JP2005056024A - Support system and support method for creating supply plan, and supporting computer program - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To solve the problem wherein, in a decision making scene of deciding a combination (scenario) of supply volumes or supply capacities about one or more products or one or more services in each kind of business, it has been difficult to make a decision upon sufficient comparison and examination of probability distributions of an evaluation index about a plurality of scenarios. <P>SOLUTION: With demand forecast data and statistical data, a user selects weighted indices from a plurality of evaluation indices such as profit, sales and opportunity loss, whereupon optimal solutions to a combination of a plurality of supply volumes or supply capacities are displayed on an efficient frontier with the selected evaluation indices on the axis of ordinates and the axis of abscissas, a polygon based on a plurality of indices and the like. The provided scheme to support the user's selection of a scenario matching the management policy on comparison of probability distributions of evaluation indices on the set in each optimal solution can support the scenario decision. <P>COPYRIGHT: (C)2005,JPO&NCIPI

Description

  The present invention relates to a support system and a support method for creating a supply plan for a product or service, and a computer program for support.

The following technologies are related to a system or a computer program that supports the work of determining the supply amount and supply capacity of a supply target for products and services under limited resources. For example, see Patent Document 1 and Patent Document 2.
Patent Document 1 describes a technique for calculating an expected value of inventory costs and an expected value of sales profit from demand prediction, and calculating one supply amount from these values.
Patent Document 2 describes a technique for calculating one optimal supply allocation solution for a plurality of supply sources based on the constraint information of each supply source.
Patent Document 3 calculates the efficient frontier of a combination (portfolio) of each financial product based on the risk and return information of the financial product, and calculates the upper limit and lower limit values of the target return and allowable risk. It describes how to calculate one optimal portfolio.
JP-A-9-73491 JP-A-9-44204 JP 2001-76057 A

In the manufacturing and service industries, there is a limit to the capacity of resources to supply products and services. In order to achieve the best possible evaluation index under the limited supply capacity, the operator should set the desired short-term supply amount (hereinafter referred to as “optimum”) and the medium-to-long-term supply capacity. It is necessary to create a plan.
However, based on the past demand actual statistics, the future demand forecast and its confidence interval (difference between expected demand and actual demand, which is predicted to occur statistically in the future based on past data) It is desirable to create a plan that takes into account In spite of the circumstances described above, the solution for optimizing the priority evaluation index while quantitatively determining the index such as risk and return has not been reflected as the actual supply amount or supply capacity of the product or service. It is desirable to provide a support system, a support method, and a program for support so that a desirable plan can be created while judging priority evaluation indexes.

  One of the objects of the present invention is to provide a system or method for creating a supply plan for a product or service that is easy to use, and a computer program for realizing the system or method.

One of the solutions according to the present invention is that the supply quantity or supply capacity information to be determined is input information including demand forecast information and demand forecast confidence interval information, accounting information including cost information, and resource information including supply capacity information. , Calculate multiple combined solutions of supply quantity or supply capacity for the supply object, and for the multiple solutions derived by calculation, probability distribution of each evaluation index, supply quantity or supply capacity information, demand forecast information, accounting information, supply Is to provide a means for quantitatively and visually comparing the load information generated by each.
In addition, one of the other solution means that one solution from the plurality of solutions can be easily selected with reference to each evaluation value, so that the solution of the actual supply amount or supply capability can be accurately determined. In addition, it provided a function to support the formulation of supply plans by making decisions efficiently.

  According to the present invention, a user-friendly system or method for creating a supply plan for a product or service, and a computer program for realizing the system or method can be obtained.

Embodiments of the present invention will be described in detail with reference to the drawings.
FIG. 1 is an overall configuration diagram of a computer system showing an embodiment of the present invention, and FIGS. 2 to 5 are databases of the system. 6, 7, and 10 are process flow diagrams in one embodiment of the present invention, and FIGS. 8, 9, 11 to 26 are diagrams showing screen transitions and screen images of processes in one embodiment of the present invention. Hereinafter, it demonstrates in order.

  In FIG. 1, the database included in the system is stored in the storage units 101 to 104, information related to demand prediction held in the storage unit 101, information related to resources held in the storage unit 102, and stored in the storage unit 103. Information relating to accounting, and information relating to the supply plan held in the storage unit 104. The multipurpose multi-optimal solution calculation unit 203 uses the multiple evaluation value calculation unit 204 to calculate a plurality of combinations of desired supply amounts or supply capacities. Information on demand prediction is input from the information input unit 201 regarding demand prediction, and stored in the storage unit 101 for demand prediction information. The plurality of evaluation value calculation units 204 includes a demand amount simulation unit 205 and an evaluation index calculation unit 206 for accounting information.

The user interface 209 includes the following three functions.
The first function is a supply amount or supply capacity selection user interface for selecting one combination from a plurality of supply amounts or supply capacity combinations. Selection section).
The second function is a resource information editing unit 213, a transaction information editing unit 214, and a demand prediction information editing unit 215, which are user interfaces for editing resource information, accounting information, and demand prediction information that are preconditions for processing calculation.
A third function is a supply plan editing unit 212 which is a user interface for editing a supply plan.

  Here, the demand forecast information means demand forecast information for the supply target. The supply value means a supply amount or a supply capacity value. Furthermore, the resource information means information on resources for supplying the supply target, and the resource consumption information means information on the amount of resources consumed when supplying each supply target. The supply target is a product or service.

  FIG. 2 shows the contents of the demand forecast information stored in the demand forecast information storage unit 101 shown in FIG. As shown in the table (a) of FIG. 2, the information related to the demand forecast information (probability distribution direct designation type) consists of the product / service name in the column direction, the demand amount and the probability belonging to it, and the data in the row direction. There are multiple lines. Further, as shown in the table (b) of FIG. 2, the information related to the demand forecast information (probability distribution parameter designation type) is composed of the product / service name, the demand amount and the probability belonging to the column direction, and those information in the row direction. There are multiple lines of data. In addition,... 216 and... 217 are data display abbreviation symbols, and further indicate that data is continuously displayed.

  FIG. 3 shows an example of the resource information in the resource information storage unit 102 and the accounting information in the accounting information storage unit 103 shown in FIG. 1, which is an embodiment in the manufacturing industry of the present invention. As shown in FIG. 3 (a), the information related to the accounting information consists of product / service names and sales unit prices, supply costs, storage costs, inventory at the beginning, and opportunity loss conversion in the column direction. There are multiple lines of data. Further, as shown in FIG. 3B, the information on the resource consumption information used for supply includes a product / service name and its associated resources, consumption, and resource capability in the column direction, and the row direction. There are multiple lines of such data. In this example, if the supply of the product exceeds the demand, inventory is generated, so information related to inventory management costs is managed and described in the accounting information. In addition to inventory management costs, there may be cases where accounting information requires data on transportation costs necessary to move the supplied products, and data on disposal costs associated with the obsolescence or expiration of the products supplied. It is also possible to manage these data. In addition,... 301 and... 302 are data display abbreviations, and indicate that data is continuously displayed.

