Information processing device, information processing method, and program

Abstract

An information processing device 100 according to the present disclosure comprises: a storage unit 121 that stores a relational expression in which the quantity for each type of event and the discharge quantity of a prescribed substance set according to each type of event are used; and a calculation unit 122 that calculates the quantity for each type of event on the basis of the relational expression.

Description

Information processing device, information processing method, and program

[0001] The present disclosure relates to an information processing device, an information processing method, and a program.

[0002] In recent years, there has been a demand to reduce emissions of substances that cause environmental loads, such as greenhouse gases such as carbon dioxide and air pollutants such as nitrogen oxides. In this regard, Patent Document 1 describes a method for calculating the amount of emissions of environmental loads caused by equipment and other possessions owned by a business operator.

[0003] Patent No. 7043691

[0004] Here, businesses may introduce new equipment and other objects or replace them depending on the business situation, which can cause changes in the objects they own. However, with the technology described in Patent Document 1, it is difficult to recognize the amount of environmental load caused by changes in the objects they own. As a result, there is a problem in that it is difficult to plan the introduction of objects while taking the environment into consideration. Furthermore, it is difficult to plan for events that can occur at a business, not just the introduction of objects by a business.

[0005] Therefore, an object of the present disclosure is to solve the above-mentioned problem of the difficulty of planning events while taking the environment into consideration.

[0006] An information processing device according to an embodiment of the present disclosure includes: a storage unit that stores a relational expression using the quantity of each type of event and an emission amount of a predetermined substance set for each type of event; and a calculation unit that calculates the quantity of each type of event based on the relational expression.An information processing method according to an embodiment of the present disclosure includes: calculating the quantity of each type of event based on the relational expression using the quantity of each type of event and an emission amount of a predetermined substance set for each type of event.A program according to an embodiment of the present disclosure includes: calculating the quantity of each type of event based on the relational expression using the quantity of each type of event and an emission amount of a predetermined substance set for each type of event.

[0007] With the above-described configuration, the present disclosure can assist in planning events while taking the environment into consideration.

[0008] Fig. 1 is a block diagram showing a configuration of a first information processing device according to the present disclosure; Fig. 2 is a diagram showing a state of processing by the first information processing device according to the present disclosure; Fig. 3 is a flowchart showing a processing operation of the first information processing device according to the present disclosure; Fig. 4 is a block diagram showing a hardware configuration of a second information processing device according to the present disclosure; Fig. 5 is a block diagram showing a configuration of the second information processing device according to the present disclosure.

[0009] First Embodiment A first embodiment of the present disclosure will be described with reference to the drawings. Note that the drawings may be relevant to any embodiment.

[0010] [Configuration] In this embodiment, the information processing device 10 is used to support a business operator in planning potential events, such as introducing an object or implementing a policy, in order to contribute to reducing the business operator's environmental impact. In this embodiment, the business operator is, for example, a business operator that uses vehicles to provide delivery services or home visit services. In this case, the business operator will own multiple vehicles in the course of its business, and may need to replace multiple vehicles depending on the business situation and the passage of time. Therefore, the business operator will develop a vehicle introduction plan while taking the environment into consideration. In this embodiment, a case will be described in which the information processing device 10 supports the development of a vehicle (object) introduction plan. Note that in this embodiment, the ownership of vehicles of each type based on a predetermined classification is treated as an event, and the number of vehicles of each type is considered to be the quantity of the event. However, the quantity of the event is not limited to representing the number of objects, such as vehicles, owned by each type, and may also represent the number or quantity of actions, policies, etc., that the business operator can take.

[0011] The information processing device 10 is composed of one or more information processing devices each including a calculation device and a storage device. As shown in FIG. 1 , the information processing device 10 includes an acquisition unit 11, a calculation unit 12, and an output unit 13. The functions of the acquisition unit 11, the calculation unit 12, and the output unit 13 can be realized by the calculation device executing a program for realizing each function stored in the storage device. The information processing device 10 also includes a relational equation storage unit 16. The relational equation storage unit 16 is composed of a storage device. Each component will be described in detail below.

