Planning device and planning method

Abstract

To achieve allowable constraint relaxation even when it is difficult to identify a constraint satisfaction solution.SOLUTION: A production plan making device 1 makes a plan related to a task. The production plan making device 1 includes: a production history DB2 that stores history information in the task; a past history reading unit 13 which reads the history information; a constraint relaxation unit 12 which identifies a deviation degree indicating a position relationship related to a constraint boundary of a constraint in making the plan of a history represented by the history information, calculates a weight indicating a degree of the constraint for constraint relaxation according to the deviation degree, and relaxes the weight when the plan cannot be made by an optimization process based on the weight; and a mathematical optimization unit 11 which makes the plan by the optimization process on the basis of the relaxed weight.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to a technology for supporting business planning. [Background technology]

[0002] In order to efficiently carry out business operations such as production planning and personnel planning in the industrial field, appropriate planning is necessary. For example, mathematical optimization technology is used to optimize plans.

[0003] When planning a project that includes such plan optimization, constraints on the project must be taken into consideration. For example, it is necessary to identify a solution that satisfies the constraints. However, there are cases where a solution that satisfies the constraints cannot be found even after a long time. In such cases, one option is to perform constraint relaxation, which relaxes the constraints on the project.

[0004] Here, Patent Document 1 proposes the following configuration for "creating an appropriate production plan that is in line with the actual situation at the site." Patent Document 1 describes that "the production planning device stores information about production plans that have been created in the past, and, based on the information, generates learning results that are the result of learning relaxation priorities, which are priorities for relaxing each of a plurality of constraints, and information used to predict at least one of the relationships between upper and lower limit setting values ​​of constraint variables when the constraints are relaxed, the leveling rate when the constraints are relaxed, and the relationships between the constraint variables when the constraints are relaxed, generates prediction results that are the result of predicting at least one of the relationships between upper and lower limit setting values ​​of constraint variables, the leveling rate, and the relationships between the constraint variables when each of the plurality of constraints is applied, based on the learning results, and creates a production plan that can satisfy all of the plurality of constraints by relaxing the constraints based on the prediction results." [Prior art documents] [Patent documents]

[0005] [Patent Document 1] Japanese Patent Application Publication No. 2018-120342 Summary of the Invention [Problem to be solved by the invention]

[0006] In Patent Document 1, the relaxation priority is manually or otherwise given as a constant in advance, and constraints are removed in the order of relaxation priority to determine whether or not the constraints can be satisfied. In this way, Patent Document 1 determines only whether or not to remove a constraint, so if one tries to remove all constraints, the accuracy of the plan may decrease depending on the selection.

[0007] Therefore, an object of the present invention is to realize an allowable constraint relaxation even when it is difficult to identify a constraint satisfying solution. [Means for solving the problem]

[0008] To solve the above problem, the present invention provides a planning device for creating a plan for a business operation, comprising: a storage device for storing history information of the business operation; and a processing device connected to the storage device, which reads the history information in accordance with a program, identifies a degree of deviation indicating a positional relationship of the history indicated by the history information with respect to a constraint boundary of a constraint in creating the plan, calculates a weight indicating a degree of constraint relaxation for the constraint according to the degree of deviation, and, if a plan cannot be created by an optimization process based on the weight, relaxes the weight, and creates the plan by the optimization process based on the relaxed weight. The present invention also includes a planning method using the planning device, a program for causing the planning device to function as a computer, and a storage medium for storing the program. [Effects of the Invention]

[0009] According to the present invention, even when it is difficult to identify a constraint satisfying solution, it is possible to create a plan that accommodates allowable constraint relaxation. [Brief explanation of the drawings]

