KR101872070B1

KR101872070B1 - Apparatus for distributing goods based on production rate, method thereof, and computer recordable medium storing the method

Info

Publication number: KR101872070B1
Application number: KR1020150084994A
Authority: KR
Inventors: 장영재; 성신웅
Original assignee: 코오롱인더스트리 주식회사; 한국과학기술원
Priority date: 2015-06-16
Filing date: 2015-06-16
Publication date: 2018-06-27
Also published as: KR20160148252A

Abstract

The present invention relates to an apparatus for distributing a product based on a production rate, a method therefor and a computer-readable recording medium on which the method is recorded. The present invention relates to a demand prediction module for predicting demand, which is a quantity per product size for each of a plurality of stores, and a demand prediction module for calculating a ratio of a quantity of a product to a size of a product produced in a factory, A candidate derivation module for obtaining a candidate classification box constituted by a ratio having a size production ratio and a difference within a predetermined range; and a selection module for selecting, from a plurality of classification boxes in the candidate classification box, And a box construction module for deriving a kind and a quantity of the classification box which minimizes the number and type of the classification boxes, and a method therefor and a computer readable recording medium on which the method is recorded.

Description

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an apparatus for distributing a product based on a production rate, a method therefor, and a computer readable recording medium on which the method is recorded.

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a product dispensing technology, and more particularly, to an apparatus for distributing goods to each store using a classification box according to a product ratio of each product size, a method therefor and a computer- Media.

Logistics refers to the flow of water from producer to consumer with less physical distribution. In general, the concept of distribution includes activities to transfer goods and services from producers to consumers and to create the utility of place, time, and ownership. Logistics, on the other hand, defines logistics as a place that creates utility of place and time, excluding transactions that satisfy the utility of ownership. Specifically, it includes both the process of transporting, unloading, packing, and storing raw and subsidiary materials into production sites, producing and shipping finished products at factories and supplying them to end users, and distribution processes such as distribution processing and transportation infrastructure . In addition, information distribution concepts such as communication infrastructure and information network are all included here. Logistics therefore refers to the parts related to national key industry activities such as transportation infrastructure, communication infrastructure, and transportation, storage, unloading, packaging, distribution, processing and information functions that companies can manage in their own way. The concept of logistics comes from logistics, a field of military science. The know-how generated in the course of establishing and managing plans for the movement and withdrawal of military personnel, the supply of military supplies, and the construction and operation of facilities was introduced into business activities under the name of logistics.

Japanese Patent Application Laid-Open No. 2002-338054, Nov. 27, 2002 (Name: Product Classification Instruction System)

An object of the present invention is to provide an apparatus for distributing a product to each store by determining the type and number of classification boxes that minimize the difference from the demand forecast according to the production ratio of each product size, And a computer readable recording medium having recorded thereon.

According to another aspect of the present invention, there is provided an apparatus for distributing a product, comprising: a demand prediction module for predicting demand, which is a quantity per size of a product, for each of a plurality of stores; A candidate derivation module which obtains a candidate classification box constituted by a ratio of size production ratio which is a ratio of the quantity per product size of the product produced in the factory among the classification boxes having different configurations and a difference within a predetermined range, And a box configuration module for deriving the type and quantity of the classification box that minimizes the difference from the demand when distributing the product using the box.

The box configuration module calculates the type and quantity of the classification box using the following equation,

Wherein M is a maximum classification box configurable number of combinations, i is an index of a store, j is an index of a classification box, k is an index of a size, N is a number of stores, S is a number of size categories, , And

Is the demand quantity with respect to the size k of the store i,

Is the number of the size k of the classification box j,

Is the number of classification boxes j allocated to the store i.

Wherein the box configuration module stores at least one of a minimum number of classification boxes distributed to each of the stores, a maximum number of classification boxes distributed to each of the stores, a maximum value of the classification box types, and a maximum value of the number of classification boxes And the type of the classification box and the quantity of the classification box are limited.

The apparatus for distributing a product according to an exemplary embodiment of the present invention includes an interface unit for communication, a sorting box sorting unit for sorting the sorting box necessary for the entire store, And a distribution processing module for transmitting the quantity to the factory terminal via the interface unit.

An apparatus for distributing a product according to an embodiment of the present invention includes an interface unit for communication and a sorting and sorting unit for sorting the quantity and type of the sorting box corresponding to the demand of each store so that the goods are distributed according to the demand of each store, And a distribution processing module that transmits the distribution processing module to the terminal.

According to another aspect of the present invention, there is provided a method for distributing a product, the method comprising: predicting a demand, which is a quantity per size of a product, for each of a plurality of stores; The method comprising the steps of: obtaining a candidate classification box having a size production ratio, which is a ratio of the quantity of each size of a product produced at a factory, and a ratio having a difference within a predetermined range; And deriving the kind and quantity of the classification box that minimizes the difference from the demand when the product is distributed using the product.

Wherein the calculating step calculates the type and quantity of the classification box using the following equation,

Is the demand quantity with respect to the size k of the store i,

Is the number of the size k of the classification box j,

Is the number of classification boxes j allocated to the store i.

Wherein the calculating step calculates at least one of a minimum number of classification boxes distributed to each of the stores, a maximum number of classification boxes distributed to each of the stores, a maximum value of the classification box types, and a maximum value of the number of classification boxes And the type of the classification box and the quantity of the classification box are limited.