[0012] The relational equation storage unit 16 stores relational equations relating to the number of vehicles of each type, which are used when supporting business operators in formulating vehicle introduction plans. In this embodiment, two relational equations, namely, a first relational equation and a second relational equation, are stored. The first relational equation represents the relationship between the number of vehicles of each type (object) and the amount of carbon dioxide (predetermined substance) emitted from the vehicles. The second relational equation represents the relationship between the number of vehicles of each type (object) and the cost of energy used by the vehicles (evaluation value).

[0013] Specifically, the first relational expression is expressed by a linear expression shown in the following equation 1. Here, the objective variable y ｔ is the carbon dioxide (CO ２ ) emissions. Explanatory variable x ｉｔ indicates the number of vehicles of each type i in each period t. ｉt is the carbon dioxide emissions per vehicle of each type i in each period t. However, the coefficient a ｉt is independent of the period t, i.e., the coefficient a ｉ It should be noted that y itself does not need to have the subscript t. In this case, the explanatory variable x ｉｔ and coefficient a ｉt The subscript t disappears from both, and y becomes the total carbon dioxide emissions.

[0014] Here, multiple vehicle types i are set in advance. In this embodiment, the vehicle type i is classified according to the energy usage status of the engine or motor, which is the vehicle's power source (power unit). Furthermore, the energy usage status is also classified according to the energy type and the size of the vehicle (power source). As an example, energy types include gasoline, biofuel, and electricity, and vehicle types based on these include gasoline / diesel vehicles (hereinafter referred to as gasoline vehicles), biofuel vehicles (hereinafter referred to as BIO vehicles), and electric vehicles (hereinafter referred to as EV vehicles). Furthermore, vehicle sizes include small, medium, large, and towing vehicles. Therefore, as shown in FIG. 2 , the vehicle type i is determined by a combination of the energy type and the vehicle size, and is set as a small gasoline vehicle (1), a medium gasoline vehicle (2), a large gasoline vehicle (3), ..., a small BIO vehicle (11), a medium BIO vehicle (12), ..., a small EV vehicle (21), a medium EV (22), ..., and so on. However, the types of vehicles are not limited to those exemplified above, and may be set according to any classification.

[0015] In this embodiment, the period t is set to one year, and as shown in FIG. 2, each year from 2022 to 2030 is set. As a result, the number of vehicles by type x ｉｔ As shown in the left diagram of Figure 2, is expressed differently for each type i and for each period t. The period is not limited to one year, and may be any period. Also, the period does not have to be set, and in this case, the number of vehicles is x ｉ It will be expressed as:

[0016] Furthermore, coefficient a is the amount of carbon dioxide emitted by one vehicle in one year, and is set in advance depending on the type of vehicle i. For example, in the case of a gasoline vehicle (gasoline / diesel vehicle), coefficient a is calculated as follows: (amount of fuel consumed [kl / vehicle-year]) × (carbon dioxide emission coefficient [t-CO ２ / kl])). In this case, the amount of fuel consumed is calculated from the distance traveled and fuel efficiency of a specified company for each vehicle type i. For this reason, the amount of fuel consumed will be a different value depending on the size of the vehicle. In the case of BIO vehicles, coefficient a is calculated as follows: (amount of fuel consumed [kl / vehicle-year]) × (carbon dioxide emission coefficient [t-CO ２ / kl]) × 0.8". The reason why the amount of fuel consumed and the carbon dioxide emission coefficient are multiplied by 0.8 is that the fuel for BIO vehicles is a mixture of diesel and 20% biofuel, which reduces the amount of carbon dioxide emissions. However, the coefficient a for BIO vehicles may be set appropriately depending on the mixing ratio of biofuel. In the case of EV vehicles, the coefficient a is calculated by multiplying "(power consumption [kWh / vehicle-year]) × (carbon dioxide emission coefficient [t-CO ２ The value is calculated using the formula: [kWh / km]. In this case, the amount of power consumption is calculated from the monthly mileage and electricity cost for each vehicle type i at a specified operator. The coefficient a, which takes time dependency t into account, can represent, for example, a gradual increase or decrease in fuel consumption or a gradual increase or decrease in the calculation method of the carbon dioxide emission coefficient.