[0010] [Figure 1] FIG. 2 is a functional block diagram of the production management system according to the first embodiment. [Figure 2] 1 is a hardware configuration diagram of a production planning device according to a first embodiment. [Figure 3] 1 is a flowchart showing a processing flow in the first embodiment. [Figure 4] FIG. 10 is a diagram showing order-product information used in the first embodiment. [Figure 5] FIG. 10 is a diagram showing order-man-hour information used in the first embodiment. [Figure 6] FIG. 10 is a diagram showing man-hour-product information used in the first embodiment. [Figure 7] FIG. 10 is a diagram showing history-delivery date information used in the first embodiment. [Figure 8] 10 is a flowchart showing a constraint relaxation processing flow in the first embodiment. [Figure 9] FIG. 10 is a diagram showing display contents showing the relationship between delivery lead times for each product in the first embodiment. [Figure 10] FIG. 10 is a diagram showing relaxed delivery date information included in the production plan in the first embodiment. [Figure 11] FIG. 10 is a diagram showing worker group schedule information included in the production plan in the first embodiment. [Figure 12] FIG. 10 is a diagram showing worker schedule information included in the production plan in the first embodiment. [Figure 13] FIG. 10 is a diagram showing display contents showing the relationship between delivery lead times for each product in the second embodiment. [Figure 14] FIG. 10 is a hardware configuration diagram of a production planning system according to a third embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0011] An embodiment for carrying out the present invention will be described below. This embodiment targets plan optimization such as production planning and personnel planning. This embodiment proposes a technique for identifying an acceptable solution in plan optimization, even when it is difficult to find a constraint-satisfying solution due to strict constraints. That is, this embodiment relaxes constraints to identify a constraint-satisfying solution that satisfies the constraints. At this time, it is desirable to perform constraint relaxation acceptable to the planner. More specifically, constraint relaxation is performed according to the degree of deviation of historical information related to the work. More desirably, the smaller the degree of deviation, the greater the weight of the constraint. In other words, the smaller the degree of deviation, the more important the constraint, i.e., the higher the evaluation. As described above, this embodiment targets a planning device for work such as production, and in the following examples, a production planning device will be described as an example of a planning device.

[0012] Furthermore, the deviation in this embodiment is an index indicating the positional relationship of the histories with respect to the constraint boundary, including distance and density. Here, when distance is used as the deviation, the closer to the constraint boundary the deviation is, the smaller the deviation. Furthermore, when density is used as the deviation, the closer the positional relationship between multiple histories is, the smaller the deviation is. Furthermore, in this embodiment, a combination of distance and density may be used as the deviation.

[0013] The deviation degree only needs to indicate the relationship between the constraint boundary and the history in the planning process, and includes other factors besides near and far and dense. In this embodiment, the constraint weight and the objective function value are determined, and the constraint is relaxed in accordance with the determined constraint weight. Optimization can then be achieved using the objective function value. Below, an example showing the specific contents of this embodiment will be described. [Example]

[0014] (Overall composition) 1 is a functional block diagram of a production management system in Example 1. The production management system has a production planning device 1, a production history DB 2, and a production device 3. The production planning device 1 is a device for creating a production plan for the production device 3. The production planning device 1 also has a mathematical optimization unit 11, a constraint relaxation unit 12, a past history reading unit 13, a relaxed constraint display unit 14, and a production status input / output unit 15.

[0015] Here, the mathematical optimization unit 11 formulates a production plan. To this end, the mathematical optimization unit 11 executes an optimization process. In the optimization process, weights (constraint weights) indicating the degree of constraints identified by the constraint relaxation unit 12 (described later) and objective function values ​​are used. Note that it is desirable for the mathematical optimization unit 11 to use, as weights, constraints that are relaxed from predetermined constraints. In addition, it is sufficient to use at least the constraint weights identified by the constraint relaxation unit 12 in the optimization process.

[0016] The constraint relaxation unit 12 also relaxes constraints in the optimization process according to the constraint boundary and the corresponding history deviation. Specifically, the constraint relaxation unit 12 specifies the weight of the relaxed constraint and the objective function. Here, the deviation is an index indicating the relationship between the constraint boundary and the corresponding history, and includes near and far and dense.

[0017] Furthermore, the past history reading unit 13 reads information and data used in the processing of this embodiment, such as the history described above, from the production history DB 2. The read history is used by the constraint relaxation unit 12. Furthermore, the relaxed constraint display unit 14 displays the relationship between the constraint boundary and the corresponding history. The displayed content will be described later with reference to FIG. 9, and the displayed content also makes it possible to intuitively grasp the degree of deviation.

[0018] Furthermore, the production status input / output unit 15 connects to the production equipment 3 and exchanges information related to the production status. The production status input / output unit 15 outputs the production plan formulated by the mathematical optimization unit 11 to the production equipment 3 as information related to the production status, and inputs the production status from the production equipment 3.

[0019] The production history DB2 is a type of storage device that stores history data related to production by the production equipment 3, etc. These will be described later. The production equipment 3 carries out production of products, etc. in accordance with a production plan formulated by the production planning device 1.

