Distribution support device, distribution support method, and program

Abstract

A distribution support device disclosed herein includes a calculation unit and a distribution result generation unit. The calculation unit, on the basis of acquired supply information, order information, and a distribution condition, acquires an index corresponding to the distribution condition from a database in which predetermined indices related to attributes are stored, and uses the acquired index to calculate a first coefficient related to a combination of supplying and orders in which the importance of the attribute is considered, and a second coefficient related to the importance of the orders. On the basis of the supply information, the order information, and the first coefficient and the second coefficient, the distribution result generation unit generates a predetermined distribution result including the allocated quantity of a product of the supply information with respect to the order information.

Description

Loading support device, loading support method, and program

[0001] The disclosed technology relates to a cargo distribution support device, a cargo distribution support method, and a program.

[0002] Conventionally, there are techniques for supporting market trading management.

[0003] Non-Patent Document 1 discloses a system for fruit and vegetable wholesale markets. The system in Non-Patent Document 1 has functions specialized for wholesale markets. Wholesale markets involve tasks such as order management, receipt management, distribution management, and sales management, and this system has the function to input and manage information related to these tasks, thereby contributing to supporting operations at wholesale markets.

[0004] Non-Patent Document 2 discloses another sales management system for the wholesale industry. The system in Non-Patent Document 1 features functions specialized for the wholesale industry, such as handling quality control items unique to the wholesale industry and handling consignment sales, a sales format unique to the wholesale industry. Like the system in Non-Patent Document 1, it is designed to support the operations of the wholesale industry and is equipped with functions to support these operations.

[0005] KitFit Marche Fruit and Vegetable Market System: Features and Functions | Tsuzuki Electric Solutions, https: / / tsuzuki.jp / jigyo / kitfit-marche / features-functions / Fresh Ichiba-kun: A sales management system specialized for wholesale and intermediate wholesale businesses | Mitsubishi Electric IT Solutions, https: / / www.mdsol.co.jp / products / freshichiba_product-outline /

[0006] One example of market operations is the distribution management of products among the various operations at wholesale markets. Distribution management involves allocating products collected / supplied from production areas across the country to orders from wholesalers and retailers, thereby completing sales and purchases between the two parties. When dividing products into multiple orders, wholesalers must simultaneously consider the conditions for multiple orders. Often, there is not enough stock to satisfy the conditions for all orders. Therefore, distribution management personnel must appropriately determine the priority of each order and decide on the final distribution. Specifically, orders may have multiple conditions, such as designated origin, grade, and class, and there are cases where orders from certain customers need to be prioritized over orders from other customers.

[0007] In such cases, even when using the systems described in Non-Patent Document 1 and Non-Patent Document 2, it is necessary to make decisions one by one while checking whether the results of allocating orders and supplies satisfy multiple conditions. Conventionally, personnel in charge of distribution management have created distribution results that satisfy conditions in accordance with various situations, based on past distribution performance and experience.

[0008] The disclosed technology has been developed in consideration of the above points, and aims to provide a loading support device, loading support method, and program that create loading results that take into account various circumstances and enable a reduction in the workload associated with loading.

[0009] A first aspect of the present disclosure is a loading support device that includes: an acquisition unit that acquires, as information for allocating and loading products to orders, supply information including multiple attributes and quantities of the product for the i-th supply from the supplier; order information including multiple attributes and quantities of the product for the j-th order from the orderer; and loading conditions related to the importance of each of the attributes and the order, based on the acquired supply information, order information, and loading conditions, acquires indicators corresponding to the loading conditions from a database in which predetermined indicators related to attributes are stored, and uses the acquired indicators to calculate a first coefficient related to the combination of supply and order that takes into account the importance of the attributes and a second coefficient related to the importance of the order; and a loading result creation unit that creates a predetermined loading result including the allocation quantity of the product in the supply information for the order information based on the supply information, the order information, the first coefficient, and the second coefficient.