[0017] The second relational expression is expressed by a linear expression shown in the following equation 2. Here, the objective variable y' ｔ is the price (cost) of energy (fuel, electricity) for each period t. ｉｔ indicates the number of vehicles of each type i in each period t. ｉｔ is the price (cost) of energy (fuel, electricity) per vehicle of each type i of vehicle for each period t. Note that y' does not need to have the subscript t, in which case y' is the total price.

[0018] Here, coefficient b is the price of energy consumed by one vehicle over a year, and is set in advance depending on the type of vehicle i. For example, in the case of a gasoline vehicle (gasoline / diesel vehicle), coefficient b is a value calculated by (amount of fuel consumed [kl / vehicle-year]) x (fuel price [yen (t) / kl])). In this case, the fuel price taking into account time dependency t is obtained from an external database, and the current value and the predicted value for each year are used as is, or the value between the current value and the predicted value for a certain year is calculated by linearly interpolating the intermediate value. Note that coefficient b for BIO vehicles and EV vehicles is also set based on the price of BIO fuel and the price of electricity, as described above.

[0019] It is assumed that the above-mentioned first relational expression and second relational expression are created in advance, input to the information processing device 10, and stored in the relational expression storage unit 16. At this time, the above-mentioned coefficients a and b may be appropriately corrected and reflected in each relational expression.

[0020] The acquisition unit 11 acquires the above-described first relational expression and second relational expression and conditions for the variables included in these relational expressions, which are input by the business operator. The conditions are conditions that the variables included in the first relational expression and the second relational expression must satisfy when the calculation unit 12 calculates the number of vehicles of each type using the first relational expression and the second relational expression, as will be described later. For example, the conditions are expressed as conditions that must be satisfied for the amount of emissions y, the number x of each type of vehicle, and the cost y'.

[0021] As an example, the conditions are expressed as follows: Minimize the total price (cost) y' for year t (reduce the second relational expression) Carbon dioxide emissions y for each year t ｔis below a target value set for each year t (keeping the first relational expression below the target value) - The total number of vehicles x for each year t is below a set value (ensuring a number of vehicles that does not affect the business) - The total number of vehicles x of a specific type (gasoline vehicles) for each year t is below a set value (reducing the number of gasoline vehicles x with each passing year t) - The total number of vehicles x of a specific type (BIO vehicles, EV vehicles) for each year t is above a set value (increasing the number of BIO vehicles, EV vehicles x with each passing year t) - The increase in the number of vehicles of a specific type (BIO vehicles, EV vehicles) for each year t is below a set value (avoiding a sudden increase in BIO vehicles, EV vehicles) However, the conditions are not limited to those mentioned above and may be any.

[0022] The calculation unit 12 calculates the number of vehicles of each type so as to satisfy the conditions constituted by the first relational expression, the second relational expression, etc. In this case, the calculation unit 12 uses a mathematical optimization method (e.g., mixed integer linear programming) to solve the first relational expression, the second relational expression, etc. so as to satisfy the conditions, thereby calculating the number of vehicles of each type that is the solution. For example, in the first relational expression, the calculation unit 12 calculates the number of vehicles of each type that is the solution by using the annual carbon dioxide emissions y t is set to a target value or less, and in the second relational expression, the total cost y' for each year is minimized, and further, the number of vehicles of each type for each year is calculated so as to satisfy the condition set for the number of vehicles x.

[0023] The output unit 13 outputs the number of vehicles of each type for each year calculated by the calculation unit 12 so that the business operator can recognize it. For example, as shown in the right diagram of Fig. 2, the number of vehicles of each type for each year is displayed.

[0024] [Operation] Next, the operation of the information processing device 10 described above will be described.