[0020] Next, an implementation example of the production planning device 1 in the first embodiment will be described. FIG. 2 is a hardware configuration diagram of the production planning device 1 in the first embodiment. In FIG. 2, the production planning device 1 can be realized by a computer. Therefore, as shown in FIG. 2, the production planning device 1 has a CPU 101 (Central Processing Unit), a memory 102, a network interface 104, a keyboard 105, a mouse 106, a screen 107, and a hard disk 108, which are connected to each other via an interface 103. Furthermore, it is desirable that the interface 103 be connected to a production history DB2 (storage device). However, if the production history DB2 is configured as an external file server, it will be connected to the network interface 104.

[0021] First, the CPU 101 is an example of a so-called processor (processing device), and executes processing in accordance with a production planning program 110 stored in a hard disk 108. This processing includes processing by the mathematical optimization unit 11, constraint relaxation unit 12, and past history reading unit 13 shown in Fig. 1. Furthermore, information included in the production planning program 110 and table group 120 used for processing by the CPU 101 is expanded in the memory 102.

[0022] The interface 103 can be realized by a bus, connecting the various components of the production planning device 1. The network interface 104 can connect to a network and perform the function of the production status input / output unit 15 in FIG.

[0023] The keyboard 105 and the mouse 106 are input devices that accept operations from the user. The keyboard 105 and the mouse 106 are examples of input devices, and at least one of them may be used. Other input devices may also be used. Furthermore, the input devices may be omitted.

[0024] Furthermore, the screen 107 is a display screen that displays the processing results of the CPU 101 and inputs from the input device. Therefore, the screen 107 can execute the function of the relaxed constraint display unit 14 in FIG. 1. Note that the screen 107 may be omitted and the above content may be displayed on a separate device, or a configuration may be provided for outputting the content by printing or audio. In other words, the production planning system 1 can be provided with some kind of output device that outputs various information described below.

[0025] Furthermore, the hard disk 108 stores the production planning program 110 and a table group 120. The hard disk 108 may be realized by various storage media such as an external HDD (Hard Disk Drive), SSD (Solid State Drive), or memory card. Furthermore, it may be realized by a device separate from the production planning device 1, such as a file server. In other words, the production history DB2 in FIG. 1 may correspond to the hard disk 108. This concludes the description of the configuration of the first embodiment.

[0026] (Processing flow and information) Next, a description will be given of the processing flow of the first embodiment and the information used in this processing flow. Fig. 3 is a flowchart showing the processing flow in the first embodiment. The contents will be described below using the configuration shown in Fig. 1.

[0027] First, in step S101, the past history reading unit 13 reads the order-product information 121 of the product that is the subject of the production plan to be formulated from the production history DB2. This step may be executed in response to an instruction from a user, or may be executed automatically when a predetermined condition is met. Here, FIG. 4 is a diagram showing the order-product information 121 used in the first embodiment. The order-product information 121 is information about the delivery of the product to be produced for each order. More specifically, the order-product information 121 has the following items for each order: product name, quantity, and delivery date.

[0028] In step S102, the past history reading unit 13 reads the order-product information 121 read in step S101. Constraints in the production plan corresponding to the above are read from the production history DB2. In this embodiment, order-man-hour information 122 and man-hour-product information 123 are read as constraints. That is, order-man-hour information 122 and man-hour-product information 123 corresponding to the product and man-hours in the order-product information 121 are read. Here, FIG. 5 is a diagram showing the order-man-hour information 122 used in the first embodiment. The order-man-hour information 122 is information about the process of the product to be produced for each order. More specifically, the order-man-hour information 122 has items for the required man-hours, number of employees, and minimum number of days for each order. Here, the minimum number of days indicates the number of days required to achieve the corresponding required man-hours with the number of employees. In this way, the constraints in the first embodiment indicate the required man-hours in the production of the product.

[0029] 6 is a diagram showing man-hour-product information 123 used in the first embodiment. Man-hour-product information 123 is information for managing processes (man-hours). More specifically, man-hour-product information 123 has items for the product name and its man-hours for each process identification information (#). Man-hours here indicate the number of days required by one worker to produce one product.

[0030] In step S103, the mathematical optimization unit 11 executes an optimization process using an objective function according to the loaded constraints to create a production plan for the order-product information 121. In step S104, the mathematical optimization unit 11 determines whether there is a solution to the minimization process that satisfies the loaded constraints, i.e., whether there is a production plan. As a result, if there is a solution (YES), the process proceeds to step S106. If there is no solution (NO), the process proceeds to step S105.