  FIG. 4 shows an example of resource information in the resource information storage unit 102 and accounting information in the accounting information storage unit 103 shown in FIG. 1 as an embodiment in the service industry (call center business) of the present invention. As shown in FIG. 4 (a), the information related to the accounting information includes the product / service name and the contract unit price, supply cost, opportunity loss conversion in the column direction, and there are multiple rows of the data in the row direction. ing. Further, as shown in FIG. 4B, the information on the resource consumption information used for supply includes a product / service name and its associated consumption resource, consumption, and resource capability in the column direction, and the row direction. There are multiple lines of such data. In the case of this embodiment, since the skills required for resources that can be handled by each service are different, the resource skills and the corresponding information are described. In addition to skill information, if it is a machine that provides services, it is necessary to include information on running costs and information on maintenance costs in accounting information. According to the method of this embodiment, such information is managed. It is also possible. In addition,... 401 and... 402 are data display abbreviations, and indicate that data is continuously displayed.

  3 and 4, the maximum supply value of each period is provided by the resource capability set in the resource information storage unit 102 by the method of this embodiment. In this case, in the supply capacity plan, the supply value of the supply target matches the supplyable value based on the resource capacity. In this case, the accounting information includes data such as the maximum funds for capital investment or employment, the amount of investment according to the increase in resource capacity, the maintenance cost required for each period, and depreciation expenses. In addition, the resource information includes data on the effective period of equipment or employment. Further, the system shown in the present embodiment has a function of restricting the supply value and the like within the range of the supply value depending on the resource capacity. When performing a simulation while performing constraints, techniques used in a constraint-oriented engine, interval value calculation engine, simultaneous inequality calculation engine, and the like are used.

FIG. 5 shows profit probability distribution information as an example of output data of the multi-evaluation value calculation unit 204 shown in FIG. 1 according to an embodiment of the present invention. The information regarding the supply plans (1) and (2) shown in (a) of FIG. 5 includes product / service names in the column direction and supply plans belonging thereto, and there are a plurality of rows of data in the row direction. . In the probability distribution information shown in the table (b) of FIG. 5, the column direction includes a range of expected profits and the corresponding probabilities, and a plurality of rows of data exist in the row direction. The probability distribution of (b) (1) is the probability distribution of the supply plan (1) of (a), and the probability distribution of (2) of (b) is the probability of the supply plan (2) of (a). Mean distribution.
Probability distribution information of profit expected by the supply plan (1) in (a) is represented by a curve 501 shown in (c). This curve 501 is a scenario in which the shape of the distribution is relatively small in kurtosis, and it is highly likely that a high profit will be obtained, but there is a high possibility that it will be deficit. The probability distribution information of the profit expected by the supply plan (2) in (a) is a curve 502 in the graph shown in (c). A curve 502 is a scenario in which the shape of the distribution is relatively high in kurtosis, and it is unlikely that high profit will be obtained, but it is also unlikely that a deficit will occur. Further,... 503 and... 504 are data display abbreviations, and indicate that data is continuously displayed.

The details of the function of each means shown in FIG. 1 will be described below.
The multi-objective / multi-optimal solution calculation unit 203 optimizes a combination for achieving the user's purpose regarding the supply amount of the supply target or the supply capability of the supply target. The multi-purpose multi-optimal solution means a plurality of optimal solution candidates having different target indices. Hereinafter, the term “multiple optimal solutions” means a plurality of candidates for determining optimal solutions, which are formed from combinations of supply plans, derived from different constraint information and calculation methods.
First, the multi-objective / multi-optimal solution calculation unit 203 reads resource information stored in the resource information storage unit 102. Next, a set of supply amount or supply capability represented by the multi-optimal solution calculated by the multi-objective multi-optimal solution calculation unit 203 is evaluated using a function provided by the multi-evaluation value calculation unit 204. In this function, an evaluation value of supply amount or supply capacity is designated as an evaluation value of one supply plan, and a plurality of desirable solutions relating to evaluation values are determined based on parameter settings for calculating a desirable solution shown in FIG. Can be sought. Information relating to a combination of the plurality of supply amounts or supply capacities is stored in the supply plan information storage unit 104. In the case of information of a combination of supply capacity plans, the information is also stored in the supply plan information storage unit 104 and the resource information storage unit 102 at the same time. The multi-evaluation value calculation unit 204 evaluates a combination of supply amounts or supply capacities in units of supply periods calculated by the multi-objective multi-optimal solution calculation unit 203 using a plurality of evaluation indexes. The multi-evaluation value calculation unit 204 evaluates a set of supply amount or supply capacity (upper limit value of supply amount) O1 to On for the demand amount of N products or the demand for N types of services.

  The flow of computer processing related to the above evaluation will be described below along the flow of FIG. The alphanumeric character “S” is the initial letter of the number representing each step of the flow. First, the profit frequency table is initialized. In the profit frequency table, when a plurality of simulations are performed during one evaluation, a value indicating how many times a certain profit appears during the plurality of simulations is displayed. In the initialization step S1001, all the frequencies are initialized to zero. Subsequently, a plurality of simulations are performed in the next steps S1002, S1003, S1004, S1005, and S1006. In step S1003, first, the demand amount simulation unit 205 is used to simulate demand amounts d1 to dn of N products or N types of services. Subsequently, with the supply values O1 to On of the N products or N types of services, the evaluation index when the demand is d1 to dn is calculated using the evaluation index calculation unit 206.

In step S <b> 1003, demand forecast information is read by the demand amount simulation unit 205 via the demand forecast information input unit 201. The demand amount simulation unit 205 first generates random numbers according to the probability distribution of the demand prediction information for N supply targets, and sets the set of random numbers as a set of demand amounts for each supply target. The demand forecast information input unit 201 reads demand forecast information in the demand forecast information storage unit 101. This demand prediction information has data indicating the probability distribution of the demand amount of each supply target. This data specifies a probability distribution direct specification type for directly specifying a demand amount and its probability as shown in FIG. 2A for each supply target, and a distribution shape and parameters of the demand amount as shown in FIG. 2B. It is held in either form of probability distribution parameter type. In the example of FIG. 2, supply targets A and B are probability distribution direct specification types, and supply targets C, D, and E are probability distribution parameter specification types, and the probability distribution information of the demand forecast amount is displayed. The demand forecast information input unit 201 has a function of reading information described in different formats. In step S1004, the evaluation index calculation unit 206 calculates the evaluation index for supply amounts O1 to On and demand amounts d1 to dn.
After executing M simulations in steps S1002 to S1006, in step S1007, each frequency in the frequency table is divided by M to obtain a probability value for each index. Finally, in step S1008, the probability value for each index is set as the evaluation value of the corresponding supply plan.