[0025] First, the first and second relational expressions described above are input and stored in the information processing device 10 (step S1 in FIG. 3). In this situation, the business operator inputs conditions set according to environmental and business goals into the information processing device 10. The conditions include keeping carbon dioxide emissions below a target value, minimizing costs, and the number of specific types of vehicles. As a result, the information processing device 10 acquires the conditions (step S2 in FIG. 3).

[0026] Next, the information processing device 10 calculates the number of vehicles of each type for each year by solving the first relational expression and the second relational expression using a mathematical optimization method (e.g., mixed integer linear programming) so as to satisfy the conditions (step S3 in FIG. 3 ).The information processing device 10 then outputs the calculated number of vehicles of each type for each year to the business operator (step S4 in FIG. 4 ).

[0027] As described above, according to this embodiment, the number of vehicles of each type is calculated using the relational expression between the number of each type of vehicle and the amount of carbon dioxide emissions, so that businesses can easily make vehicle introduction plans that take the environment into consideration. In particular, by setting the conditions of keeping carbon dioxide emissions below a target value, minimizing costs, and further setting the number of vehicles, it is possible to support the creation of vehicle introduction plans that can achieve environmental and business goals.

[0028] Although the above example illustrates the case where the number of vehicles of each type is calculated for each period t, such as one year, a period does not necessarily have to be set. In this case, the number of vehicles of each type without a specified period is simply calculated.

[0029] In the above example, the first relational expression and the second relational expression are expressed linearly as shown in Expression 1 and Expression 2. However, the first relational expression and the second relational expression may be expressed nonlinearly. In this case, the calculation unit 12 may calculate the number of vehicles of each type, which is a solution, by using a method such as exhaustive search, quadratic cone optimization, semidefinite optimization, or polynomial optimization so as to satisfy the conditions.

[0030] [Modification 1] Next, a modification of the above-described process performed by the information processing device 10 will be described. Here, a modification of the above-described first relational expression will be described.

[0031] In the above, the objective variable y in the first relational expression shown in Equation 1 is the amount of carbon dioxide emitted from the vehicle, but this objective variable y is not limited to carbon dioxide and may be the amount of exhaust of a predetermined substance that causes an environmental load, such as greenhouse gases including other substances or air pollutants such as nitrogen oxides. In this case, the coefficient a is the amount of emission of the predetermined substance per vehicle for each type of vehicle, and the condition may be set such that the annual emission amount of the predetermined substance is equal to or less than a target value.

[0032] [Modification 2] Next, a modification of the above-described process performed by the information processing device 10 will be described. Here, a modification of the above-described second relational expression will be described.

[0033] In the above, the objective variable y' in the second relational expression shown in Equation 2 was the price of energy (fuel, electricity). However, this objective variable y' may be a value different from the emissions set in the first relational expression and may be another value (evaluation value) set depending on the vehicle. For example, the objective variable y' in the second relational expression may be the price of the vehicle itself. In this case, the coefficient b may be the purchase price per vehicle for each type of vehicle or the lease price per year. Furthermore, a condition may be set such that the total sum y' of the prices of the vehicles themselves per year is minimized.

[0034] Furthermore, for example, the objective variable y' in the second relational expression may be the sales or profit of the business of the operator. In this case, the coefficient b may be the sales or profit per vehicle for each type of vehicle. The condition may be set such that the sales or profit y' is maximized.

[0035] Furthermore, for example, the objective variable y' in the second relational expression may be the time or man-hours required for the business operator to carry out the business. In this case, the coefficient b may be the time or man-hours required per vehicle for each type of vehicle. The condition may be set to minimize the time or man-hours.

[0036] Furthermore, for example, the objective variable y' in the second relational equation may be an ESG score, which is an index that evaluates an operator's (company's) efforts in ESG (E: Environment, S: Social, G: Governance). In this case, the coefficient b may be an ESG score that can be calculated per vehicle for each vehicle type. A condition may be set that the ESG score be maximized. Note that instead of the ESG score, another evaluation value may be used as the objective variable y'.