[0010] A second aspect of the present disclosure is a loading support method in which a computer executes the following processing: as information for allocating and loading a product to be supplied to an order, supply information including multiple attributes and quantities of the product for the i-th supply from the supplier; order information including multiple attributes and quantities of the product for the j-th order from the orderer; and loading conditions related to the importance of each of the attributes and the order; based on the acquired supply information, order information, and loading conditions, an index corresponding to the loading conditions is acquired from a database in which predetermined indexes related to attributes are stored; using the acquired indexes, calculates a first coefficient related to the combination of supply and order that takes into account the importance of the attribute and a second coefficient related to the importance of the order; and creates a predetermined loading result including the allocation quantity of the product in the supply information for the order information based on the supply information, the order information, the first coefficient, and the second coefficient.

[0011] According to the disclosed technology, it is possible to create a distribution result that takes into account various circumstances, thereby reducing the workload associated with distribution.

[0012] FIG. 1 is a block diagram showing the hardware configuration of a loading support device. FIG. 2 is a block diagram showing the functional configuration of a support system including the loading support device of this embodiment. FIG. 3 is a flowchart showing the flow of support processing as a loading support method using the loading support device. FIG. 4 is a flowchart showing the calculation process of each coefficient. FIG. 5 is a flowchart showing the loading result creation process. FIG. 6A is supply information for input example (1). FIG. 6B is order information for input example (1). FIG. 6C is an example of loading conditions and read-out indicators for input example (1). FIG. 7 is an example of first and second coefficients. FIG. 8A is an example of loading results for input example (1). FIG. 8B is an example of loading results for input example (1). FIG. 9 is an example of loading conditions and read-out indicators for input example (2). FIG. 10 is an example of loading results for input example (2). FIG. 11 is an example of loading conditions and read-out indicators for input example (2). FIG. 12 shows an example of the distribution result in input example (3).

[0013] An example of an embodiment of the disclosed technology will be described below with reference to the drawings. Note that the same reference numerals are used to designate identical or equivalent components and parts in each drawing. Also, the dimensional proportions in the drawings are exaggerated for the sake of explanation and may differ from the actual proportions.

[0014] The configuration of an embodiment of the present disclosure will be described below.

[0015] FIG. 1 is a block diagram showing the hardware configuration of a load distribution support device 100. As shown in FIG. 1, the load distribution support device 100 includes a CPU (Central Processing Unit) 11, a ROM (Read Only Memory) 12, a RAM (Random Access Memory) 13, a storage 14, an input unit 15, a display interface (I / F) 16, and a communication interface (I / F) 17. Each component is connected to each other via a bus 19 so as to be able to communicate with each other. The load distribution support device 100 may be configured with one or more servers equipped with these hardware components, or may be configured with multiple servers.

[0016] The CPU 11 is a central processing unit that executes various programs and controls each part. That is, the CPU 11 reads the programs from the ROM 12 or the storage 14 and executes the programs using the RAM 13 as a work area. The CPU 11 controls the above components and performs various arithmetic processing in accordance with the programs stored in the ROM 12 or the storage 14. In this embodiment, the programs are stored in the ROM 12 or the storage 14.

[0017] The ROM 12 stores various programs and various data. The RAM 13 temporarily stores programs or data as a working area. The storage 14 is configured by a storage device such as an HDD (Hard Disk Drive) or an SSD (Solid State Drive), and stores various programs including an operating system and various data.

[0018] The input unit 15 includes a pointing device such as a mouse and a keyboard, and is used to input various types of information.

[0019] The display interface 16 is, for example, a liquid crystal display, and displays various information. The display interface 16 may be a touch panel type and function as the input unit 15.

[0020] The communication interface 17 is an interface for communicating with other devices such as terminals, etc. For this communication, for example, a wired communication standard such as Ethernet (registered trademark) or FDDI, or a wireless communication standard such as 4G, 5G, or Wi-Fi (registered trademark) is used.