After the step of deriving the type and the quantity of the classification box, the kind and quantity of the classification box necessary for the entire store are transmitted to the factory terminal so that the product produced in the factory is packed in accordance with the kind and quantity of the classification box required for the entire store .

And transmitting to the warehouse terminal the type and quantity of the classification box corresponding to the demand of each store so that the goods are distributed according to the demand of each store after deriving the kind and quantity of the classification box.

According to another aspect of the present invention, there is provided a computer-readable recording medium having recorded thereon a method for distributing a product according to a preferred embodiment of the present invention.

According to the present invention as described above, a classification box is used to distribute a product to each store. The classification box may have a configuration in which the size and quantity of the goods are different. Further, the present invention determines the type and quantity of the classification boxes provided to each store according to the demand forecast, and packages the products produced in the factory using the determined types. Therefore, there is no need to carry out additional repacking work in the warehouse, and it is possible to save the logistics cost by simply providing the classification boxes in combination with each store. Moreover, because the distribution of goods through demand forecasting can not only reduce opportunity loss due to inadequate demand, but also reduce the loss of management overhead costs. In addition, since the type and quantity of the classification box are derived by using the candidate classification box configured at a similar ratio to the size production ratio, the computing speed of the computing apparatus performing such an operation is improved and the business can be processed quickly.

1 is a view for explaining a classification box according to an embodiment of the present invention.
Figures 2 and 3 are flow charts illustrating the benefits of goods distribution using a classification box in accordance with an embodiment of the present invention.
4 is a view for explaining a method of constructing a classification box according to an embodiment of the present invention.
FIG. 5 is a view for explaining a correlation between a production amount of a product according to an embodiment of the present invention and a ratio of a size of a product stored in a classification box used for distribution.
6 and 7 are views for explaining a goods distribution system according to an embodiment of the present invention.
8 is a block diagram illustrating a configuration of a management server according to an embodiment of the present invention.
9 is a flowchart for explaining a method for distributing a product of the goods distribution system according to the embodiment of the present invention.
10 is a flowchart for explaining a method for distributing a product of a management server according to an embodiment of the present invention.

Prior to the detailed description of the present invention, the terms or words used in the present specification and claims should not be construed as limited to ordinary or preliminary meaning, and the inventor may designate his own invention in the best way It should be construed in accordance with the technical idea of the present invention based on the principle that it can be appropriately defined as a concept of a term to describe it. Therefore, the embodiments described in the present specification and the configurations shown in the drawings are merely the most preferred embodiments of the present invention, and are not intended to represent all of the technical ideas of the present invention. Therefore, various equivalents It should be understood that water and variations may be present.

Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings. Note that, in the drawings, the same components are denoted by the same reference symbols as possible. Further, the detailed description of known functions and configurations that may obscure the gist of the present invention will be omitted. For the same reason, some of the elements in the accompanying drawings are exaggerated, omitted, or schematically shown, and the size of each element does not entirely reflect the actual size.

According to the embodiment of the present invention, a product is distributed to each store using a classification box. The classification box will be described below. 1 is a view for explaining a classification box according to an embodiment of the present invention.

Referring to FIG. 1, a sorting box according to an embodiment of the present invention is basically a packaging container for storing goods having different sizes and quantities. In an embodiment of the present invention, the article can be a garment. As shown, the size of the garment is L (large), M (medium) and S (small). These classification boxes may have various types, and they may be composed of different sizes and quantities according to their types. 1, the sorting box 1 accommodates 5 size S, 10 size M, and 5 size L. [ Classification Box 2 contains three S size, eight M size and three L size. Classification Box 3 contains three S sizes, five M sizes and zero L sizes. The classification box j stores 0 size S, 3 sizes M, and 0 size L.

As described above, the classification boxes are configured in different sizes and quantities according to their types, and there is an advantage that the burden of logistics can be reduced when such classification boxes are used. The advantages of such a classification box will now be described in more detail. Figures 2 and 3 are flow charts illustrating the benefits of goods distribution using a classification box in accordance with an embodiment of the present invention. FIG. 2 shows a general product dispensing process using a general packing box without a classification box, and FIG. 3 shows a product distribution process based on a classification box. Referring to FIG. 2 and FIG. 3, a general product distribution procedure and a classification box-based product distribution procedure will be described in comparison with each other. Particularly, in FIG. 2 and FIG. 3, the 'shipping center' emphasizes that the warehouse is a small warehouse in terms of the capacity to store goods compared to the 'warehouse'. In other words, a 'warehouse' is a large warehouse in terms of capacity to store goods compared to a 'shipping center'.

As shown in the figure, a general product dispensing process produces goods at a factory, packages each product by size, and then delivers it to a shipping center and a warehouse. For example, L size, M size, and S size of the garment A are packed in different packaging boxes. The packaging made at the factory is made by size, but the goods to be shipped to each store must provide goods of different size and quantity. For example, it is necessary to provide clothing A with three L size, M size ten, and S size seven. Therefore, the shipping center or the warehouse should repackage each quantity according to the size required for each store. That is, after opening the packaging box packed by size, it is packed again in another packaging box in the size and quantity necessary for each store. Once these packages are completed, the items can be shipped to the store, and each store can sell the product to the customer.