[0031] Furthermore, in step S105, the constraint relaxation unit 12 relaxes the constraints read in step S102 using the history related to the production planning. Here, in the first embodiment, the past history reading unit 13 reads the history-delivery date information 124 as the history related to the production planning. FIG. 7 is a diagram showing the history-delivery date information 124 used in the first embodiment. As shown in FIG. 7, the history-delivery date information 124 is information indicating examples (history) of products and their delivery date margins. Here, the delivery date margin is indicated by the number of days difference from the requested or scheduled delivery date. For example, past history 1 indicates that product A was delivered five days late, and past history 2 indicates that product A was delivered on time. Furthermore, past history 3 indicates that product A was delivered five days early, that is, with that margin of error.

[0032] An example of the constraint relaxation process in step S105 using the history-delivery date information 124 will be described below. Fig. 8 is a flowchart showing the constraint relaxation process flow in the embodiment 1. In step S1051, the constraint relaxation unit 12 reads the past history, that is, the history-delivery date information 124.

[0033] Furthermore, steps S1052 to S1054 are repeated for each product that is the subject of the production plan. First, in step S1052, the constraint relaxation unit 12 extracts history related to the creation of the production plan from the read history-delivery date information 124. In other words, the past history of the product that is the subject of the production plan is extracted. Here, when creating a production plan for order 1 in FIG. 4, past histories 1 to 3 including product A in FIG. 7 are extracted.

[0034] In step S1053, the constraint relaxation unit 12 calculates the weight of the constraint for the extracted past history. To this end, in this embodiment, the constraint relaxation unit 12 first calculates the standard deviation as an example of the average value and the variance value using (Equation 1) and (Equation 2).

[0035]

number

[0036]

number

[0037] Here, in (Equation 1) and (Equation 2), X indicates the "delivery margin" and N indicates the number of extracted past histories. As a result, the constraint relaxation unit 12 calculates the average value using (Equation 1) and applies this result to (Equation 2) to calculate the standard deviation. Here, the standard deviation indicates the deviation between the constraint boundary and the history. Therefore, this standard deviation can be used as an example of the degree of deviation.

[0038] Alternatively, it may be used as a deviation based on the distance between the past history and the constraint boundary. To this end, the constraint relaxation unit 12 calculates the distance from the constraint boundary for each loaded past history. Then, the constraint relaxation unit 12 sets the inverse of the calculated distance as the weight of the history. Furthermore, the constraint relaxation unit 12 allocates the constraint boundary according to the weight, and sets the weight of the allocated constraint section as the weight.

[0039] Next, in step S1054, the constraint relaxation unit 12 determines whether calculation of weights for products that are the subject of the production plan has been completed, and if not, executes the processes from S1052 onwards for the remaining products. If calculation of weights for products that are the subject of the production plan has been completed, the process proceeds to step S1055.

[0040] Furthermore, in step S1055, the constraint relaxation unit 12 relaxes the weight calculated in step S1053. Here, in this embodiment, to relax the weight, a standard deviation, which is an example of the degree of deviation, is used. Then, the constraint relaxation unit 12 determines whether the constraint (weight) before relaxation is equal to or less than a predetermined threshold (ci) using (Equation 3). Here, a constraint (weight) being equal to or less than the predetermined threshold (ci), that is, being small, means that the standard deviation is large. This also means that the degree of deviation is equal to or greater than a predetermined value. The threshold (ci) may be stored in advance in the production planning device 1, or may be received from a user.

[0041]

number

[0042] When using the deviation based on the distance between the past history and the constraint boundary, the constraint relaxation unit 12 performs relaxation using a straight line connecting the constraint boundary and the past history.

[0043] Then, if the constraint (weight) before relaxation is equal to or less than a predetermined threshold (ci), the constraint relaxation unit 12 relaxes the weight of the constraint using (Equation 4) according to the standard deviation, which is an example of the deviation degree, i.e., calculates the relaxed constraint (weight).

[0044]

number

[0045] In step S1056, the constraint relaxation unit 12 applies the calculated relaxed constraints (weights) to (Equation 5) to calculate the objective function.

[0046]

number

[0047] This concludes the explanation of the flowchart in FIG. 8, i.e., the constraint relaxation process (step S105), and we return to the explanation of FIG. 3. If the constraints are relaxed in step S105, the process proceeds to step S103. In step S103, the mathematical optimization unit 11 executes optimization processing using the objective function corresponding to the relaxed constraints, i.e., the objective function calculated in step S1056, to formulate a production plan. As a result, a production plan with an extended delivery date is formulated for products that cannot or are difficult to produce within the original delivery date. Then, in step S104, step S105 is repeated until a solution of the minimization processing that satisfies the restricted constraints is found.