FIG. 6 shows a flow of demand forecast information input processing in the demand forecast information input unit 201. The alphanumeric character “S” represents the initial letter of each step of the system operation flow. In steps S601 to S614, the following processing is repeatedly executed for the target product / service. First, in step S602, the supply target is checked whether the demand forecast amount of the supply target is a direct designation type or a parameter type. If it is a direct designation type, the demand amount and its probability value are read in step S603.
If it is a parameter type, the process proceeds to step S604 to check whether the shape is a normal distribution or lognormal distribution probability distribution. If applicable, the process proceeds to step S605, and the average value and variance data are read.
If not, the process proceeds to step S606 to check whether the shape is a uniform probability distribution. If applicable, the process proceeds to step S607, and the maximum value and minimum value data are read.
If not, the process proceeds to step S608, and it is checked whether the shape is a triangular distribution or Beta distribution probability distribution. If applicable, the process proceeds to step S609, and the maximum value / mode / minimum value data is read.
If not, the process proceeds to step S610 to check whether the shape is a binomial probability distribution. If applicable, the process proceeds to step S611, and the average value and variance data are read.
If not, the process proceeds to step S612 to check whether the shape of the Poisson distribution is a probability distribution. If applicable, the process proceeds to step S613, and average value data is read.
If none of these are applicable, processing such as notification of a definition error or the like is prompted to specify probability distribution parameters, or a default type defined in advance by the system is forcibly applied. The flow of this process is not shown.
Steps S602 to S613 are repeated for the target product and service. When the above process is completed for the target product / service, the reading of the demand prediction information is terminated.

  In the evaluation index calculation unit 206, the supply amounts or supply capacity sets O1 to On generated by the multipurpose multi-optimal solution calculation unit 203 and the demand amounts generated by the demand amount simulation unit 205 are the demand amounts d1 to dn. Calculate metrics such as profit and opportunity loss conversion factors. The evaluation index calculation unit 206 reads information such as sales unit price information, supply cost information, storage cost information, opening inventory information, opportunity loss cost conversion coefficient information from the accounting information storage unit 103. Based on this read information, the following profits are calculated.

For example, if the sales unit price of the product is ui, the supply cost is ci, the storage cost is wi, the initial inventory quantity is q0i, and the opportunity loss cost conversion coefficient is bi, the profit is calculated by the equation (Equation 1). Similarly, if the unit sales price of the service is ui, the supply cost is ci, and the opportunity loss cost conversion coefficient is bi, the profit is calculated by the equation (Equation 2). The calculation of profits can include factors other than those described above, such as setup costs, logistics costs, disposal costs, and depreciation costs when dealing with capital investment issues.
A user interface 209 is a user interface for selecting a supply amount or supply capability for selecting one combination from a plurality of supply amounts or combinations of supply capabilities. The multi-solution display unit 210 displays a combination (scenario) of a plurality of supply amounts or supply capacities calculated by the multi-objective multi-optimal solution calculation unit 203 from the supply amount or supply capacity information in the supply plan information storage unit 104. . Details will be described later on the display and selection screen (FIGS. 11 to 12, FIGS. 14 to 18, and FIGS. 20 to 26) of optimal solution information formed by a combination of supply plans.

  FIG. 7 shows a flowchart of operation in one embodiment of the present invention. The alphanumeric character “S” is the initial letter of each step of the flow. In step S701, information required for simulation and scenario creation, such as accounting information including cost information and selling price information, and resource information including resource capability information and consumption resource information, defined by the user is input to the system. In step S <b> 702, predicted demand fluctuation information including information such as demand prediction information and demand probability distribution and distribution thereof is input to the system. Here, the demand forecast information and its confidence interval information (predicted forecast demand fluctuation information) may be arbitrarily input by the user, or the forecast information may be automatically input to the system. In the following description, “automatic” means that processing is performed without human processing by a function of the system or the like.

In step S703, one or more combinations of supply quantities or supply capacities (scenarios) are calculated by the system based on the information on constraints and the information on demands input in steps S701 and S702. In step S704, each evaluation index selected by the user is displayed for the scenario calculated in step S703. In this embodiment, the probability frequency distribution with each evaluation index as the horizontal axis is displayed on a screen of a personal computer or the like by the display function provided by the system.
In step S705, selection of a desired scenario is input from the plurality of scenarios displayed by the user in step S704. The scenario selected by the function provided by the system is applied to the supply plan, processed, reflected in the supply plan display unit, and the result is displayed. In step S706, with respect to the scenario selected in step S705, the user confirms the display result of the supply amount and supply capacity in each period, and determines whether or not the scenario is appropriate. That is, for example, scenario 2 is selected in step S705 in FIG. When the user determines that the selected scenario is not appropriate, the user returns to step S705 again, selects a different scenario depending on the function provided by the system, and again determines the appropriateness. The user repeats the procedures of step S705 and step S706 until it determines that the selected scenario is appropriate. If it is determined that the selected scenario is appropriate and, for example, a selection button 1411 shown in FIG. 14 described later is selected, it is determined in the next step S707 whether the user needs to adjust the scenario selected in step S706. If it is determined in step S707 that no adjustment is necessary for the scenario selected by the user, the user instructs the system to store. According to the storage instruction, the data is stored in the system by the storage function of the system, and the scenario is applied as a final supply plan.
If it is determined in step S707 that the scenario selected by the user needs to be adjusted, the user adjusts the scenario in step S708. In step S709, for the scenario corrected in step S708, a demand amount simulation is performed on the system using a simulation function provided by the system, and the probability frequency distribution of each evaluation index is calculated. The system displays the simulation result for the adjusted scenario in step S710. After referring to the simulation result, the user determines again whether the scenario prepared in step S707 needs to be adjusted. The process ends when adjustment is no longer necessary. Through the operation flow described above, the user can make an appropriate supply plan in accordance with the management policy.

  FIG. 8 shows a transition of a screen accompanying processing, which is an embodiment of the present invention. A screen 801 operates as a menu screen. Details are described in FIG. A transition can be made from the menu screen to screens 803 to 808 corresponding to FIGS. A specific example of the demand simulation setting screen 803 is shown in FIG. 19, a specific example of a calculation setting screen 804 of a desired solution for the supply plan is shown in FIG. 13, and a specific example of the demand forecast / supply plan / accounting information screen 805 is shown in FIGS. This will be described below with reference to FIGS. Specific examples of the multiple optimal solution comparison and selection screen 806 for the supply plan are shown in FIGS. 14 to 18, FIGS. 20 to 21, and FIGS. 24 to 25. Specific examples of the demand simulation screen are shown in FIGS. A specific example of the adjustment screen 808 will be described below with reference to FIGS.