On the other hand, if we look at the distribution procedure based on the classification box, the product is produced at the factory, packed using the classification box, and then delivered to the delivery center. Since the classification box has a different quantity for each size, a combination of one or more classification boxes can match the quantity per size required for each store. Therefore, unlike the general product distribution procedure, the shipping center combines the required classification boxes and delivers them to the store without having to repackage them according to the size required for each store. Then, you can sell it to customers at each store. As described above, in the case of using the classification box, there is no need for a repackaging procedure before delivery, and therefore, the time for storing the goods in the warehouse is extremely short because the repacking time and manpower are reduced. As described above, according to the goods distribution procedure based on the classification box, time and manpower are remarkably reduced, and only a small-sized shipping center can be used, resulting in a remarkable saving in logistics costs.

In order to maximize the benefits of the classification box described above, it is important to know how to construct the classification box. Hereinafter, how to configure a classification box for optimal product distribution according to an embodiment of the present invention will be described. 4 is a view for explaining a method of constructing a classification box according to an embodiment of the present invention.

According to the present invention, the distribution of goods is based on demand, and the demand means the quantity per size of each product required in each store. Here, demand is a predicted value, and such demand forecasting can be performed based on sales data such as sales results. The demand prediction in the embodiment of the present invention is not limited, but the demand prediction predicts the quantity of each product size required in each store.

As shown in FIG. 4, it is assumed that when there is a store 1 to store i, the demanded quantity (demanded quantity) of each store by the demand size is derived by the demand forecast. In case of store 1, 7 size S, 23 size M, and 10 size L are required. For store 2, 5 sizes S, 12 sizes and 4 sizes are required. , S size 3, M size 8, and L size 2 are required. For store i, it is assumed that 10 size S size, 20 size M size, and 9 size L are required.

As shown in the figure, in the case of the sorting box 1, five sorting boxes S, 10, and 5 are used for distributing goods. In the case of sorting box 2, three sorting boxes S M size 8, and L size 3, and in the case of the classification box 3, it is assumed that the classification box 3 is composed of three S sizes and five M sizes, and the classification box j is composed of three M sizes.

For example, when the classification boxes 1, 2, and j are distributed to the store 1 according to the demand of the store 1, the products distributed to the store 1 are 8 size S size, 21 size M size, and 8 size L size. Compared to the demand for store 1, there are one S size, two M sizes, and two L sizes. In this way, when distributing a product using a classification box, it may not provide the same quantity as the demand.

Therefore, according to the present invention, when distributing a product using a classification box, the classification of the classification box and the quantity of the classification box should be determined so that the difference from the demand is minimized. This will be described in more detail with reference to another example. For example, it is assumed that there are three stores, and the demand is as shown in Table 1 below.

store S size M size L size Store 1 9 20 9 Store 2 9 15 7 Store 3 8 10 6

It is assumed that the configuration of the classification box is as shown in the following Table 2 as a reference example as a reference for comparison.

Classification box S size M size L size Classification Box 1 5 10 5 Classified Box 2 3 9 4 Classification Box 3 3 4 2

According to the example of Table 2, when one sorting box 1 and one sorting box 2 are distributed in the store 1, the products distributed to the store 1 are S size 8, M size 19, and L size 9. Compared with the demand for the store 1 shown in Table 1, one S size is lacking and one M size is lacking. In addition, when one classification box 2 and one classification box 3 are distributed in the store 2, the products distributed in the store 2 are 6 sizes of S size, 13 sizes of M size, and 6 sizes of L size. Compared with the demand for store 2 shown in Table 1, it lacks three sizes, lacks two sizes, and lacks one size. And if you distribute 2 boxes 3 in store 3, the products distributed in store 3 are 6 size S, 8 size M, and 4 size L. Compared to the demand for store 3 shown in Table 1, it lacks two S sizes, lacks two M sizes, and lacks two L sizes. In other words, when using the classification boxes shown in Table 2, the difference from the demand is 6 S size, 5 M size, and 3 L size.

As a comparative example for comparison with the above-described reference example, it is assumed that the configuration of the classification box is as shown in Table 3 below.

Classification Box Configuration S size M size L size Classification Box 1 5 10 5 Classified Box 2 4 10 4 Classification Box 3 4 5 3

According to the example of Table 3, when one classified box 1 is distributed to store 1 and one classified box 2 is distributed to store 1, there are nine S size, 20 M size, and 9 L size. This is not different from the demand for store 1 shown in Table 1. In addition, when one classification box 2 is distributed to the store 2, and one classification box 3 is distributed, the products distributed to the store 2 are S size 8, M size 15, and L size 7. This is due to the lack of one S size when compared to the demand for Store 2 shown in Table 1. If you distribute 2 boxes 3 in store 3, the products distributed to store 3 are 8 size S, 10 size M and 6 size L. This is not different from the demand for Store 3 shown in Table 1. In other words, when using a classification box having the configuration shown in Table 2, only one difference in size is in short supply.

As described above, when the classification boxes in Table 3 are used, it can be seen that the difference from demand is reduced as compared with the use of the classification boxes in Table 2. [ As such, the present invention must derive the type and quantity of the optimal sort box in order to minimize the difference from demand. In other words, to minimize the difference from demand, what type of classification box should be used, and how many classification boxes should be used. For example, according to Tables 1 and 3, the present invention can derive the types and the quantities of the classification boxes as shown in Tables 4 and 5 below.