[0037] [Variation 3] Next, another variation of the processing by the information processing device 10 described above will be described. In this embodiment, a case will be described in which the information processing device 10 is applied to a business content different from that of embodiment 1. In the above, the explanatory variable x in the first relational expression and the second relational expression is the number of vehicles of each type, but the explanatory variable x may be other equipment, materials, etc.

[0038] For example, if a business operator is engaged in the construction and design of buildings, the explanatory variable x may represent the quantity of each type of material (wall materials, flooring materials, etc.) used in the building or the equipment (solar panels, hot water heaters, electrical appliances, etc.) to be installed. In this case, the objective variable y in the first relational equation is the carbon dioxide emissions, as described above, and the coefficient a represents the carbon dioxide emissions per unit quantity during the manufacture and use of the materials and equipment. The objective variable y' in the second relational equation may represent the introduction cost or running cost of the materials and equipment, the energy consumption associated with the use of the materials and equipment, the time required for construction, a predetermined environmental evaluation value, etc., and the coefficient b represents the value of the objective variable y' per unit quantity during the manufacture and use of the materials and equipment. The conditions may include: the objective variable y in the first relational equation being below a certain value for carbon dioxide emissions; the objective variable y' in the second relational equation being minimized for costs; and the explanatory variable x representing the required quantity of each material and equipment. This allows the information processing device 10 to calculate the quantities of materials and equipment required for a building that can be constructed at low cost and in a short construction period while taking the environment into consideration.

[0039] As another example, if a business provides food and beverages, the explanatory variable x may represent the quantity of each type of ingredient (beef, chicken, vegetables, etc.) or tableware (plates, chopsticks, etc.) used in the food and beverages. In this case, the objective variable y in the first relational equation is the carbon dioxide emissions, as described above, and the coefficient a represents the carbon dioxide emissions per unit quantity during the production and use of the ingredients and tableware. For example, the objective variable a is set based on the carbon dioxide emissions emitted during the raising and cultivation of ingredients, and the coefficient a represents the carbon dioxide emissions per unit quantity during the production and use of wooden tableware. Furthermore, the objective variable y' in the second relational equation may represent the cost of the ingredients and tableware, and the coefficient b represents a value corresponding to the objective variable y' per unit quantity during the production and use of the ingredients and tableware. Conditions may include: the objective variable y in the first relational equation must be below a certain value; the objective variable y' in the second relational equation must be minimized; and the required quantity of each ingredient and tableware must be set. This allows the information processing device 10 to calculate the quantities of ingredients and tableware necessary to provide food and beverages at low cost while taking the environment into consideration.

[0040] As an example, when a business uses the first relational expression to plan employee transportation, the explanatory variable x may represent the use or nonuse of each type of transportation, such as train, bus, car, bicycle, or walking, and the travel distance. In this case, the objective variable y in the first relational expression is the carbon dioxide emissions, as described above, and the coefficient a represents the carbon dioxide emissions per unit travel distance when using the transportation. The objective variable y' in the second relational expression may represent the cost or travel time of using the transportation, and the coefficient b represents a value corresponding to the objective variable y' per unit travel distance or distance when using the transportation. Conditions may be set such that the objective variable y in the first relational expression is equal to or less than a certain value, and the objective variable y' in the second relational expression is minimized. This allows the information processing device 10 to calculate transportation methods that are low-cost and require short travel times while taking the environment into consideration.

[0041] [Variation 4] Next, another variation of the processing by the information processing device 10 described above will be described. While the information processing device 10 described above has illustrated a case in which the number of vehicles of each type is calculated using the first relational expression and the second relational expression, the information processing device 10 may calculate the number of vehicles of each type so as to satisfy a condition using only the first relational expression. In this case, the condition may be set such that the carbon dioxide emissions, which are the objective variable y in the first relational expression, are equal to or less than a certain value, and a constraint on the number of vehicles of each type. The information processing device 10 may calculate the number of vehicles of each type so as to satisfy such a condition using only the first relational expression. This allows the information processing device 10 to calculate the number of vehicles of each type while taking the environment into consideration. Note that even when only the first relational expression is used in this way, the objective variable y, explanatory variable x, and coefficient a may be set appropriately depending on the various businesses described above.