[0048] Then, if a solution of the minimization process that satisfies the relaxed constraints exists, in step S106, the relaxed constraint display unit 14 displays the proposed production plan. At this time, in addition to the production plan, the relationship of the delivery lead time for each product may also be displayed. The contents of this display will be explained. FIG. 9 is a diagram showing the display content showing the relationship of the delivery lead time for each product in Example 1. In FIG. 9, the delivery lead time, which is the past history regarding the delivery lead time, is plotted and displayed for each product. In Example 1, delivery lead time = 0 (no delivery lead time) is set as the constraint boundary. By displaying FIG. 9, it is possible to intuitively grasp the deviation degree regarding the delivery lead time. In the example of FIG. 9, product C is the farthest from the constraint boundary in terms of distance from the constraint boundary. In other words, when distance is used, the deviation degree of product C is the largest. Furthermore, in the example of FIG. 9, the average of the past history (delivery lead time) of product A is 0, and the distance from the constraint boundary is the smallest, but the variance of each past history is the largest. In this case, either one of them may be used as the deviation, or a deviation that takes into account both the distance and the dispersion according to a predetermined rule or formula may be used.

[0049] 10 to 12 show information indicating the contents of the production plan formulated in the first embodiment. FIG. 10 is a diagram showing relaxed delivery date information 125 included in the production plan in the first embodiment. The relaxed delivery date information 125 has the same structure as the order-product information 121 shown in FIG. 4, but indicates a relaxed delivery date. As such, since the relaxed delivery date information 125 has the same structure as the order-product information 121, it is also possible to provide either one and update the delivery date as appropriate.

[0050] 11 is a diagram showing worker group schedule information 126 included in the production plan in Example 1. The worker group schedule information 126 is information indicating the schedule (plan) for producing products for each of multiple workers (workers 1-5). FIG. 11 shows that workers 1-5 will produce product B, product C, and product A in that order.

[0051] FIG. 12 is a diagram showing worker schedule information 127 included in the production plan in the first embodiment. The worker schedule information 127 is information indicating the schedule (plan) for producing products for each worker. FIG. 12 shows that each worker will produce product B, product C, and product A in that order. It is sufficient to provide at least one of worker group schedule information 126 and worker schedule information 127. This concludes the explanation of the first embodiment, and in the first embodiment, it is possible to perform appropriate constraint relaxation according to the degree of deviation. [Example]

[0052] In the second embodiment, a different display is performed from that in the first embodiment. FIG. 13 is a diagram showing the display contents showing the relationship between delivery margins for each product in the second embodiment. In FIG. 13, a histogram is displayed in addition to the display contents of the first embodiment. The histogram is information showing the total number of past histories for each product for each delivery margin. FIG. 13 shows that there are more past histories with a positive delivery time (with margin) than those with a delivery time of 0 or a negative time (no margin). In this way, according to the second embodiment, it is possible to intuitively grasp the status of the past histories. [Example]

[0053] In the third embodiment, the production planning device 1 is implemented by a server such as a cloud server. FIG. 14 is a hardware configuration diagram of a production planning system in the third embodiment. In the third embodiment, the production planning device 1 is connected to the production devices 3 and a management terminal group 70 via a network 60. The management terminal group 70 can be implemented by a computer such as a PC or a tablet. The management terminal group 70 receives operations from users and notifies the production planning device 1 of the operations. As a result, the production planning device 1 executes processing in accordance with the operations. The management terminal group 70 receives and outputs the processing results of the production planning device 1. For example, the display contents and the formulated production plans in the first and second embodiments are output. The users who use the management terminal group 70 include the person in charge of production management.

[0054] Furthermore, the production planning system 1 of the third embodiment is realized by a server, but has similar hardware as a computer to that of the first embodiment. That is, the production planning system 1 of the third embodiment has a CPU 101, a memory 102, a network interface 104, and a hard disk 108, which are connected to each other via an interface 103. However, the keyboard 105, mouse 106, and screen 107 of the first embodiment can be omitted in this embodiment because the management terminal group 70 has the functions thereof. Furthermore, the hard disk 108 corresponds to the production history DB2 in FIG. 1, but it can also be externalized as in the first embodiment.

[0055] A production planning program 110 and a table group 120 are stored in a storage medium represented by a hard disk 108. These are the same as those explained in the first embodiment, and the contents thereof will be briefly explained below.