  FIG. 9 shows the menu screen. By operating (selecting) the menu 902 or the icon 903 indicating the menu, the supply plan can be made and analyzed. A plurality of screens shown in FIGS. 11 to 12, FIGS. 14 to 18, and FIGS. 20 to 26 can be displayed in the display area 904. By displaying a plurality of information simultaneously, it is convenient that a supply plan can be made while comparing and examining a plurality of constraint information and scenarios.

  FIG. 11 shows a screen for displaying and adjusting information on demand forecast, supply plan, and accounting in one embodiment of the present invention. In a specific example 1101 of the demand forecast / supply plan / accounting information screen, a period that is a unit in the display area 1103, here, the demand forecast value of the product in each period is a solid line graph, and the upper limit value in the confidence width of the demand forecast value The lower limit value is represented by a dotted line graph. The supply amount is represented by a light gray bar graph 1112, and the surplus supply value is represented by a dark gray bar graph 1114. Here, the surplus supply value is a supply value that exceeds the predicted demand. For example, it represents inventory or surplus production capacity in the manufacturing industry and surplus capacity in the service industry. Moreover, when displaying stock etc., you may display the accumulation stock of each period. The supply amount and surplus supply value can also be edited by directly dragging and dropping a graph on a screen of a personal computer or the like with a mouse or the like. A product displayed in the display area 1103 can be selected from a list of product names displayed by clicking a pull-down menu 1102. In the display area 1104, in addition to the information on the demand forecast value on the graph and the information on the supply amount, the accounting information is automatically displayed based on the information held by the system. Further, by selecting each cell in the table, the information in the selection section can be edited.

  FIG. 12 shows a display and adjustment screen for information relating to demand forecasting / supply planning / accounting in one embodiment of the present invention. In FIG. 11, the supply amount and the surplus supply value are displayed in a stacked manner, whereas in FIG. 12, the supply amount and the surplus supply value are displayed in parallel. Other parts and functions are the same as those in FIG. By switching to the display method of FIG. 12, the surplus supply value can be edited with reference to the origin 0 of the graph in the display area 1202. This is convenient for planning a plan centered on inventory in the manufacturing industry. 11 and 12 can be switched from the “Display” menu in FIG.

FIG. 13 shows a screen for setting a desired solution calculation method and parameters in an embodiment of the present invention. A display area 1303 displays options for an index to be optimized. An evaluation index to be optimized is displayed in a display area 1304. The selected index can be displayed in the display area 1304 by clicking a button 1305 in a state where the index to be optimized is selected on 1303. The index displayed in the display area 1304 can be an index for calculation of a desired solution. In addition, by clicking the button 1306, all the options in the display area 1303 are moved to the display area 1304. Further, by selecting an index that is not optimized on the display area 1304 and clicking the button 1307 to leave an evaluation index for optimization in the display area 1304, the index to be optimized can be selected. By clicking a button 1308, an optimization index displayed in the display area 1304 can be cleared (all optimization index options are returned to the display area 1303).
The optimization method can be selected from a plurality of tags having optimization logic names described on the tab 1309. In the example of the tab 1309, a genetic algorithm, an annealing method, and a Lagrangian relaxation method can be selected. The simplex method is often applied to the optimal supply plan (product mix problem) of multiple products in the manufacturing industry. Other methods that are considered more general may be implemented. When the optimization logic is selected from the tab 1309, further detailed parameters can be set in the display area 1310. In the example of FIG. 13, the genetic algorithm is selected as the optimization method.
In the example of FIG. 13, the index specified from the index in the display area 1303 moves to the display area 1304 and disappears from the display area 1303, but it may not disappear from the display area 1303. That is, the index is selected by specifying the index in the display area 1303 and selecting the display 1305 for operation. The selected index may be displayed in the display area 1304. Even if an index is once selected and displayed in the display area 1304, it can be removed from the selected index by selecting the display 1307 for operation. Even if it is displayed in the display area 1304 as being selected in this case, the index specified from the display area 1304 can be erased in the display 1307 for operation. A display 1306 for operation has a function of selecting all the indicators in the display area 1303. In addition, the display 1308 for operation has a function of deselecting all the indexes selected and displayed in the display area 1304. In that case, all the selected indexes in the display area 1304 are deleted.

FIG. 14 shows a screen for displaying a plurality of candidates for determining a desired solution, which is formed by a combination of supply plans in one embodiment of the present invention, and selecting a desired solution therefrom. This screen is a screen for displaying a plurality of desirable solutions and comparing them to select a desired solution candidate. This screen is displayed by selecting two optimization indexes in FIG. 13 or selecting 2 from the index number pull-down menu 1402. When the index number is selected from the index number pull-down menu 1402, the index selected in FIG. 13 (the index displayed in the display area 1304) is first displayed. When it is exhausted, unselected indices are displayed in the display area such as 1406 and 1407 in order from the index list 1303. When the display area is 3 or more, a display area after 1406 and 1407 is automatically generated. In this way, in the example of FIG. 14, the two optimization indices selected in FIG. 13 are first displayed in the pull-down menus 1406 and 1407, but other indices are reset from the pull-down menus 1406 and 1407. You can also. Based on the two optimization indexes selected in this way, optimization can be executed from the menu screen of FIG. 9 to perform optimization calculation. As a result, each scenario corresponding to the data of each product or service can be planned.
Although described above, the term (optimum) (optimization) is used in this specification in the sense of (desirable) and not in the narrowest sense of being most desirable.
Each scenario is displayed as a point or graphic (in this example, a circular graphic) on the display area 1405, as a graph of probability frequency distribution on the display area 1408, and as an evaluation value of a plurality of indices on the display area 1410. The Each scenario of the plurality of display areas corresponds to each other. For example, the scenario number 2 corresponds to 1422 in the display area 1405, 1421 in the display area 1408, and 1423 in the display area 1410. In order to identify a plurality of scenarios, the scenarios in the display areas 1405, 1408, and 1410 may be displayed in different colors.
What is shown in the display area 1405 relates to a means for displaying each scenario on a graph having two evaluation indexes as a vertical axis and a horizontal axis. For example, when each scenario on the display area 1405 represents profit on the horizontal axis and variance on the vertical axis, the scenario plotted on the upper right represents a scenario with higher profit but higher uncertainty, and is plotted on the lower left. This represents a scenario with lower profit but lower uncertainty (not shown). When the maximization of the expected value of profit and the minimization of the standard deviation of profit are selected as priority evaluation indexes, the graph is generally called an efficient frontier. In this case, the multiple solutions draw a curve representing the trade-off relationship between risk and return.