[0042] Second Embodiment Next, a second embodiment of the present disclosure will be described with reference to the drawings. This embodiment shows an outline of the configuration of the information processing device described in the above-mentioned embodiment. Note that Figures 4 and 5 are diagrams for explaining the configuration, and these diagrams may be relevant to any of the embodiments.

[0043] First, the hardware configuration of the information processing device 100 will be described with reference to Fig. 4. The information processing device 100 is configured as a general information processing device, and is equipped with the following hardware configuration, for example: CPU (Central Processing Unit) 101 (arithmetic unit); ROM (Read Only Memory) 102 (storage device); RAM (Random Access Memory) 103 (storage device); programs 104 loaded into RAM 103; storage device 105 storing programs 104; drive device 106 for reading and writing data from and to a storage medium 110 external to the information processing device; communication interface 107 for connecting to a communication network 111 external to the information processing device; input / output interface 108 for inputting and outputting data; and bus 109 for connecting the various components.

[0044] 4 shows an example of the hardware configuration of the information processing device 100, and the hardware configuration of the information processing device is not limited to the above-described case. For example, the information processing device may be configured with only a part of the above-described configuration, such as excluding the drive device 106. Furthermore, the information processing device may use a GPU (Graphics Processing Unit), a DSP (Digital Signal Processor), an MPU (Micro Processing Unit), an FPU (Floating Point Number Processing Unit), a PPU (Physics Processing Unit), a TPU (Tensor Processing Unit), a quantum processor, a microcontroller, or a combination thereof, instead of the above-described CPU.

[0045] The information processing device 100 can be equipped with the storage unit 121 and calculation unit 122 shown in FIG. 5 by having the CPU 101 acquire and execute the program group 104. The program group 104 is stored in advance in the storage device 105 or the ROM 102, for example, and is loaded into the RAM 103 and executed by the CPU 101 as needed. The program group 104 may be supplied to the CPU 101 via the communication network 111, or may be stored in advance in the storage medium 110, and the drive device 106 may read out the program and supply it to the CPU 101. However, the above-mentioned storage unit 121 and calculation unit 122 may be constructed using dedicated electronic circuits for realizing such means.

[0046] The storage unit 121 stores a relational expression using a quantity for each type of event set in advance and an emission amount of a predetermined substance set for each type of event. The calculation unit 122 calculates the quantity for each type of event based on the relational expression. At this time, the calculation unit 122 may calculate the quantity for each type of event based on the relational expression so as to satisfy conditions set for variables included in the relational expression.

[0047] With the above-described configuration, the present disclosure can calculate the quantity of each type of event based on a relational expression using the quantity of each type of event and the emission amount of a predetermined substance set for each type of event. This makes it possible to calculate the quantity of each type of event while taking the environment into consideration, thereby supporting the creation of event plans.

[0048] At least one of the functions of the memory unit 121 and the calculation unit 122 described above may be executed by an information processing device installed and connected anywhere on the network, that is, may be executed by so-called cloud computing.

[0049] The above-described program can be stored and supplied to a computer using various types of non-transitory computer-readable media. Non-transitory computer-readable media include various types of tangible storage media. Examples of non-transitory computer-readable media include magnetic recording media (e.g., flexible disks, magnetic tapes, hard disk drives), magneto-optical recording media (e.g., magneto-optical disks), CD-ROMs (Read Only Memory), CD-Rs, CD-RWs, and semiconductor memories (e.g., mask ROMs, PROMs (Programmable ROMs), EPROMs (Erasable PROMs), flash ROMs, and RAMs (Random Access Memory)). The program can also be supplied to a computer by various types of transitory computer-readable media. Examples of transitory computer-readable media include electrical signals, optical signals, and electromagnetic waves. The transitory computer-readable media can be supplied to a computer via wired communication paths such as electric wires and optical fibers, or via wireless communication paths.