[0021] Next, each functional configuration of the load distribution support device 100 will be described. Figure 2 is a block diagram showing the functional configuration of a support system including the support device of this embodiment. Each functional configuration is realized by the CPU 11 reading a program stored in the ROM 12 or storage 14, expanding it into the RAM 13, and executing it. Below, embodiments will be described separately according to the processing mode. Note that the hardware configuration and functional configuration are similar in each embodiment, so the same reference numerals will be used in the description.

[0022] First Embodiment As shown in FIG. 2, the support system 1 includes a distribution support device 100 and a user terminal 110 .

[0023] The user terminal 110 includes a first input unit 112 , a second input unit 114 , and a third input unit 116 .

[0024] The first input unit 112 accepts supply information input directly by the user or specified through a file, and outputs it to the distribution support device 100. The supply information consists of a supply ID, multiple attributes, and supply quantity. The multiple attributes include the desired sales date, shipping origin, grade, class, and packaging style.

[0025] The second input unit 114 accepts order information input directly by the user or specified via a file, and outputs it to the distribution support device 100. The order information consists of an order ID, multiple attributes, and order quantity. The multiple attributes include the desired purchase date, designated origin, designated grade, designated class, and designated packaging style.

[0026] The third input unit 116 accepts input of distribution conditions specified by the user and outputs them to the distribution support device 100. The distribution conditions include important attributes and designation of important orders. The designation format is, for example, [Place of Origin / Grade, None]. In this case, it indicates that the attribute with the first priority of importance is "Place of Origin," the attribute with the second priority of importance is "Grade," and it also indicates that important orders are not included in the distribution conditions.

[0027] The distribution support device 100 includes an acquisition unit 120 , a database 122 , a calculation unit 124 , and a distribution result creation unit 126 .

[0028] The acquisition unit 120 acquires supply information, order information, and distribution conditions as various information for allocating and distributing the products to be supplied to orders, through input from the user terminal 110. An example of a product is a product on the market.

[0029] The database 122 stores multiple indices related to attributes. The multiple indices are the importance of attribute pairs and weights corresponding to important attributes. The importance of attribute pairs is determined for attribute pairs on the supply side and the order side, and the importance is determined according to the degree of match, for example, "for each attribute, if the supply and the order are the same, the value is 2, and if they are different, the value is 1." Different values ​​may also be set for each attribute. Weights are determined according to the importance. For example, a value of 25 is set for an attribute with the highest priority, a value of 5 for an attribute with the second highest priority, and a value of 1 for the others.

[0030] The calculation unit 124 obtains indicators corresponding to the distribution conditions from the database 122 based on the obtained supply information, order information, and distribution conditions. The calculation unit 124 also uses the obtained indicators to calculate a first coefficient related to the combination of supply and order that takes into account the importance of the attributes, and a second coefficient related to the importance of the order. Details of the processing by the calculation unit 124 and each coefficient will be described later in the explanation of the operation.

[0031] The distribution result creation unit 126 creates a predetermined distribution result including the allocation quantity of the product in the supply information for the order information based on the supply information, the order information, the first coefficient, and the second coefficient. Details of the processing by the distribution result creation unit 126 will be described later in the explanation of the operation.

[0032] Next, the operation of the loading distribution support device 100 will be described. Figure 3 is a flowchart showing the flow of support processing as a loading distribution support method by the loading distribution support device 100. The support processing is performed by the CPU 11 reading a program from the ROM 12 or storage 14, expanding it into the RAM 13, and executing it. The loading distribution support device 100 executes the support processing in response to various information input from the user terminal 110.

[0033] In step S100, the CPU 11 functions as the acquisition unit 120 to acquire supply information, order information, and distribution conditions.

[0034] In step S102, the CPU 11, as the calculation unit 124, calculates a first coefficient for the combination of supply and order taking into account the importance of attributes and a second coefficient for the importance of the order, based on the acquired supply information, order information, and distribution conditions, using indicators acquired from the database 122.

[0035] In step S104, the CPU 11, as the distribution result creation unit 126, creates a predetermined distribution result including the allocation quantity of the product in the supply information for the order information based on the supply information, the order information, the first coefficient, and the second coefficient.