Classification Box Configuration S size M size L size Quantity Classification Box 1 5 10 5 One Classified Box 2 4 10 4 2 Classification Box 3 4 5 3 3

store Quantity in Box 1 Quantity in Box 2 Quantity in Box 3 Store 1 One One 0 Store 2 0 One One Store 3 0 0 2

Referring to Tables 4 and 5, the types and the quantities of derived classification boxes are classified into the types of classification boxes required for the entire store as shown in Table 4, the quantity according to the types, and the demand for each store as shown in Table 5 And the type and quantity of the classification box corresponding to the classification box. Through the types and quantities of classification boxes as shown in Table 4, the types of classification boxes have a certain configuration (size and quantity of each size), and it is possible to know how many kinds of classification boxes should be prepared. Through the types and quantities of classification boxes as shown in Table 5, it is possible to know how many kinds of classification boxes should be distributed to which stores.

According to the present invention, the types and the quantities of the above-mentioned classification boxes can be derived by using the following equation (1).

Where N is the number of stores, S is the number of size categories, M is the maximum number of classification box configurable combinations, i is the index of the store, j is the index of the classification box, and k is the index of the size. Also,

Is the demand for size k of store i,

Is the number of the size k of the classification box j,

Represents the number of classification boxes j allocated to store i. According to the equation (1), when there is a demand for each size of the store, the present invention derives the sort box quantity and the quantity that minimizes the difference from the demand.

On the other hand, for example, in the case of using a sort box in which one size and one quantity are accommodated, it is the same as the individual package, and the use of such a classification box can satisfy the demand of all stores, It is the same. Thus, according to the present invention, when deriving the classification box type and quantity, the following items can be set in advance. That is, the present invention sets the minimum number of classification boxes distributed to each store, the maximum number of classification boxes distributed to each store, the maximum value of the configuration of the classification box, and the maximum value of the number of classification boxes. This setting will be described in more detail as follows.

When deriving the types and the quantities of the classification boxes through Equation (1), the minimum quantity of the classification boxes distributed to each store can be defined according to the following equation (2).

For example, in the equation (2), if the min value is 1, the minimum number of classification boxes distributed to each store is one.

Also, when deriving the types and the quantities of the classification boxes through Equation (1), the maximum quantity of the classification boxes distributed to each store can be defined according to the following Equation (3).

For example, in the equation (3), if the max value is 3, the maximum number of classification boxes distributed to each store is three.

Also, when deriving the types and the quantities of the classification boxes through Equation (1), the maximum value of the configuration of the classification box can be defined by the following Equation (4).

In Equation (4)

Represents 1 if the classification box j is used, and 0 otherwise.

For example, if the max value is 6, the maximum value of the classification box type is six. That is, there are six classification boxes in total.

Also, when deriving the types and the quantities of the classified box through Equation (1), the maximum value of the quantity of the classified box can be defined by the following Equation (5).

For example, if the max value is 800, the maximum value of the number of classification boxes is 800.

In addition, it is possible to limit the number of stores for which classification boxes are to be provided, the maximum number of items that can be stored in one sort box, and the minimum number of items to be stored in one sort box.

In summary, when deriving the type and quantity of classification boxes using Equation (1), the minimum quantity of classification boxes distributed to each store, the maximum quantity of classification boxes distributed to each store, the maximum value of the configuration of classification boxes, The maximum number of items in the classification box, the number of stores for which a classification box should be provided, the maximum number of items that can be stored in one classification box, and the minimum quantity of products to be stored in one classification box, Can be derived.

Meanwhile, the present invention provides a method for reducing the amount of computation of a process for deriving the types and quantities of classification boxes through the above-described Equation (1). The present invention adopts a method of reducing the object of calculation in order to reduce the amount of computation. FIG. 5 is a view for explaining a correlation between a production amount of a product according to an embodiment of the present invention and a ratio of a size of a product stored in a classification box used for distribution.

5, one product is composed of four kinds of sizes, that is, sizes 85, 90, 95 and 100, and the production amount (PA) per size, which is the production amount for each size of the product produced in the factory, is 200 , 867, 680 and 200, respectively. Then, the size production ratio (PR), which is a ratio of each size of produced goods, becomes 0.10: 0.45: 0.35: 0.10. On the other hand, the classification box stores different quantities for each size, and the ratio of the sizes stored in the classification box is referred to as a " size ratio CR ". When the type of classification box derived from Equation (1) is examined, the size composition ratio (CR) of the classification box used for product distribution has a difference within a certain range from the size production ratio (PR) The size ratio CR of the box shows a difference of more than a certain range from the size production ratio PR. For example, referring to FIG. 1, a classification box 1947, which is one of a plurality of classification boxes derived through Equation 1 and used for product distribution, has a size ratio CR of 0.09: 0.45: 0.36: The difference in production rate (PR = 0.10: 0.45: 0.35: 0.10) is 0.01, 0, -0.01, and 0.01 for each size. On the other hand, the classification box 334, which is one of the classification boxes not adopted, shows a difference of 0.04, 0.39, -0.54, and 0.10 by the size production ratio (PR) and size. As described above, the size composition ratio CR of the sort box 334 which is not adopted in comparison with the size constituent ratio CR of the adopted sort box 1947 shows a large difference from the size production ratio PR. In other words, the size constituent ratio CR of the adopted sort box 1947 is smaller than the size constituent ratio PR of the sort box 334 which is not adopted. Accordingly, even when only the classification box composed of the size production ratio PR and the size composition ratio CR having a difference within a predetermined range is considered, the type and quantity of the optimal classification box can be obtained.

Let's take a look at how to reduce the amount of computation in more detail. Assuming that the size of the product is 4, the maximum number of items that can be accommodated in one classification box is 20, and the minimum number of items to be contained in one classification box is 2, the number of types of configurable classification boxes is 10,621 as shown in Table 6.