By clicking each scenario in the display area 1405, a straight line perpendicular to the vertical axis and the horizontal axis is displayed, and each scenario on the corresponding display area 1408 and the table 1410 is also selected by displaying the scenario ID or reversely displaying it. It can be. In this example, the scenario 1422 is clicked and a dotted line is displayed in a cross shape. The scenario ID is 2, and the corresponding scenario is the scenario ID 2 displayed on the corresponding data on the graph, and the corresponding record is highlighted in the table. Similarly, each scenario can be selected from the display area 1408 and the table 1410, and even if the scenario is clicked on the display area 1408 or the table 1410, all corresponding scenarios are automatically selected. Can do. When one of the scenarios in the display area 1405, the display area 1408, or the table 1410 is selected in this way, the part representing the scenario in the display area 1405, the display area 1408, and the table 1410 is implemented in this embodiment. It is automatically highlighted as selected by the function of the system provided by the example.
The display area 1408 of FIG. 14 is a graph of probability frequency distribution in which the horizontal axis is an index displayed in the pull-down menu 1409 and the vertical axis is frequency. By selecting “cumulative frequency distribution” or “frequency distribution + cumulative frequency distribution” from the pull-down menu 1403 on this graph, the cumulative frequency distribution can be displayed, or the frequency distribution and the cumulative frequency distribution can be displayed simultaneously. it can. In this example, the scenario temporarily set state is represented by the scenario ID number at the top of the graph on 1408, but other methods such as a bold solid line may be used. That is, in FIG. 14, the display type can be selected from the pull-down menu 1403. When the selected type is displayed in the form of a graph, pull-down menus 1409, 1407, and 1406 are displayed on the axis of the graph. When an index is selected from the displayed pull-down menu, a graph with the selected index as an axis is displayed. Is displayed.
Table 1410 displays a table listing evaluation values of a plurality of indices for each scenario. The columns include a column that can specify a horizontal record, and a plurality of scenarios on the display area 1405 and the display area 1408 can be displayed or deleted by checking or unchecking. That is, by specifying the target of the display area 1401, a graph of the specified scenario is displayed in the display areas 1405 and 1408. When many scenarios are calculated by such a function, it is easy to identify each scenario on the display area 1405 and the display area 1408, which is convenient. The same operation can be performed by right-clicking each scenario on the display area 1405 or each scenario in each graph on the display area 1408.
Selection processing is executed by selecting the selection button 1411. This selection processing is processing performed by the supply plan selection unit 211 shown in FIG. 1, and is a means for selecting a combination of supply amount or supply capability. When this button 1411 is clicked, a combination of supply amount or supply capability in the temporarily selected state (for example, scenario with scenario ID 2 in FIG. 14) is reflected in the supply plan graph and table (display area 1103, table 1104, etc.), respectively. Is done.

  Further, as shown in FIG. 14, the X-axis item can be freely changed by a pull-down menu 1407 and the Y-axis item can be freely changed by a pull-down menu 1406, and the data displayed in the graph is also changed in the X-axis and Y-axis. It has a function that is automatically and instantly changed according to the item. As described above, in one function of this embodiment, by directly changing the axis item of the multidimensional graph using a pull-down menu or the like, the displayed graph and data are automatically changed in response to the change of the item. A processing method to be changed is provided.

  FIG. 15 shows an example of display of optimum solution information formed by a combination of supply plans in one embodiment of the present invention and an example of an operation screen for selecting the optimum solution. The screen configuration and basic operations are the same as the operations, functions, and effects described with reference to FIG. 14, and the case where the index for evaluation is further increased will be described with reference to FIG. When three optimization indices are selected in FIG. 13, a three-dimensional graph in the display area 1502 is displayed by selecting the index number 3 from the pull-down menu 1402. When a scenario is to be created for the three indicators displayed in the pull-down menus in the display areas 1406, 1407, and 1503, optimization is executed from the menu screen of FIG. 9 in this display state. When the optimization is executed, the scenarios for the three indices specified in the display areas 1406, 1407, and 1503 in FIG. 15 are displayed in the display area 1502 as points and figures (circular figures in this example).

  FIG. 16 shows a display example of optimum solution information formed by a combination of supply plans and an optimum solution selection screen in one embodiment of the present invention. The screen configuration and basic operations, functions, and effects are the same as those described with reference to FIGS. By selecting four or more optimization indexes in FIG. 13 or selecting four or more indexes from the pull-down menu 1402, a polygonal radar chart as shown in the display area 1602 shown in FIG. 16 is displayed. In FIG. 16, 6 is specified as the number of indices. Based on the designation, a hexagonal radar chart is displayed in the display area 1602. When optimization is performed on the specified plural (six types) of indicators from the menu screen of FIG. 9, each scenario is displayed in the display area 1602 as a point or a figure (in this example, a dotted polygon).

  FIG. 17 shows an example of an optimal solution information display and optimal solution selection screen formed by a combination of supply plans in one embodiment of the present invention, and a display and adjustment screen of demand forecast / supply plan / accounting information. . The screen configuration is common to the components 1102, 1103, 1104, 1403, 1404, 1408, 1409, and 1410 in FIGS. To realize quantitative scenario analysis and practical decision making, demand forecast (displayed on 1103, 1104), supply plan (displayed on 1103, 1104), accounting information (displayed on 1104), information on each planning scenario ( 1408) is displayed at the same time. For this reason, it is easy to judge whether the supply plan is unreasonable for application to the actual site from the user's point of view, and it is easy to find chronic supply shortages. is there. The component 1102 in FIG. 11 may switch display with the component 1202 in FIG.

  FIG. 18 shows an example of an optimal solution information display and optimal solution selection screen formed by a combination of supply plans in one embodiment of the present invention, and a display and adjustment screen of demand forecast / supply plan / accounting information. . The screen configuration is common to the components 1102, 1103, 1104, 1402, 1405, 1406, 1407, and 1410 in FIGS. In order to actually realize quantitative scenario analysis and decision making, demand forecast (displayed on 1103, 1104), supply plan (displayed on 1103, 1104), accounting information (displayed on 1104), information on each planning scenario ( (Displayed in 1405 and 1410) at the same time is useful for determining the feasibility of each scenario and for finding problems as in FIG. The component 1103 may be displayed in the display method of the component 1202 having the format shown in FIG. The components 1405, 1406, and 1407 can be switched with the component 1502 in the format shown in FIG. 15 or the component 1602 in the format shown in FIG.

  FIG. 19 shows an example of a demand simulation setting screen in one embodiment of the present invention. A sampling method selection area 1902 is provided with a function of selecting a demand data sampling method in the simulation. In this example, Monte Carlo simulation and Latin hypercube simulation can be selected. Other simulation methods may also be implemented. In the input area 1903, the number of simulations is set. In general, when the number of simulations is not sufficiently high, the selection of the Latin hypercube simulation method is effective to avoid sampling bias.