[0050] Although the present disclosure has been described above with reference to the above-described embodiments, the present disclosure is not limited to the above-described embodiments. Various modifications that can be understood by those skilled in the art can be made to the configuration and details of the present disclosure within the scope of the present disclosure. Furthermore, each of the above-described embodiments can be combined with other embodiments as appropriate.

[0051] <Supplementary Notes> Some or all of the above embodiments can also be described as in the following supplementary notes. Below, an outline of the configurations of an information processing device, an information processing method, and a program according to the present disclosure will be described. However, the present disclosure is not limited to the following configurations. (Supplementary Note 1) An information processing device comprising: a storage unit that stores a relational expression using the quantity for each type of event and an emission amount of a predetermined substance set according to each type of event; and a calculation unit that calculates the quantity for each type of event based on the relational expression. (Supplementary Note 2) The information processing device according to Supplementary Note 1, wherein the calculation unit calculates the quantity for each type of event based on the relational expression so as to satisfy a condition set for a variable included in the relational expression. (Supplementary Note 3) The information processing device according to Supplementary Note 2, wherein the calculation unit calculates the quantity for each type of event based on the relational expression so as to satisfy the condition set for the emission amount included in the relational expression. (Supplementary Note 4) The information processing device according to Supplementary Note 2, wherein the calculation unit calculates the quantity of each type of event based on the relational expression so as to satisfy the condition set for the quantity of each type of event included in the relational expression. (Supplementary Note 5) The information processing device according to Supplementary Note 1, wherein the storage unit stores a second relational expression using the quantity of each type of event and an evaluation value set for each type of event that is different from the emissions, and the calculation unit calculates the quantity of each type of event based on the relational expression and the second relational expression. (Supplementary Note 6) The information processing device according to Supplementary Note 5, wherein the calculation unit calculates the quantity of each type of event based on the relational expression and the second relational expression so as to satisfy a second condition set for a variable included in the second relational expression. (Supplementary Note 7) The information processing device according to Supplementary Note 6, wherein the calculation unit calculates the quantity of each type of the event based on the relational expression and the second relational expression so as to satisfy the second condition set for the evaluation value included in the second relational expression.(Supplementary Note 8) The information processing device according to Supplementary Note 6, wherein the calculation unit calculates the quantity of each type of event based on the relational expression and the second relational expression so as to satisfy the second condition set for the quantity of each type of event included in the second relational expression. (Supplementary Note 9) The information processing device according to Supplementary Note 1, wherein the memory unit stores the relational expression using the quantity of each type of event and the emission amount for each preset period, and the calculation unit calculates the quantity of each type of event for each period based on the relational expression. (Supplementary Note 10) The information processing device according to Supplementary Note 5, wherein the memory unit stores the relational expression using the quantity of each type of event and the emission amount for each preset period, and stores the second relational expression using the quantity of each type of event for each period and the evaluation value, and the calculation unit calculates the quantity of each type of event for each period based on the relational expression and the second relational expression. (Supplementary Note 11) The information processing device according to Supplementary Note 1, wherein the storage unit stores the relational expression using the quantity of the events for each type that is set in accordance with energy usage by the events and the emission amount set in accordance with each type of the events. (Supplementary Note 12) The information processing device according to Supplementary Note 11, wherein the storage unit stores the relational expression using the number of owned vehicles for each type that is the event and the emission amount set in accordance with each type of the vehicle. (Supplementary Note 13) The information processing device according to Supplementary Note 5, wherein the storage unit stores the relational expression using the quantity of the events for each type that is set in accordance with energy usage by the events and the emission amount set in accordance with each type of the events, and also stores the second relational expression using the quantity of the events for each type and the evaluation value set in accordance with each type of the event.(Supplementary Note 14) The information processing device according to Supplementary Note 13, wherein the storage unit stores the relational expression using the number of owned vehicles of each type, which is the event, and the emission amount set for each of the vehicle types, and also stores the second relational expression using the number of vehicles of each type and the cost of the vehicles, which is the evaluation value set for each of the vehicle types. (Supplementary Note 15) An information processing method, wherein the quantity of each type of object is calculated based on a relational expression using the quantity of each type of event and the emission amount of a predetermined substance set for each of the event types. (Supplementary Note 16) The information processing method according to Supplementary Note 15, wherein the quantity of each type of event is calculated based on the relational expression so as to satisfy a condition set for a variable included in the relational expression. (Supplementary Note 17) The information processing method according to Supplementary Note 15, wherein the quantity of each type of object is calculated based on the relational expression and a second relational expression using the quantity of each type of event and an evaluation value set for each type of object different from the emission amount. (Supplementary Note 18) The information processing method according to Supplementary Note 17, wherein the quantity of each type of event is calculated based on the relational expression and the second relational expression so as to satisfy a second condition set for a variable included in the second relational expression. (Supplementary Note 19) A computer-readable storage medium storing a program for causing a computer to execute a process of calculating the quantity of each type of event based on a relational expression using the quantity of each type of event and an emission amount of a predetermined substance set for each type of event. (Supplementary Note 20) The storage medium according to Supplementary Note 19, wherein the storage medium stores a program for causing a computer to execute a process of calculating the quantity of each type of event based on a second relational expression using the quantity of each type of event and an evaluation value set according to each type of event that is different from the amount of emissions, and the relational expression.