Classification Box Type Size 85 Size 90 Size 95 Size 100 Classification Box 1 8 4 4 4 Classified Box 2 One 5 3 4 Classification Box 3 2 One 4 3 Classification Box 4 10 0 4 0 Classification Box 5 3 One 8 7 Classification Box 6 One 6 0 12 Classification Box 7 5 0 6 5 Category Box 8 2 13 5 0 Classification Box 9 3 2 2 10 Classification Box 10 9 7 One 0 .
.
.
. Classification Box 10,621 8 5 2 0

When considering all the 10,621 classification boxes, the present invention uses the above-described size production ratio (PR) because it takes a lot of time to obtain the result due to a large amount of computation. It is assumed that the production amount (PA) and the size production ratio (PR) by size are as shown in Table 7 below.

Size 85 Size 90 Size 95 Size 100 Production by size
(PA) 200 867 680 200 Size production ratio
(PR) 0.10 0.45 0.35 0.10

As described above, according to the actual calculation result, since the classification box having the size composition ratio CR similar to the size production ratio PR is selected, the size production ratio PR and the size composition ratio (CR). The classification box thus extracted will be referred to as a " candidate classification box ". Such candidate classification boxes are, for example, as shown in Table 8 below.

Classification Box Type Size 85 Size 90 Size 95 Size 100 Classification Box 1 One 4 3 One Classified Box 2 2 8 6 2 Classification Box 3 One 5 4 One Classification Box 4 2 7 6 2 Classification Box 5 2 7 5 2 Classification Box 6 One 8 6 2 Classification Box 7 2 8 6 One Category Box 8 One 7 6 2 Classification Box 9 2 7 6 One Classification Box 10 One 6 5 One .
.
.
. Classification Box 30 One 7 6 One

As shown in Table 8, the candidate classification box is a classification box composed of a size production ratio (PR) of all kinds of classification boxes and a size composition ratio (CR) of a difference within a predetermined range. Typically, an example of the classification box 1 among the candidate classification boxes is 0.11: 0.44: 0.33: 0.11, and the size ratio CR of the classification box 1 is different from the size production ratio (PR = 0.10: 0.45: 0.35: 0.10) not big. These candidate classification boxes are 30 kinds. This is only 0.28% of the 10,621 classification boxes in Table 6. When the type and quantity of the classification box are calculated using Equation (1) in consideration of only the candidate classification box, the calculation amount of Equation (1) is reduced and the calculation time can be shortened.

The difference within the predetermined range described above may be changed according to the setting of the user. That is, the degree of difference between the size ratio CR and the size ratio PR for deriving the candidate classification box can be changed according to the user's setting. The larger the degree of difference, the larger the number of candidate classification boxes, and if the degree of difference is reduced, the number of candidate classification boxes will decrease. Therefore, these differences can be derived through repeated simulations or adjusted to the computing power of the device.

According to the embodiment of the present invention, the difference within the predetermined range may be limited to a case where the sum of the differences of all the size ratios is within the predetermined value. For example, it may be set to a case where the sum of the differences for the ratios of all sizes is less than 0.15. If the size production ratio (CR) is 0.09: 0.55: 0.36: 0.09 and the size production ratio (PR) is 0.10: 0.45: 0.35: 0.10, the difference is 0.01, 0.1, -0.01 and 0.01 for each size. The sum of the differences for all sizes is | 0.01 | + | 0.1 | + | -0.01 | + | 0.01 | = 0.13. Accordingly, the classification box having the size ratio CR can be selected as the candidate classification box. According to the embodiment of the present invention, the difference within the predetermined range may be such that the sum of the differences of all the size ratios is within the predetermined value, and the difference of the respective size ratios does not exceed the predetermined value. For example, the sum of the differences of the ratios of all the sizes may be set to less than 0.15, and the difference of the ratios of the sizes may not exceed 0.09. If the size production ratio (CR) is 0.09: 0.55: 0.36: 0.09 and the size production ratio (PR) is 0.10: 0.45: 0.35: 0.10, the difference is 0.01, 0.1, -0.01 and 0.01 for each size. The sum of the differences for all sizes is 0.13, so the sum of the differences for the ratios of all sizes is less than 0.15, but the difference between the second sizes is 0.1 to 0.09. Accordingly, the classification box having the size ratio CR can not be selected as the candidate classification box.

Hereinafter, configurations of the present invention for distributing a product using the classification box as described above will be described. First, a system for distributing goods according to an embodiment of the present invention will be described. 6 and 7 are views for explaining a goods distribution system according to an embodiment of the present invention.

6 and 7, the goods distribution system according to the embodiment of the present invention is for distributing goods to each store using a classification box. The goods distribution system includes a management server 100, a factory terminal 200, a warehouse terminal 300, and a store terminal 400.

The management server 100 is a device for managing overall matters concerning distribution of goods. As a representative example, the management server 100 may be a computing device having server-class computing computing capability. The factory terminal 200 is a device disposed in each factory (factory 1 to factory a) for producing goods. The warehouse terminal 300 is a device disposed in a warehouse for temporarily storing goods, and the store terminal 400 is a device disposed in each store (store 1 to store i). The factory terminal 200, the warehouse terminal 300, and the store terminal 400 may be a personal computer as a representative example. In addition, the factory terminal 200, the warehouse terminal 300, and the store terminal 400 may be, for example, a smart phone, a tablet device, a pellet device, a PDA, a notebook computer, or the like. The factory terminal 200, the warehouse terminal 300, and the store terminal 400 may be connected to the management server 100 via a network.