[0036] Next, the calculation process of each coefficient in step S102 will be described with reference to the flowchart of FIG.

[0037] In step S120, based on the acquired distribution conditions, the CPU 11 acquires the importance of the attribute pair and the weight of each attribute corresponding to the important attribute of the distribution conditions as indicators corresponding to the distribution conditions from the database 122. Examples of the indicators will be described later.

[0038] In step S122, the CPU 11 calculates a first coefficient C for the i-th supply in the supply information and the j-th order in the order information using the acquired supply information, order information, importance of the attribute pair, and weight of each attribute according to the following equation (1): ｉ，ｊ The first coefficient C ｉ，ｊ is the weight p of each attribute for each supply and order pair (i, j). ｋ The importance of attribute pairs is calculated using ｋ，ｉ，ｊ The weighted sum c ｉ，ｊ is obtained by taking ...(1)

[0039] Here, P = [p １ , ..., p Ｎ ], p ｋ : weight for the kth attribute. In this way, for each combination of the i-th supply and the j-th order, the first coefficient is calculated by calculating a weighted sum using the importance of the attribute pair and the weight of each attribute.

[0040] In step S124, the second coefficient d ｊ The second coefficient d ｊ In calculating this, for example, 1 is set for important orders specified as distribution conditions, and 0 is set for other orders. In this way, when an order that is designated as important in the distribution conditions is specified, the second coefficient is found by calculating a coefficient that corresponds the allocation quantity to the order quantity of the designated order.

[0041] Next, the distribution result creation process in step S104 will be described with reference to the flowchart of FIG.

[0042] In step S140, the CPU 11 calculates the allocation amount to be calculated by the variable q of the allocation amount from the i-th supply to the j-th order. ｉ，ｊ Define

[0043] In step S142, the CPU 11 calculates a first coefficient C expressed by the following equation (2): ｉ，ｊ and the allocation variable q ｉ，ｊ Define the objective function as a linear sum of ...(2)

[0044] In step S144, the CPU 11 sets (or updates) an allowable deviation of the allocation amount from the order quantity.

[0045] In step S146, the CPU 11 calculates the allocation variable q ｉ，ｊ The constraints that must be satisfied are defined as follows: [1] to [4]. [1] Allocation variable q ｉ，ｊ is greater than or equal to zero for all i and j. [2] Budget variable q ｉ，ｊ The sum of the quantities for j is equal to the i-th supply. [3] The quota variable q ｉ，ｊ The difference between the total quantity of i related to the jth order, i.e., the allocation quantity to the jth order, and the order quantity is equal to or less than the allowable deviation value. [4] The second coefficient d ｊ If is 1, the allocation to the jth order is set equal to the order quantity.

[0046] Regarding [4], the constraint may be a quantity corresponding to the designation of an important order. For example, if the designation of the distribution condition is "important order (at least 90% of the order quantity)", the second coefficient d ｊ In this way, the constraint [4] can be set to satisfy the allocation of the order quantity according to the second coefficient.

[0047] In step S148, the CPU 11 calculates the allocation variable q that maximizes the objective function by a mathematical optimization technique. ｉ，ｊ is derived.

[0048] In step S150, the CPU 11 determines whether a solution has been found. Whether a solution has been found can be determined, for example, by using a method that can determine whether constraints are satisfied, and by referring to the solution derivation result obtained by software used in the optimization method, such as a so-called solver. If a solution has been found, the process ends. If a solution has not been found, the process returns to step S144, where the deviation tolerance is updated to a larger value, and the derivation is repeated. The found solution is output as the derivation result of the derivation result creation unit 126.

[0049] Next, an input example (1) of supply information, order information, and distribution conditions will be explained. Fig. 6A shows the supply information of input example (1). Fig. 6B shows the order information of input example (1). Fig. 6C shows an example of distribution conditions and read-out indicators of input example (1).

