorporation time, and exercise duration) as design variables, but constraint conditions are set for the design variables. When performing multi-objective analysis using the objective functions (1) to (4) described above, the design variables must satisfy the constraint conditions. In the present disclosure, the constraint conditions are set in advance by the constraint condition table 154 shown in FIG. 8. In this constraint condition table 154, the minimum exercise amount, maximum exercise amount, maximum exercise duration, maximum total exercise duration, non-exercise time period, maximum number of inclusions, minimum number of inclusions, and interval time are set as constraint conditions.

[0028] The minimum amount of exercise set in the constraint condition table 154 represents the minimum amount of exercise per exercise event to be incorporated into the basic schedule. The amount of exercise of the exercise event to be incorporated must be equal to or greater than the minimum amount of exercise. The maximum amount of exercise set in the constraint condition table 154 represents the maximum amount of exercise per exercise event to be incorporated into the basic schedule. The amount of exercise of the exercise event to be incorporated must be equal to or less than the maximum amount of exercise. The amount of exercise of the exercise event can be determined by referring to the exercise event table 151 (FIG. 3) described above.

[0029] The maximum exercise time set in the constraint condition table 154 represents the maximum exercise time per exercise event to be included in the basic schedule. The maximum total exercise time set in the constraint condition table 154 represents the maximum total exercise time of each exercise event to be included in the basic schedule.

[0030] The non-exercise time period set in the constraint condition table 154 represents a time period during which exercise events cannot be incorporated into the basic schedule. The maximum number of inclusions set in the constraint condition table 154 represents the maximum number of exercise events that can be incorporated into the basic schedule. The minimum number of inclusions set in the constraint condition table 154 represents the minimum number of exercise events that can be incorporated into the basic schedule.

[0031] The interval time set in the constraint condition table 154 indicates the minimum time that must be secured between exercise events when multiple exercise events are incorporated into a basic schedule. If multiple exercise events are performed consecutively with almost no time in between, there is a risk that the next exercise event will be performed without having had time to recover from fatigue caused by the previous exercise event. To prevent this situation, the interval time is set as a constraint condition.

[0032] Returning to FIG. 1, the optimization schedule creation unit 144 extracts Pareto solutions that meet a predetermined criterion from the multiple Pareto solutions (type (event ID) of each exercise event to be incorporated, incorporation time, exercise duration) calculated by the Pareto solution calculation unit 143. Specifically, the optimization schedule creation unit 144 extracts a total of five Pareto solutions as Pareto solutions that meet the predetermined criterion, including four Pareto solutions that best achieve each objective of the above-mentioned four objective functions and a Pareto solution that is most balanced with respect to each objective of the four objective functions. That is, (1) the type (event ID), incorporation time, and exercise time of each exercise event that results in the lowest deletion cost, (2) the type (event ID), incorporation time, and exercise time of each exercise event that results in the greatest amount of exercise for the user, (3) the type (event ID), incorporation time, and exercise time of each exercise event that results in the least physical burden on the user, (4) the type (event ID), incorporation time, and exercise time of each exercise event that results in the highest timing score, and (5) the type (event ID), incorporation time, and exercise time of each exercise event that is most balanced with respect to each objective of each objective function are extracted.

[0033] Then, the optimization schedule creation unit 144 creates an optimization schedule that incorporates an exercise event into a basic schedule based on each extracted Pareto solution. Since the five Pareto solutions described above are extracted, the optimization schedule creation unit 144 creates, in response to these, (1) an optimization schedule with the lowest deletion cost, (2) an optimization schedule with the highest amount of exercise for the user, (3) an optimization schedule with the lowest burden on the user, (4) an optimization schedule with the highest timing score, and (5) an optimization schedule with the best balance between objectives. The optimization schedule creation unit 144 is an example of an optimization schedule creation means in the present disclosure.

[0034] Here, an example of an optimized schedule created by the optimized schedule creation unit 144 will be described. Fig. 9 shows an optimized schedule for the purpose of minimizing the deletion cost, in which the free time at the time of waking up is replaced with the exercise event "walking" in the basic schedule shown in Fig. 2.