Basically, the store terminal 400 stores sales data having information related to sales made at a store where the store terminal 400 is disposed. This sales data includes a quantity per size of goods sold for a predetermined period. Accordingly, the store terminal 400 transmits the sales data to the management server 100 at predetermined intervals so that the management server 100 can predict the demand.

The management server 100 collects sales data from a plurality of store terminals 400 via a network, and predicts the demand of each store. Although the specific algorithm for predicting demand in the embodiment of the present invention is not limited, the management server 100 can derive the quantity per size of each product in each store through demand forecasting. 1 to 4, the management server 100 derives the type and quantity of the classification box so that the difference from the predicted demand is minimized according to the predicted demand for each store. At this time, in order to reduce the amount of computation, the type and quantity of classification boxes can be calculated considering only the candidate classification box. As shown in Table 8, the candidate classification box is composed of a ratio of size production ratio, which is the ratio of the quantity of each size of the product produced in the factory among all kinds of classification boxes, and a ratio having a difference within a predetermined range.

The factory terminal 200 transmits the production amount data including the production amount per product size to the management server 100 so that the management server 100 derives the size production ratio which is the ratio of the quantity of each size of the product produced in the factory . In addition, the factory terminal 200 receives the type and quantity of the classification box derived by the management server 100 from the management server 100 via the network, and displays the type and quantity of the received classification box on the screen. The type and quantity of the classification box displayed on the screen may be the type and quantity of the classification box corresponding to the entire store as shown in Table 4. [ Accordingly, the employees of the factory will pack the goods according to the type and quantity of the classification box. Then, the product packed in the box at the factory will be shipped and put into the warehouse.

The warehouse terminal 300 receives the type and quantity of the classification box derived by the management server 100 from the management server 100 via the network and displays the type and quantity of the received classification box on the screen. The types and the quantities of the classification boxes displayed on the screen of the warehouse terminal 300 may be the types and the quantity of the classification boxes corresponding to the demand of each store as shown in Table 5. [ Accordingly, one or more sort boxes will be delivered to the store for each store in the warehouse.

Next, the configuration of the management server 100 according to the embodiment of the present invention will be described in more detail. 8 is a block diagram illustrating a configuration of a management server according to an embodiment of the present invention.

The management server 100 includes an interface unit 110, an input unit 120, a display unit 130, a storage unit 140, and a control unit 150. [

The interface unit 110 is a network interface for communication with the factory terminal 200, the warehouse terminal 300, and the store terminal 400, respectively. The interface unit 110 may include a modem, an interface card, a wired / wireless LAN card, a USB port, a serial port, a parallel port, and a data bus. The interface unit 110 can receive various messages, information, data, and the like from the control unit 150 and transmit the received messages, information, and data to the store terminal 400. The interface unit 110 may receive various messages, information, data, and the like from the store terminal 400 and may transmit the received messages, information, and data to the control unit 150.

The input unit 120 receives a user's key operation for controlling various functions, operations, and the like of the management server 100, generates an input signal, and transmits the generated input signal to the controller 150. The input unit 120 may be a keyboard, a mouse, or the like. The input unit 120 may include at least one of a power key, a character key, a number key, and a direction key for power on / off. The function of the input unit 120 may be performed in the display unit 130 when the display unit 130 is implemented as a touch screen and may be omitted if the display unit 130 can perform all functions only have.

The display unit 130 may receive data for screen display from the control unit 150 and display the received data on a screen. Particularly, it is possible to display on the screen the demand, the configuration of the classification box, and the like according to the size of the store according to the embodiment of the present invention. Also, the display unit 130 can visually provide menus, data, function setting information, and various other information of the management server 100 to the user. When the display unit 130 is formed by a touch screen, some or all of the functions of the input unit 120 may be performed instead. The display unit 130 may include a liquid crystal display (LCD), an organic light emitting diode (OLED), and an active matrix organic light emitting diode (AMOLED).

The storage unit 140 stores each kind of data required for the operation of the management server 100, each application, and each kind of data generated according to the operation of the management server 100. The storage unit 140 may be a storage unit, a memory unit, or the like. The storage unit 140 may include a program area and a data area. The program area includes an operating system (OS) for booting and operation of the management server 100, an application for executing a method for deriving an optimal classification box configuration according to an embodiment of the present invention, An application executing a method for distributing a product according to an embodiment of the present invention, and the like. The data area may store various species data for product distribution. Each kind of data stored in the storage unit 140 can be deleted, changed or added according to a user's operation.

The control unit 150 may control the overall operation of the management server 100 and the signal flow between the internal blocks of the management server 100 and may perform a data processing function of processing the data. The controller 190 may be a central processing unit (CPU), an application processor, a GPU (Graphic Processing Unit), or the like.

The control unit 150 includes a demand prediction module 151, a candidate derivation module 153, a box configuration module 155, and an allocation processing module 157. The demand prediction module 151 is for predicting the demand, which is the demand amount per product size, for each store. The candidate derivation module 153 generates a candidate classification box composed of a size production ratio which is the ratio of the quantity of each size of the product produced in the factory among all kinds of classification boxes and a ratio (size composition ratio) . The box configuration module 155 derives the types and the quantities of the classification boxes that minimize the difference from the predicted demand when distributing the products to each store by selecting a plurality of classification boxes from among the candidate classification boxes. The distribution processing module 157 is for distributing the products according to the types and quantity of the derived boxes. In the embodiment of the present invention, the demand prediction module 151, the candidate derivation module 153, the box configuration module 155, and the distribution processing module 157 will be described as being implemented in hardware, but not limited thereto, Each of the demand prediction module 151, the candidate derivation module 153, the box configuration module 155 and the allocation processing module 157 is stored in the storage unit 140 and is implemented as an application executed in the control unit 150 It is possible. The operation of the controller 150 including the demand prediction module 151, the candidate derivation module 153, the box configuration module 155 and the distribution processing module 157 will be described in more detail below.