[0050] The indexes that are read out will now be explained. The weight of each attribute that is read out in the calculation unit 124 according to the distribution conditions is the weight that combines multiple attributes. For example, if the important attribute of the distribution conditions is specified as "origin / grade", this indicates that origin is the first priority and is of high importance, followed by grade, which is the second priority and is of high importance. In this case, if the weight of each attribute is P = [p_origin, p_grade, p_class], the weight of each attribute that is read out will be P = [25, 5, 1]. Note that the symbol "_" indicates a subscript.

[0051] 7 shows an example of the first coefficient and the second coefficient. In the example shown in FIG. 7, as shown in the process of step S122, the first coefficient cｉ，ｊ For each supply and order pair (supply / order pair), the weight p ｋ The importance of attribute pairs is calculated using ｋ，ｉ，ｊ For each supply / order pair, the importance of each attribute pair v ｋ，ｉ，ｊ is read out. An example is given for the first edition supply / order pair "S1, D1". For "S1, D1", the attribute pair of origin is "Tochigi-Tochigi", which is the same for supply and order, so the result is 2. For "S1, D1", the attribute pair of grade is "A-SA", which is different for supply and order, so the result is 1. For "S1, D1", the attribute pair of class is "L-L", which is the same for supply and order, so the result is 2. The weighted sum of the importance of each attribute pair above is calculated as "25*2+5*1+1*2=57". Note that there is no important order, so the second coefficient is [d １ , d ２ ]=[0,0].

[0052] Figures 8A and 8B are examples of distribution results for input example (1). As shown in Figure 8A, the distribution results are the results of allocating quantities for each order and supply pair. If Figure 8A is summarized by order (D1 and D2), the distribution results are the results of allocation summarized by the breakdown of each supply for each order ID, as shown in Figure 8B. In the case of input example (1), the result is that D1 has a large allocation from Tochigi, and D2 has a large allocation from Aichi.

[0053] Next, input example (2) of supply information, order information, and distribution conditions will be explained. The supply information and order information are assumed to be the same as input example (1). Figure 9 is an example of the distribution conditions and the indexes read out for input example (2). The important attribute is "grade / class," with first priority being grade and second priority being class. In this case, the weight of each attribute P = [p_origin, p_grade, p_class] is P = [1, 25, 5]. Figure 10 is an example of the distribution result for input example (2). A distribution result is created that prioritizes matching of grades, resulting in a large allocation to D1 from S2, which matches SA, and a large allocation to D2 from S1, which matches A.

[0054] Next, an input example (3) of supply information, order information, and distribution conditions will be explained. The supply information and order information are the same as input example (1). Figure 11 is an example of distribution conditions and read-out indicators for input example (2). The important attribute is "grade / class", with first priority being grade and second priority being class, which is similar. Also, the important order is specified as "first order". In this case, the order ID is the first d １ is treated as important, and the second coefficient is [d １ , d ２ ] = [1, 0]. Figure 12 is an example of the distribution result for input example (3). In this case, as with input example (2), a distribution result is created that matches the grades preferentially and completely fills the order quantity for the first order, D1, i.e., the allocation number for D1 is 10.

[0055] As described above, the loading / unloading support device 100 of this embodiment creates loading / unloading results that take various situations into consideration, making it possible to reduce the workload associated with loading / unloading.

[0056] [Second Embodiment] The second embodiment is an aspect in which the first coefficient is calculated using history information. The calculation unit 124 may calculate the first coefficient by further using history information. In calculating the weighted sum related to the first coefficient, if history information exists for the ith supply in the supply information and the jth order in the order information, the history information is taken into consideration as shown in the following formula (3). The history information is expressed as a frequency and an interval (frequency, recency) as (f ｉ，ｊ , r ｉ，ｊ ) is expressed as ｉ，ｊ '=c ｉ，ｊ +q １ ×f ｉ，ｊ +q ２ ×r ｉ，ｊ ...(3)

[0057] Here, [q １ , q ２ ] is the weight and [q １ , q ２ ]=[1, -1], the greater the frequency and the smaller the recency, the greater the contribution. ｉ，ｊ) by adding historical information (frequency and interval weighted to adjust the contribution rate) to ｉ，ｊ ' is calculated. Furthermore, the value of the history information is added to the history specified by the weight of each attribute. This makes it possible to take into account history information linked to the past. As described above, when there is history information for a supply and order pair, the calculation unit 124 of the second embodiment calculates the first coefficient by adding values ​​related to the frequency and interval in the history information and calculating a weighted sum.