  FIG. 26 shows an example of a display screen of the multiple optimal solutions and demand simulation results described above with reference to 1408 in FIG. 14 in one embodiment of the present invention. The screen configuration is common to the components 1403, 1404, and 1409 in FIG. The display area 2602 is the same as the display area 1408 in FIG. 14, but in addition to the probability distribution for each index of the plurality of calculated supply plans indicated by the dotted line, the probability frequency distribution diagram of the evaluation result obtained as a result of the demand simulation Is an example indicated by a solid line. In addition to the common characteristics that represent the evaluation values of the supply plans 1 to N calculated with the table 1410 of FIG. 14 in the table 2603, the evaluation value of the supply plan obtained as a result of the demand simulation is selected (by shading or the like). This is an example indicated by a highlighted record. The display area 2602 and the table 2603 are effective for visually and quantitatively comparing a plurality of supply plan plans obtained by the optimization calculation with other supply plan plans based on demand simulation or the like.

FIG. 20 shows an example of display and adjustment screen for each information of demand simulation and demand forecast / supply plan / accounting in one embodiment of the present invention. The screen configuration is the same as the screen configuration of FIG. 17 except for the display area 2602, table 2603, and table 2004 of FIG.
A case where a supply plan simulation is performed on the screen of FIG. 20 will be described. Here, the supply plan simulation includes an editing process and a demand simulation process.
In the editing process, the product name pull-down menu 1102, display area 1103, and table 2004 are used to edit the supply information, demand amount, inventory amount, sales amount, manufacturing unit price, and other constraint information and supply plan.
In the demand simulation process, it is possible to quantitatively analyze the supply plan edited in the editing process by performing a demand simulation based on the demand prediction and the confidence interval of the predicted demand. The supply plan simulation may be performed regardless of the order either before or after the process for obtaining an optimal solution based on the setting shown in FIG. 13 (simulations shown in FIGS. 14 to 18).
The result of the demand simulation is output to the display area 2602 in a format that can be distinguished from other scenarios in order to quantitatively and visually compare each index with other scenarios. A display area 2602 indicates the probability frequency distribution of the index 1409 with a dotted line for each supply plan obtained by the optimization calculation. On the other hand, the result of the demand simulation is an example indicated by a thick solid line.
By selecting one of the other scenarios on the display area 2602 or the table 2603 and clicking the selection button 1411, the setting based on the selected information can be reflected in the supply plan again. As examples of means for discriminating a scenario before editing, a table 2603 provides an identification means by gray color display, and a display area 2602 provides means for writing a scenario ID along a broken line.

FIG. 21 shows an example of display and adjustment screen for each information of demand simulation and demand forecast / supply plan / accounting in one embodiment of the present invention. The basic configuration, operation, action, and effect of the screen configuration are the same as those described in FIG. In the screen configuration of FIG. 18, the display area 2102, the table 2603, and the table 2004 are slightly changed.
A case where a supply plan simulation is performed on the screen of FIG. 21 will be described. Here, the supply plan simulation includes an editing process and a demand simulation process. In the editing process, on the product name pull-down menu 1102, display area 1103, and table 2004, restriction information such as supply quantity, demand quantity, inventory quantity, sales quantity, and manufacturing unit price, and supply plan editing are performed. In the demand simulation process, the supply plan edited in the editing process is quantitatively analyzed by performing a demand simulation based on the demand prediction and the confidence interval of the predicted demand. The supply plan simulation may be performed either before or after the process for obtaining the optimum solution based on the setting shown in FIG. 13 (simulations shown in FIGS. 14 to 18).
The result of the demand simulation is output to the display area 2102 in a format that can be distinguished from other scenarios in order to quantitatively and visually compare each index with other scenarios. In the display area 2102, the simulation results of other scenarios are represented by white circles, and the simulation results of the scenario based on the demand simulation edited in the vicinity are represented by black circles. It is also possible to select one of the other scenarios on the display area 2102 or the table 2603 and click the selection button 1411 to reflect the selection result again in the supply plan. As an example of a means for distinguishing the scenario before the editing, a means for identifying by gray color display on the display area 2102 and the table 2603 and a means for writing a scenario ID together on the display area 2102 can be cited.

FIG. 22 shows an example of a display and adjustment screen for demand forecast / supply plan / accounting information, and a reference and adjustment screen for individual resource constraint information and load information in one embodiment of the present invention. The basic concept of the screen configuration and the concept of operation, action, and effect are the same as those of the components 1102, 1103, and 1104 in FIG. A display area 2203 and a table 2204 display data in the resource specified from the resource pull-down menu 2202. The graph in the display area 2203 is a graph in which the workload or machine occupation time allocated to each work or service of each resource in each period is expressed in a pile-up manner. In a display area 2203, the load amount for providing the supply target is displayed as a solid line graph, and the maximum load capacity of each period is displayed as a dotted line graph. A table 2204 displays the load amount for providing the supply target and the maximum load capacity in each period in a table format.
For example, you can edit the load plan by moving a bar indicating the load on the graph in the display area 2203 (for example, the bar of the graph written as PR1 in FIG. 22) to another period by dragging and dropping. It is. When the load amount is edited, the corresponding supply plan is automatically corrected and reflected in the display area 1103 and the table 1104 by the system. Similarly, when the supply plan is edited on the display area 1103 and the table 1104, the corresponding load amount is reflected on the display area 2203 and the table 2204. This mechanism is effective for creating an executable load balance plan.

  FIG. 23 shows an example of a display and adjustment screen for demand forecast / supply plan / accounting information and a reference screen for resource constraint information and load information in one embodiment of the present invention. The basic concept, operation, action, and effect of the screen configuration are the same as the components 1102, 1103, and 1104 in FIG. A display area 2302 and a table 2303 display a load amount for providing a supply target in a resource necessary for supply in a graph and a table, respectively. When the supply plan is edited on the display area 1103 and the table 1104, the corresponding load amount is automatically reflected on the display area 2302 and the table 2303. This mechanism is effective for creating an executable load balance plan.

FIG. 24 shows an example of a display and selection screen relating to optimal solution information formed by a combination of supply plans in one embodiment of the present invention, a reference screen relating to constraint information and load information of individual resources, and an adjustment screen. The basic concept, operation, action, and effect of the screen configuration are the same as the components 1403, 1404, 1408, 1409, 1410 in FIG. 14 and the components 2202, 2203, 2204 in FIG. An arbitrary scenario is selected from a plurality of scenarios planned by the optimization of the supply plan in the display area 1408 and the table 1410, and the selection button 1411 is clicked, whereby the resource selected in the resource pull-down menu 2202 is displayed in the display area. This can be reflected in the load graph 2203 and the table 2204.
When the load plan on the display area 2203 is edited, a demand simulation is performed on the edited scenario, and the probability frequency distribution of the index can be compared with other scenarios. This mechanism is effective for creating an executable load balance plan.