Next, a description will be made of a method of distributing a product based on a production ratio of a product distribution system according to an embodiment of the present invention. 9 is a flowchart for explaining a method for distributing a product of the goods distribution system according to the embodiment of the present invention. In FIG. 9, it is assumed that the management server 100, the factory terminal 200, the warehouse terminal 300, and the store terminal 400 are linked with each other through a network. That is, each of the factory terminal 200, the warehouse terminal 300, and the store terminal 400 can be connected to the management server 100 via the network. Although the factory terminal 200, the warehouse terminal 300 and the store terminal 400 are shown one by one, the factory terminal 200, the warehouse terminal 300 and the store terminal 400 are representatively shown will be.

9, the store terminal 400 transmits the sales data to the management server 100 in step S110. This sales data includes the quantity per size of the merchandise sold for a predetermined period in the store where the store terminal 400 is disposed. The factory terminal 200 transmits the production amount data to the management server 100 in step S120. The yield data includes the amount of production by size of the commodity.

The management server 100 receiving the sales data and the production amount data predicts the demand of each store based on the sales data. Here, the demand is the quantity per size of the product that is expected to be sold in the store. In addition, the management server 100 derives a size production ratio based on the production amount data, and the size production ratio is a ratio of the quantity of each size of the goods produced in the factory. Then, the management server 100 obtains candidate classification boxes constituted by ratios of derived size production ratios and difference within a predetermined range among all kinds of classification boxes. Then, in step S130, the management server 100 derives a classification box type and a quantity that minimize the difference from the demand among the candidate classification boxes. At this time, the management server 100 can derive the classification box type and the quantity according to Equations (1) to (5).

Then, the management server 100 transmits the configuration of the classification box to the factory terminal 200 in step S140. Then, the factory terminal 200 displays the configuration of the classification box received in step S150 on the screen. Employees of the factory confirming the markings will package the goods produced according to the configuration of the classification box. In the factory, the items packed in the box will be shipped and put into the warehouse.

At this time, the management server 100 transmits the type and quantity of the classification box to the warehouse terminal 300 in step S160. Here, the type and quantity of the classified box depend on the demand of each store. Then, the warehouse terminal 300 displays on the screen the type and quantity of the classification box received in step S170. The staff of the warehouse will confirm the type and quantity of the sort box according to the demand of each store. As a result, one or more sorting boxes arranged according to the demand of each store in the warehouse will be delivered to each store.

We have discussed product distribution system. Then, in more detail, a description will be given of a method of distributing goods based on a production rate by the management server 100 of the goods distribution system. 10 is a flowchart for explaining a method for distributing a product of a management server according to an embodiment of the present invention.

Referring to FIG. 10, the demand prediction module 151 of the control unit 150 collects sales data from the store terminal 400 through the interface unit 110 in step S210. This sales data includes the quantity per size of the merchandise sold for a predetermined period in the store where the store terminal 400 is disposed. In step S220, the demand prediction module 151 may derive the expected demand of each store based on the sales data. Here, the demand is the quantity per size of the product that is expected to be sold in each store. For example, demand may be as shown in Table 1.

The candidate derivation module 153 of the control unit 150 collects the production amount data from the factory terminal 200 through the interface unit 110 in step S230. Such production data includes the amount of production by size of the commodity. Subsequently, the candidate derivation module 153 derives the size production ratio based on the production amount data in step S240. Here, the size production ratio is the ratio of the quantity of each product of the product produced in the factory. The above-described production amount and size production ratio per size may be as shown in Table 7. Then, the candidate derivation module 153 obtains the candidate classification box based on the size production ratio in step S250. Here, the candidate classification box refers to a classification box having a size production ratio among all kinds of classification boxes and a ratio having a difference within a predetermined range. For example, the candidate classification box is as shown in Table 8.

Next, in step S260, the box configuration module 155 of the control unit 150 sets parameters necessary for deriving the type and quantity of the classification box. These parameters include the minimum number of classification boxes distributed to each store, the maximum number of classification boxes distributed to each store, the maximum value of the classification box type, and the maximum number of classification boxes. The parameters may further include the number of stores for which classification boxes are to be provided, the maximum number of items that can be stored in one classification box, and the minimum number of items to be stored in one classification box. For example, when the user inputs the above-described parameters, the box configuration module 155 receives the parameters through the input unit 120 and sets the corresponding values according to the input parameters. As another example, the parameter may be stored in advance in the storage unit 140, and the box configuration module 155 may load the parameter stored in the storage unit 140 to set the corresponding value.

Subsequently, in step S270, the box configuration module 155 derives a classification box type and a quantity that minimize the difference from the demand predicted by the demand prediction module 151 among the candidate classification boxes derived by the candidate derivation module 153 . The box configuration module 155 can derive the types and quantity of classification boxes according to equations (1) to (5) as described above. The types and quantities of the classification boxes include the types and quantities of classification boxes required for the entire store as shown in Table 4 and the types and quantity of the classification boxes corresponding to the demand of each store as shown in Table 5.