[0035] Figure 10 shows an optimized schedule aimed at maximizing the amount of exercise by incorporating a high-intensity exercise event, “jogging,” into all three free periods in the morning, afternoon, and evening, in addition to the basic schedule shown in Figure 2.

[0036] Moreover, Figure 11 shows an optimized schedule aimed at maximizing the timing score by incorporating the exercise event “brisk walking” around 7:00 and 19:00, which are the time periods when the timing score is highest, in comparison with the basic schedule shown in Figure 2.

[0037] 1, the schedule proposing unit 145 performs processing for proposing to the user each optimized schedule created by the optimized schedule creating unit 144. Specifically, the schedule proposing unit 145 displays on the display unit 13 a screen displaying a list of each optimized schedule that has been created.

[0038] The storage unit 15 serves as a so-called secondary storage device (auxiliary storage device) and is, for example, a readable / writable non-volatile flash memory, a hard disk drive, etc. The storage unit 15 stores programs and various data executed by the control unit 14. For example, the storage unit 15 stores the various tables described above (exercise event table 151, deletion cost table 152, exercise timing table 153, constraint condition table 154).

[0039] Next, the operation of the schedule creation device 1 will be described. For example, a user who wants to overcome a lack of daily exercise operates the operation unit 12 of the schedule creation device 1 to input a basic schedule, which is the user's basic plan for the day, and instructs execution of a schedule optimization process targeting this basic schedule. In response to this instruction, the control unit 14 executes a schedule proposal process shown in the flowchart of FIG.

[0040] First, as a pre-processing, the pre-processing unit 141 acquires each objective function (removal cost calculation function, exercise amount calculation function, burden amount calculation function, timing score calculation function) for optimizing the basic schedule, and each table (exercise event table 151, removal cost table 152, exercise timing table 153, constraint condition table 154) necessary for multi-objective analysis targeting each objective function, and stores them in the storage unit 15 (step S101). For example, the pre-processing unit 141 can acquire each objective function and each table by having the user input the parameter value of each objective function, the item value of each table, etc. via the operation unit 12. Alternatively, the pre-processing unit 141 may acquire each objective function, each table, etc. from a server (not shown) via the communication unit 11. Note that if each objective function and each table are already stored in the storage unit 15, step S101 may be omitted.

[0041] Next, the basic schedule acquiring unit 142 acquires the basic schedule input by the user (step S102).

[0042] Next, the Pareto solution calculation unit 143 obtains a daily timing score distribution based on the acquired basic schedule and the exercise timing table 153 (step S103). This timing score distribution is used by the timing score calculation function to calculate the timing score from the timing of the exercise event incorporated into the basic schedule.

[0043] Next, the Pareto solution calculation unit 143 performs a multi-objective analysis on each objective function (removal cost calculation function, exercise amount calculation function, burden amount calculation function, timing score calculation function) for optimizing the basic schedule within a range that satisfies the constraint conditions specified in the constraint condition table 154, using an algorithm such as NSGA-II (Elitist Non-dominated Sorting Genetic Algorithm), and calculates multiple Pareto solutions (step S104). Note that the algorithm for performing the multi-objective analysis is not limited to NSGA-II, and the multi-objective analysis may be performed using an algorithm such as SPEA2 (Strength Pareto Evolutionary Algorithm 2), MOEA / D (Multiobjective Evolutionary Algorithm based on Decomposition), IBEA (Indicator-Based Evolutionary Algorithm), or HypE (Hypervolume Estimation Algorithm).

[0044] Next, the Pareto solution calculation unit 143 extracts a Pareto solution that meets a predetermined criterion from among the calculated multiple Pareto solutions (step S105).

[0045] Next, the optimized schedule creation unit 144 creates an optimized schedule for each extracted Pareto solution by incorporating an exercise event into a basic schedule based on the Pareto solution (step S106).

[0046] Next, the schedule suggestion unit 145 displays each of the created optimized schedules on the display unit 13 and suggests the optimized schedules to the user (step S107). For example, the user can eliminate lack of exercise by adopting an optimized schedule that he / she likes from among the multiple displayed optimized schedules and performing exercise according to the adopted optimized schedule every day.