  FIG. 25 shows an example of a display and selection screen for optimal solution information formed by a combination of supply plans in one embodiment of the present invention, and a reference screen for resource constraint information and load information. The basic concept, operation, action, and effect of the screen configuration are the same as the components 1403, 1404, 1408, 1409, and 1410 in FIG. 14 and the components 2202, 2203, and 2204 in FIG. An arbitrary scenario can be reflected in the load graph 2302 and the table 2303 by selecting an arbitrary scenario from a plurality of scenarios prepared by the optimization of the supply plan in the display area 1408 and the table 1410 and clicking the selection button 1411. This mechanism is effective for creating an executable load balance plan.

As described above in detail, generally, when there are a plurality of priority evaluation indexes, there is often a trade-off relationship between the respective evaluation indexes, in which one is insufficient when one is prioritized. In the above-described embodiment, it is possible to easily determine the optimal combination of supply amount or supply capability of the supply target according to the situation while quantitatively determining the priority evaluation index.
Further, in the above embodiment, based on the demand forecast obtained based on the actual demand value and its statistical data and the confidence interval of the demand forecast, the priority evaluation indexes can be made as close to the optimum value as possible. , Calculate multiple solutions, output probability distribution of each evaluation index corresponding to each solution, and user select appropriate solution according to organizational policy based on quantitative evaluation value of each solution An environment capable of being provided can be provided.

As described above, according to the method of the above embodiment, it is possible to more easily, more accurately, and more efficiently carry out the task of formulating a supply plan. One of the means is to use demand forecast information including statistical data of past actual values, accounting information including cost information, and resource information including supply capacity information as constraint information, and further optimize a plurality of designated evaluation indexes. It is to obtain a plurality of sets (scenarios) of a combination of supply amount or supply capability of one or more products or one or more services.
One of the further measures is to quantitatively and visually compare the probability distribution of the evaluation index data of each scenario in the obtained solution, select an arbitrary scenario from the calculated multiple scenarios, and then evaluate each evaluation index of the multiple solutions. It is possible to make adjustments while visually confirming the supply plan and supply load information graphically on the screen.
In the calculation of a plurality of optimum solutions, a plurality of evaluation indexes can be selected as optimization indexes. This maximizes profits, minimizes risks, maximizes share (maximizes sales), avoids maximum stockouts (minimizes lost opportunities), minimizes scrap quantities (minimizes inventory) Can be selected independently or simultaneously according to strategies and tactics to solve the challenges faced by the organization.
As described above, according to the present invention, it is possible to facilitate the user's supply plan formulation and improve the accuracy and efficiency of the supply plan.

The supply plan determination means provided by the method of the above embodiment can be applied to the formulation of supply plans in a plurality of business fields. For example, in the food manufacturing industry, the expiry date information (inventory availability information) is input as constraint information in advance, thereby supporting the optimal supply plan formulation for each period based on the demand forecast information of the sales information for each food. can do. Also, in the call center industry, it is possible to support the optimal personnel allocation plan formulation for each time zone based on the demand prediction information of the traffic information by inputting the skill information of the allocated personnel as constraint information in advance. Also, in the home appliance retail industry, it is possible to support the formulation of the optimal purchase plan for each period based on the demand forecast information of the sales information of each product by inputting the available inventory area in the store as constraint information in advance. it can. Further, in the semiconductor industry, it is possible to support the formulation of an optimal supply plan (capital investment plan) based on semiconductor demand forecast information by inputting investment funds that can be procured in advance as constraint information. Similarly, in the medical and welfare industry and the real estate industry, the optimal floor space increase is based on predictive information on the number of inpatients in hospitals and demand forecasts for office space by inputting investment funds that can be procured in advance as constraint information. Can support planning and office supply planning.
As described above, the user can confirm a plurality of optimization plans calculated based on the evaluation index to be selected, and can arbitrarily make adjustments. According to the method of the present embodiment, each index of multiple solutions, supply plan, and supply load information are visually displayed on a screen as a chart, enabling setting / change and fine adjustment, thereby enabling the user's supply plan. It can help improve the accuracy and efficiency of formulation. In addition to maximizing profits and minimizing risk, the evaluation metrics to be selected include maximization of share (maximization of sales), maximum avoidance of missing parts (minimization of opportunity loss), and minimum disposal quantity (Minimization of inventory), etc. can be selected independently or simultaneously. For this reason, multi-faceted evaluation is possible, and a more accurate supply plan can be formulated.

1 is an overall configuration diagram of an embodiment of a computer system to which the present invention is applied. It is a figure which shows the demand prediction information in one Example of this invention. It is a figure which shows the accounting information and resource information of one Example in the manufacturing industry of this invention. It is a figure which shows the accounting information and resource information of one Example in the service industry of this invention. It is a figure which shows the probability distribution of the profit in one Example of this invention. It is a figure which shows the demand forecast information input process in one Example of this invention. It is a figure which shows the example of operation in one Example of this invention. It is a screen transition of the process in one Example of this invention. It is a figure which shows the menu screen in one Example of this invention. It is a figure which shows the probability distribution calculation process of the evaluation parameter | index in one Example of this invention. It is an example of the display and adjustment screen of each information of demand forecast, supply plan, and accounting in one example of the present invention. It is an example of the display and adjustment screen of each information of demand forecast, supply plan, and accounting in one example of the present invention. It is an example of the calculation method of the optimal solution in one Example of this invention, and the parameter setting screen. It is an example of the display and selection screen of the optimal solution information formed by the combination of the supply plan in one Example of this invention. It is an example of the display and selection screen of the optimal solution information formed by the combination of the supply plan in one Example of this invention. It is an example of the display and selection screen of the optimal solution information formed by the combination of the supply plan in one Example of this invention. It is an example of the display and adjustment screen of each information of the optimal solution information formed and displayed by the combination of the supply plan in one Example of this invention, demand forecast, supply plan, and accounting. It is an example of the display and adjustment screen of each information of the optimal solution information formed and displayed by the combination of the supply plan in one Example of this invention, demand forecast, supply plan, and accounting. It is an example of explanatory drawing of the setting screen of the demand simulation in one Example of this invention. It is an example of the display and adjustment screen of each information of the demand simulation in one Example of this invention, demand forecast, supply plan, and accounting. It is an example of the display and adjustment screen of each information of the demand simulation in one Example of this invention, demand forecast, supply plan, and accounting. It is an example of the display and adjustment of each information of demand forecast, supply plan, and accounting in one embodiment of the present invention, and reference and adjustment screens of constraint information and load information of individual resources. It is an example of the reference screen of the demand forecast, supply plan, accounting information display and adjustment, resource constraint information and load information in one embodiment of the present invention. It is an example of the display and selection screen of the optimal solution information formed by the combination of the supply plan in one Example of this invention, and the reference and adjustment screen of the constraint information and load information of each resource. It is an example of the display and selection screen of the optimal solution information formed by the combination of the supply plan in one Example of this invention, the reference screen of resource constraint information, and load information. It is an example of the display screen of the result of the demand simulation in one Example of this invention.