[0058] [Other Modifications] In the above-described embodiment, the importance of an attribute pair is set based on the degree of matching between the attribute pair, i.e., "2 if the supply and order are the same, 1 if they are different." However, this is not limited to this example. For example, the importance of an attribute pair may be assigned to each attribute according to the desired conditions. For example, the importance of a pair of origins may be set to 10 for "Tochigi-Tochigi," 5 for "Tochigi-Aichi," and 1 for "Tochigi-Kumamoto," as an importance inversely proportional to distance. Similarly, the importance of each attribute pair for grade pairs and class pairs may be set according to the distance. Similarly, the weights of each attribute may be set to any ratio, such as [100, 10, 1], rather than [25, 5, 1]. As described above, the importance of each attribute pair may be set according to the distance between the attribute pairs.

[0059] Regarding the distribution result creation unit 126, the allocation amount q from the i-th supply to the j-th order ｉ，ｊ is calculated using a mathematical optimization technique, but any other technique that optimizes (maximizes or minimizes) the objective function may be applied.

[0060] In the above embodiments, the support processing executed by the CPU after reading the software (program) may be executed by various processors other than the CPU. Examples of such processors include programmable logic devices (PLDs) whose circuit configuration can be changed after manufacture, such as field-programmable gate arrays (FPGAs), graphics processing units (GPUs), and dedicated electrical circuits, such as application-specific integrated circuits (ASICs), which are processors having a circuit configuration specifically designed to execute specific processing. The support processing may be executed by one of these various processors, or by a combination of two or more processors of the same or different types (e.g., multiple FPGAs, a combination of a CPU and an FPGA, etc.). Furthermore, the hardware structure of these various processors is, more specifically, an electric circuit that combines circuit elements such as semiconductor elements.

[0061] In the above embodiment, the program is pre-stored (installed) in the storage 14, but the present invention is not limited to this. The program may be provided in a form stored on a non-transitory storage medium such as a CD-ROM (Compact Disk Read Only Memory), a DVD-ROM (Digital Versatile Disk Read Only Memory), or a USB (Universal Serial Bus) memory. The program may also be downloaded from an external device via a network.

[0062] The following additional notes are provided regarding the above-described embodiments.

[0063] (Supplementary Item 1) A loading support device comprising: a memory; and at least one processor connected to the memory, wherein the processor is configured to: acquire supply information including multiple attributes and quantities of the product for the i-th supply from the supplier, order information including multiple attributes and quantities of the product for the j-th order from the ordering party, and loading conditions related to the importance of each of the attributes and the order, as information for allocating and loading products to be supplied to orders; acquire indicators corresponding to the loading conditions from a database in which predetermined indicators related to attributes are stored, based on the acquired supply information, order information, and loading conditions; calculate, using the acquired indicators, a first coefficient related to a combination of supply and order that takes into account the importance of the attribute, and a second coefficient related to the importance of the order; and create a predetermined loading support device including an allocation quantity of the product in the supply information for the order information, based on the supply information, order information, the first coefficient, and the second coefficient.

[0064] (Supplementary Item 2) A non-transitory storage medium storing a program executable by a computer to execute support processing, the non-transitory storage medium comprising: supply information including multiple attributes and quantities of the product for the i-th supply from the supplier; order information including multiple attributes and quantities of the product for the j-th order from the ordering party; and distribution conditions related to the importance of each of the attributes and the order, as information for allocating and distributing the product to be supplied to orders; obtains, based on the acquired supply information, order information, and distribution conditions, an index corresponding to the distribution conditions from a database in which predetermined indexes related to attributes are stored; calculates, using the acquired index, a first coefficient related to the combination of supply and order taking into account the importance of the attribute, and a second coefficient related to the importance of the order; and creates a predetermined distribution result including the allocation quantity of the product in the supply information for the order information, based on the supply information, order information, the first coefficient, and the second coefficient.