[0056] First, the production planning program 110 has a mathematical optimization module 111, a constraint relaxation module 112, and a past history reading module 113. Each of these modules executes the same processing as each unit in Fig. 1. That is, the mathematical optimization module 111 corresponds to the mathematical optimization unit 11, the constraint relaxation module 112 corresponds to the constraint relaxation unit 12, and the past history reading module 113 corresponds to the past history reading unit 13. Furthermore, each piece of information that makes up the table group 120 has already been explained with reference to Figs. 4 to 7 and 10 to 12.

[0057] In the third embodiment, production plans for a plurality of production devices may be made by the production planning device 1. Furthermore, the production planning device 1 may be realized as a production management device that executes production management.

[0058] In the third embodiment described above, the production planning device 1 can be realized as a server, so that the operating costs of the production device 3 can be reduced.

[0059] The above-described embodiments are merely examples of the present invention, and the present invention includes various modifications and applications. For example, at least one of distance and variance may be used as the deviation, or other parameters may be used. Furthermore, the present invention can be applied to applications other than production planning. For example, the present invention can be applied to the formulation of maintenance plans (including modifications) for equipment and facilities, and the formulation of operation plans for equipment, etc. [Explanation of symbols]

[0060] 1...production planning device, 11...mathematical optimization unit, 12...constraint relaxation unit, 13...past history reading unit, 14...relaxed constraint display unit, 15...production status input / output unit, 101...CPU, 102...memory, 103...interface, 104...network interface, 105...keyboard, 106...mouse, 107...screen, 108...hard disk, 110...production planning program, 111...mathematical optimization module, 112...constraint relaxation module, 113...past history reading module, 120...table group, 121...order-product information, 122...order-man-hour information, 123...man-hour-product information, 124...history-delivery date information, 125...relaxed delivery date information, 126...worker group schedule information, 127...worker schedule information, 2...production history DB, 3...production device

Claims

1. A planning device for creating a business plan, a storage device that stores history information of the business; A device connected to the storage device and configured to: Read the history information; Identifying a deviation indicating a positional relationship of the history indicated by the history information with respect to a constraint boundary of the constraint in the planning of the plan; calculating a weight indicating a degree of constraint for relaxing the constraint according to the degree of deviation; If a plan cannot be formulated by the optimization process based on the weights, the weights are relaxed; A planning device having a processing device that creates the plan through the optimization process based on the relaxed weights.

2. The planning device according to claim 1, The degree of deviation is at least one of the distance between the history and the constraint boundary and the density of the history.

3. 3. The planning device according to claim 2, The constraint is the number of man-hours required to produce the product, The processing device is a planning device that creates a production plan for the product with an extended delivery date for the product based on the relaxed weight.

4. 4. The planning device according to claim 3, The processing device is a planning device that uses, as the constraints, order-man-hour information related to the process of the product and man-hour-product information for managing the process of the product.

5. 4. The planning device according to claim 3, The planning device further comprises an output device that outputs the relationship with the delivery margin for each product.

6. 6. The planning device according to claim 5, The output device further outputs a histogram indicating the total number of past product histories.

7. A planning method using a planning device that creates a plan for a task using a computer, comprising: a storage device stores history information of the business; A processing device connected to the storage device performs the following steps according to a program: Read the history information; Identifying a deviation indicating a positional relationship of the history indicated by the history information with respect to a constraint boundary of the constraint in the planning of the plan; calculating a weight indicating a degree of constraint for relaxing the constraint according to the degree of deviation; If a plan cannot be formulated by the optimization process based on the weights, the weights are relaxed; A planning method comprising: a processing device that generates the plan by the optimization process based on the relaxed weights.

8. 8. The planning method according to claim 7, A planning method in which the degree of deviation is at least one of the distance between the history and the constraint boundary and the density of the history.

9. 9. The planning method according to claim 8, The constraint is the number of man-hours required to produce the product, The planning method includes the processing device creating a production plan for the product with an extended delivery date based on the relaxed weight.

10. 10. The planning method according to claim 9, The planning method, in which the processing device uses, as the constraints, order-man-hour information relating to the process of the product and man-hour-product information for managing the process of the product.

11. 10. The planning method according to claim 9, Furthermore, the output device may include a device for outputting a relationship with a delivery margin for each of the products.

12. The planning method according to claim 11, The planning method further includes outputting a histogram indicating the total number of past product histories.

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