Explanation of symbols

DESCRIPTION OF SYMBOLS 101 ... Demand forecast information memory | storage part, 102 ... Resource information memory | storage part, Accounting information memory | storage part ... 103, Supply plan information memory | storage part ... 104, 201 ... Demand forecast information input part, 203 ... Multi-purpose multiple optimal Solution calculation unit, 209 ... user interface, 801 ... menu screen, 901 ... menu screen of the embodiment, 1101 ... demand forecast / supply plan / accounting information screen of the embodiment, 1301 ... calculation setting screen of optimal solution of the embodiment, 1401 ... Comparison selection screen of multiple optimal solutions of the embodiment, 1901 ... Demand simulation setting screen of the embodiment, 2001 ... Supply simulation simulation screen of the embodiment, 2201 ... Individual resource load adjustment screen of the embodiment, 2301 ... Resources of the embodiment Load adjustment screen

Claims (14)

A storage device for storing information, an input / output device including a display device, and a processing device;
Demand forecast information input from the input / output device is stored in the storage device, further an evaluation index is designated, and the supply plan and the evaluation value of the evaluation index are based on the demand forecast information and the designated evaluation index. A support system for creating a supply plan calculated by a processing device and configured to display a plurality of supply plans and evaluation values of evaluation indexes obtained by the calculation on the display device. A support system for creating the supply plan according to claim 1,
Support system for creating a supply plan characterized by displaying a demand forecast value and its upper limit value and lower limit value, supply amount or supply capacity value, and opportunity loss value in association with each other on the display screen of the display device . A support system for creating the supply plan according to claim 1,
A support system for creating a supply plan, wherein the established frequency distribution related to the specified evaluation index and the supply amount or supply capacity of each supply target are displayed in association with each other on a display screen. A support system for creating the supply plan according to claim 3,
A plurality of evaluation values calculated for the specified evaluation index are displayed, and the probability distribution is displayed in a graph with a plurality of values associated with the plurality of evaluation values, and is specified from the plurality of evaluation values displayed above. When an evaluation value is selected, a support system for creating a supply plan, wherein a graph of values corresponding to the selected evaluation value is specified and displayed. A support system for creating the supply plan according to claim 3 or claim 4,
If there is an evaluation index related to profit as the evaluation index, and the evaluation index related to profit is specified, the probability distribution is displayed as a graph of a plurality of values with the evaluation index related to profit as an axis, and the plurality of displayed When a specific evaluation value is selected from the evaluation values, a support system for creating a supply plan, wherein a graph of a value corresponding to the selected evaluation value is specified and displayed. A support system for creating the supply plan according to claim 1,
When a plurality of evaluation indexes are specified, a plurality of evaluation values are calculated corresponding to the specified evaluation index, and a graph of a scenario with the plurality of evaluation values and the specified plurality of evaluation indexes as axes, Is a support system for creating a supply plan, characterized in that the information is displayed in correspondence with the display screen of the display device. A storage device for storing information, an input / output device including a display device, and a processing device;
The demand forecast information of the product and the probability distribution information of the demand forecast amount are stored in the storage device, the evaluation index is further designated, the demand forecast information, the probability distribution information of the demand forecast amount, and the designated evaluation index. Based on the above, the product supply amount and the evaluation value related to the evaluation index are calculated by the processing device, and the plurality of supply amounts obtained by the calculation and the evaluation value of the evaluation index are output. Support system for creating supply plans. A storage device for storing information, an input / output device including a display device, and a processing device;
The demand forecast information for the service and the probability distribution information of the demand forecast amount are stored in the storage device, the evaluation index is further designated, the demand forecast information, the probability distribution information of the demand forecast amount, and the designated evaluation index. The service supply amount and the evaluation value related to the evaluation index are calculated by the processing device based on the above, and the plurality of supply amounts obtained by the calculation and the evaluation value of the evaluation index are output. Support system for creating supply plans. A storage device for storing information, an input / output device including a display device, and a processing device;
Demand forecast information for the product and probability distribution information of the demand forecast amount are stored in the storage device, and further, an evaluation index is designated, the demand forecast information, the probability distribution information of the demand forecast amount, and the designated evaluation index Based on the above, it is configured to calculate the capital investment scale and the evaluation value related to the evaluation index by the processing device, and to output the evaluation values of the plurality of capital investment scales and the evaluation index obtained by the calculation. Support system for creating supply plans. A storage device for storing information, an input / output device including a display device, and a processing device;
The demand forecast information for the service and the probability distribution information of the demand forecast amount are stored in the storage device, the evaluation index is further designated, the demand forecast information, the probability distribution information of the demand forecast amount, and the designated evaluation index. Based on the above, a probability distribution relating to an investment plan or supply capacity plan for a service and an evaluation index is calculated by the processing device, and a probability distribution relating to an investment plan or supply capacity plan and an evaluation index for a plurality of services obtained by the calculation A support system for creating a supply plan, characterized in that the system is configured to output the output. A storage device for storing information, an input / output device including a display device, and a processing device;
Demand forecast information input from the input / output device is stored in the storage device, further an evaluation index is designated, and the supply plan and the evaluation value of the evaluation index are based on the demand forecast information and the designated evaluation index. A support method for creating a supply plan calculated by a processing device and displaying a plurality of supply plans and evaluation values of evaluation indexes obtained by the calculation on the display device. A storage device for storing information, an input / output device including a display device, and a processing device;
The demand forecast information of the product and the probability distribution information of the demand forecast amount are stored in the storage device, the evaluation index is further designated, the demand forecast information, the probability distribution information of the demand forecast amount, and the designated evaluation index. A supply plan characterized in that the supply amount of the product and an evaluation value related to the evaluation index are calculated by the processing device, and the evaluation values of the plurality of supply amounts and the evaluation index obtained by the calculation are output. Support method for creating. A computer program characterized in that a system having a storage device for storing information, an input / output device including a display device, and a processing device has the following functions:
The input demand forecast information is stored in the storage device, the specified evaluation index is further stored, and the supply plan and the evaluation value of the evaluation index based on the demand prediction information and the specified evaluation index are stored in the processing device. And the evaluation values of the plurality of supply plans and evaluation indexes obtained by the calculation are displayed on the display device. A computer program characterized in that a system having a storage device for storing information, an input / output device including a display device, and a processing device has the following functions:
The demand forecast information of the product and the probability distribution information of the demand forecast amount are stored in the storage device, the designated evaluation index is further memorized, and the demand forecast information and the probability distribution information of the demand forecast amount are designated as described above. Based on the evaluation index, the supply amount of the product and the evaluation value related to the evaluation index are calculated by the processing device, and the plurality of supply amounts and evaluation values of the evaluation index obtained by the calculation are output.

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