[0047] Thus, according to this embodiment, a multi-objective analysis is performed on multiple objective functions with different objectives for optimizing the basic schedule, with information about the exercise events to be incorporated into the user's basic schedule as design variables, and multiple Pareto solutions are calculated. Then, Pareto solutions that meet a predetermined criterion are extracted from the multiple calculated Pareto solutions, and an optimized schedule is created for each extracted Pareto solution that incorporates exercise events based on the Pareto solution. This makes it possible to create an optimal schedule for the user that meets multiple objectives.

[0048] (Modification) Although an embodiment of the present invention has been described above, the present invention is not limited to the above-described embodiment, and various modifications are possible without departing from the gist of the present invention.

[0049] For example, in the above embodiment, a Pareto solution was calculated by multi-objective analysis of four objective functions, namely, a deletion cost calculation function, a momentum calculation function, a burden calculation function, and a timing score calculation function. However, the multiple objective functions subject to the multi-objective analysis are not limited to these.

[0050] For example, in the above embodiment, a basic schedule for one day is optimized, but the period of the basic schedule that is the subject of the present invention is not limited to one day. For example, the present invention can also be applied when optimizing a basic schedule for one week.

[0051] For example, in the above embodiment, the basic schedule is optimized by incorporating an exercise event into the basic schedule, but a specific event other than an exercise event may be incorporated for optimization. For example, the basic schedule may be optimized by incorporating a study event instead of an exercise event in order to support the study of a user who is a test-taker. In this case, it is necessary to prepare a plurality of objective functions each having a different optimization objective, with information about the study event to be incorporated (study subject, number of questions, difficulty, study time, etc.) as design variables. For example, an objective function for maximizing study time, an objective function for maximizing the difficulty of the questions to be studied, an objective function for minimizing the deletion cost, an objective function for maximizing the study timing score, which is an index for evaluating the timing of studying, etc. In addition, as constraint conditions for the design variables, the minimum number of study questions, the minimum study time, the maximum number of study questions, the maximum study time, time periods when studying is not possible, etc. may be appropriately set.

[0052] For example, if the user's daily behavioral history can be acquired, a schedule can be created that takes the behavioral history into consideration. Specifically, exercise events that are not included in the user's behavioral history (recorded no exercise events) may not be included in the optimized schedule. For example, a constraint condition may be set in advance so that recorded no exercise events are not calculated as Pareto solutions, or Pareto solutions that include recorded no exercise events may be excluded from extraction targets in step S105 of the schedule proposal process shown in FIG. 12.

[0053] For example, when the user's daily action record history and the target value set by the user can be obtained, the Pareto solutions may be extracted in step S105 of the schedule proposal process shown in FIG. 12 by taking these into consideration. Specifically, when the amount of exercise in a day indicated by the action record does not reach the target value, a Pareto solution having an exercise event with an amount of exercise that is increased by a predetermined percentage (e.g., 5%) by the amount of exercise indicated by the action record may be extracted in step S105. In this way, it is possible to propose a schedule that makes it easier to achieve the unachieved goal in the future. Also, when the amount of exercise in a day indicated by the action record reaches the target value, a Pareto solution close to the exercise event included in the action record may be extracted in step S105.

[0054] In the above embodiment, the control unit 14 has been described as functioning as each unit shown in FIG. 1 (pre-processing unit 141, basic schedule acquisition unit 142, Pareto solution calculation unit 143, optimized schedule creation unit 144, schedule proposal unit 145). However, this is merely an example, and the functions of each unit shown in FIG. 1 may be realized by dedicated hardware. Examples of dedicated hardware include a single circuit, a composite circuit, a programmed processor, an ASIC (Application Specific Integrated Circuit), an FPGA (Field-Programmable Gate Array), and combinations of these. The functions of each unit shown in FIG. 1 may be realized by individual hardware, or the functions of each unit may be realized together by a single piece of hardware.

[0055] It should be noted that some of the functions of each unit shown in Fig. 1 may be realized by dedicated hardware, and the remaining functions may be realized by software or firmware. In this way, the functions of each unit shown in Fig. 1 can be realized by hardware, software, firmware, or a combination of these.