[0065] 1 Support system 100 Load distribution support device 110 User terminal 120 Acquisition unit 122 Database 124 Calculation unit 126 Load distribution result creation unit

Claims

1. A loading support device including: an acquisition unit that acquires, as information for allocating and loading products to be supplied to orders, supply information including multiple attributes and quantities of the product for the i-th supply from the supplier, order information including multiple attributes and quantities of the product for the j-th order from the ordering party, and loading conditions related to the importance of each of the attributes and orders; a calculation unit that acquires, based on the acquired supply information, order information, and loading conditions, indicators corresponding to the loading conditions from a database in which predetermined indicators related to attributes are stored, and calculates, using the acquired indicators, a first coefficient related to the combination of supply and order taking into account the importance of the attributes and a second coefficient related to the importance of the order; and a loading result creation unit that creates a predetermined loading result including the allocation quantity of the product in the supply information for the order information based on the supply information, order information, the first coefficient, and the second coefficient.

2. The distribution support device of claim 1, wherein the indicators to be obtained are the importance of attribute pairs defined for attribute pairs on the supply side and the order side and the weight of each attribute corresponding to the important attributes of the distribution conditions, and the calculation unit obtains the first coefficient by calculating a weighted sum using the importance of the attribute pairs and the weight for each combination of the i-th supply and the j-th order, and the calculation unit obtains the second coefficient by calculating a coefficient that corresponds the allocation quantity to the order quantity of the specified order when an order that is considered important in the distribution conditions is specified.

3. The distribution result creation unit defines a variable for the allocation amount from the i-th supply to the j-th order, defines an objective function as a linear sum of the first coefficient and the allocation amount variable, sets a predetermined deviation tolerance, defines constraints that the allocation amount variable must satisfy, finds the allocation amount variable that optimizes the objective function so as to satisfy the constraints, and creates the distribution result by updating the deviation tolerance and repeating optimization until a solution is obtained using a mathematical optimization technique.

4. The distribution support device of claim 2, wherein the calculation unit calculates the first coefficient by adding values ​​relating to frequency and interval in the history information and calculating the weighted sum when there is history information for a supply and order pair.

5. The distribution support device of claim 2, wherein the importance of the attribute pair is determined as an importance according to the degree of matching of the attribute pair, or as an importance determined for each attribute and for each attribute pair according to the distance between the attribute pairs.

6. Let the variable of the quota be q ｉ，ｊ and wherein the constraints are: first, the allocation variable is greater than or equal to zero for all i and j; second, the sum of the quantities of the allocation variable for j is equal to the i-th supply quantity; third, the sum of the quantities of the allocation variable for i is less than or equal to the deviation tolerance; and fourth, the allocation of the order quantity according to the second coefficient is satisfied.

7. A loading support method in which a computer executes the following processes: acquires, as information for allocating and loading products to be supplied to orders, supply information including multiple attributes and quantities of the product for the i-th supply from the supplier, order information including multiple attributes and quantities of the product for the j-th order from the ordering party, and loading conditions related to the importance of each of the attributes and orders; acquires, based on the acquired supply information, order information, and loading conditions, indicators corresponding to the loading conditions from a database in which predetermined indicators related to attributes are stored; calculates, using the acquired indicators, a first coefficient related to the combination of supply and order taking into account the importance of the attributes, and a second coefficient related to the importance of the order; and creates a predetermined loading result including the allocation quantity of the product in the supply information for the order information based on the supply information, order information, first coefficient, and second coefficient.

8. A program for causing a computer to function as each part of the distribution support device according to any one of claims 1 to 6.

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