[0052] REFERENCE SIGNS LIST 10 Information processing device 11 Acquisition unit 12 Calculation unit 13 Output unit 14 Relational equation storage unit 100 Information processing device 101 CPU 102 ROM 103 RAM 104 Program group 105 Storage device 106 Drive device 107 Communication interface 108 Input / output interface 109 Bus 110 Storage medium 111 Communication network 121 Storage unit 122 Calculation unit

Claims

1. a storage unit that stores a relational expression using the quantity for each type of event and the emission amount of a predetermined substance set according to each type of event; a calculation unit that calculates the quantity of each type of the event based on the relational expression; An information processing device comprising:

2. 2. The information processing device according to claim 1, the calculation unit calculates the quantity of each type of the event based on the relational expression so as to satisfy a condition set for a variable included in the relational expression; Information processing device.

3. 3. The information processing device according to claim 2, the calculation unit calculates the quantity of each type of event based on the relational expression so as to satisfy the condition set for the emission amount included in the relational expression; Information processing device.

4. 3. The information processing device according to claim 2, the calculation unit calculates the quantity of each type of the event based on the relational expression so as to satisfy the condition set for the quantity of each type of the event included in the relational expression; Information processing device.

5. 2. The information processing device according to claim 1, the storage unit stores a second relational expression using the quantity of each of the types of the event and an evaluation value set according to each of the types of the event that is different from the emission amount; the calculation unit calculates the quantity of each type of the event based on the relational expression and the second relational expression. Information processing device.

6. 6. The information processing device according to claim 5, the calculation unit calculates the quantity of each type of the event based on the relational expression and the second relational expression so as to satisfy a second condition set for a variable included in the second relational expression; Information processing device.

7. 7. The information processing device according to claim 6, the calculation unit calculates the quantity of each type of the event based on the relational expression and the second relational expression so as to satisfy the second condition set for the evaluation value included in the second relational expression; Information processing device.

8. 7. The information processing device according to claim 6, the calculation unit calculates the quantity of each type of the event based on the relational expression and the second relational expression so as to satisfy the second condition set for the quantity of each type of the event included in the second relational expression; Information processing device.

9. calculating the quantity of each type of event based on a relational expression using the quantity of each type of event and the emission amount of a predetermined substance set according to each type of event; Information processing methods.

10. calculating the quantity of each type of event based on a relational expression using the quantity of each type of event and the emission amount of a predetermined substance set according to each type of event; A program that causes a computer to execute a process.