[0056] By applying a program for realizing each function of the schedule creation device 1 of the present invention so that it can be executed by a processor that controls an existing information processing device, the existing information processing device can be made to function as the schedule creation device 1 of the present invention.

[0057] Such a program can be applied by any method. For example, the program may be applied by storing it in a computer-readable non-transitory storage medium such as a flexible disk, a CD (Compact Disc)-ROM, a DVD (Digital Versatile Disc)-ROM, or a memory card. Alternatively, the program may be superimposed on a carrier wave and applied via a communication network such as the Internet or a LAN (Local Area Network). Specifically, the program may be posted and distributed on a bulletin board (BBS: Bulletin Board System) on a communication network. Then, a processor that controls an existing information processing device may start up this program and execute it under the control of an OS in the same way as other application programs, thereby realizing each function of the schedule creation device 1 according to the present invention.

[0058] Although the embodiment and the modified examples of the present invention have been described above, the present invention is not limited to these. The present invention includes appropriate combinations of the embodiment and the modified examples, and appropriate modifications thereto.

[0059] The present invention allows various embodiments and modifications without departing from the broad spirit and scope of the present invention. The above-described embodiments are for explaining the present invention and do not limit the scope of the present invention. In other words, the scope of the present invention is indicated by the claims, not the embodiments. Various modifications made within the scope of the claims and within the scope of the meaning of the invention equivalent thereto are considered to be within the scope of the present invention. [Explanation of symbols]

[0060] 1...schedule creation device, 11...communication unit, 12...operation unit, 13...display unit, 14...control unit, 141...pre-processing unit, 142...basic schedule acquisition unit, 143...Pareto solution calculation unit, 144...optimization schedule creation unit, 145...schedule proposal unit, 15...storage unit, 151...motion event table, 152...deletion cost table, 153...motion timing table, 154...constraint condition table

Claims

1. a Pareto solution calculation means for performing a multi-objective analysis on a plurality of objective functions, the design variables of which are information about specific events to be incorporated into the user's basic schedule, within a range satisfying constraint conditions of the design variables, and calculating a plurality of Pareto solutions; A schedule creation device comprising:

2. an optimization schedule creation means for extracting a Pareto solution that meets a predetermined criterion from the plurality of calculated Pareto solutions, and for each of the extracted Pareto solutions, creating an optimization schedule in which the specific event is incorporated into the basic schedule based on the Pareto solution; The schedule creation device according to claim 1 .

3. one of the plurality of objective functions is an objective function for minimizing a deletion cost associated with deleting an event in the basic schedule by incorporating the specific event into the basic schedule; 3. The schedule creation device according to claim 1 or 2.

4. One of the plurality of objective functions is an objective function that aims to maximize a timing score indicating an evaluation of a timing for incorporating the specific event into the basic schedule.

3. The schedule creation device according to claim 1 or 2.

5. the specific event is an event related to the user's exercise, One of the plurality of objective functions is an objective function for maximizing the amount of exercise of the user.

3. The schedule creation device according to claim 1 or 2.

6. the specific event is an event related to the user's exercise, One of the plurality of objective functions is an objective function aimed at minimizing a burden on a user associated with exercise.

3. The schedule creation device according to claim 1 or 2.

7. the optimization schedule creation means extracts, as a Pareto solution that meets the predetermined criterion, a Pareto solution that is most likely to achieve an objective of one of the plurality of objective functions; The schedule creation device according to claim 2.

8. the optimization schedule creation means extracts a Pareto solution that is most balanced with respect to each objective of the plurality of objective functions as a Pareto solution that meets the predetermined criteria; The schedule creation device according to claim 2.

9. A multi-objective analysis is performed on a plurality of objective functions, the design variables of which are information about specific events to be incorporated into the user's basic schedule, within a range that satisfies the constraints of the design variables, and a plurality of Pareto solutions are calculated. How to create a schedule.

10. Computer, a Pareto solution calculation means for performing a multi-objective analysis on a plurality of objective functions, the design variables of which are information about specific events to be incorporated into the user's basic schedule, within a range satisfying constraint conditions of the design variables, and calculating a plurality of Pareto solutions; A program that functions as a

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