The distribution processing module 157 of the control unit 150 transmits the type and quantity of the classification box to the factory terminal 200 through the interface unit 110 in step S280. For example, the types and the quantities of the classification boxes transmitted to the factory may be as shown in Table 4. Then, the factory terminal 200 displays the type and quantity of the received classification box on the screen, and the staff of the factory confirming the type and quantity of the classification box will package the produced goods according to the type and quantity of the classification box. In addition, the goods packed in the sort box will be shipped and put into the warehouse.

In step S290, the distribution processing module 157 transmits the type and quantity of the classification box corresponding to the demand of each store to the warehouse terminal 300. For example, the types and the quantities of the classification boxes transmitted to the warehouse terminal 300 may be in a format including Table 4 and Table 5. [ Then, the warehouse terminal 300 displays the type and quantity of the received classification box on the screen, and the staff of the warehouse that confirms the type and quantity of the classification box will arrange the type and quantity of the classification box according to the demand of each store. As a result, one or more sorting boxes arranged according to the demand of each store in the warehouse will be delivered to each store.

Meanwhile, the method for distributing a product according to the embodiment of the present invention may be implemented in a form of a program readable by various computer means and recorded in a computer-readable recording medium. Here, the recording medium may include program commands, data files, data structures, and the like, alone or in combination. Program instructions to be recorded on a recording medium may be those specially designed and constructed for the present invention or may be available to those skilled in the art of computer software. For example, the recording medium may be a magnetic medium such as a hard disk, a floppy disk and a magnetic tape, an optical medium such as a CD-ROM or a DVD, a magneto-optical medium such as a floppy disk magneto-optical media) and ROMs, RAMs, flash memory, and the like. Examples of program instructions may include machine language wires such as those produced by a compiler, as well as high-level language wires that may be executed by a computer using an interpreter or the like. Such a hardware device may be configured to operate as one or more software modules to perform the operations of the present invention, and vice versa.

According to the present invention, the types and quantity of the classification boxes provided to each store are determined according to the demand forecast, and the products produced in the factory are packaged and shipped using the determined types. Accordingly, the present invention does not require additional work of repackaging in the warehouse. Therefore, logistics costs can be saved. Moreover, because the distribution of goods through demand forecasting can not only reduce opportunity loss due to inadequate demand, but also reduce the loss of management overhead costs. Since the computation amount is reduced by using the candidate classification box, the operation speed can be improved and the work can be performed quickly.

While the present invention has been described with reference to several preferred embodiments, these embodiments are illustrative and not restrictive. It will be understood by those skilled in the art that various changes and modifications may be made without departing from the spirit of the invention and the scope of the appended claims.

100: management server 110:
120: input unit 130: display unit
140: storage unit 150: control unit
151: Demand prediction module 153: Candidate derivation module
155: box configuration module 157: distribution processing module
200: Factory terminal 300: Warehouse terminal
400: store terminal

Claims

A demand prediction module for predicting demand, which is a quantity per size of a product for each of a plurality of stores, when the size of the product is plural;
A plurality of types of goods having one or two or more kinds of sizes in one box are stored in a plurality of kinds of classification boxes having at least one of sizes of a plurality of commodities accommodated and quantities of sizes different from other boxes A candidate derivation module which obtains a plurality of types of candidate classification boxes, the plurality of types of candidate classification boxes each having a ratio of size production ratio and a difference within a predetermined range, ;
And when a product is distributed among the plurality of types of candidate classification boxes, a type and a quantity of a classification box having a configuration in which a difference between a quantity of each product and a quantity of each product according to the predicted demand of each of the plurality of stores is minimized Box configuration module;
An interface unit for communication; And
The type and the quantity of the classification boxes necessary for the entire store are displayed on the screen so that the types and quantity of the classification boxes necessary for the whole store are set so that the products produced at the factory are packed in accordance with the kinds and quantity of the classification boxes required for the whole store A distribution processing module for transmitting the data to a factory terminal through an interface unit;
And an outlet for dispensing the product.

The method according to claim 1,
The box configuration module
The type and quantity of the classification box are derived using the following equation,

N is the number of stores,
S is the number of sizes,
M is the maximum number of classification box configurable combinations,
I is the index of the store,
J is the index of the classification box,
K is an index of size,
remind

Is the demand for size k of store i,
remind

Is the number of the size k of the classification box j,
remind

Is the number of classification boxes (j) distributed to the store (i).

3. The method of claim 2,
The box configuration module
A minimum quantity of the sort box distributed to each of the stores,
A maximum number of sorting boxes distributed to each of the stores,
The maximum value of the kind of the classification box and
Limiting at least one of the maximum values of the quantities of the classification box
And the type and quantity of the classification box are derived.

delete

The method according to claim 1,
The distribution processing module
And the type and quantity of the sort box corresponding to the demand of each store are transmitted to the warehouse terminal through the interface unit so that the goods are distributed according to the demand of each store.

A method for distributing a product of a management server,
Predicting demand, which is a quantity per product size of each of a plurality of stores, when the size of the product is plural;
A plurality of products having one or two or more kinds of sizes are accommodated in one box having a configuration in which the size and the quantity of the goods are different from each other and at least one of the sizes of the stored plurality of goods and the quantity per size is different from the other box A plurality of types of candidate classification boxes are obtained from among a plurality of types of classification boxes having a configuration in which a size production ratio which is a ratio of a quantity of each size of a product produced in a factory to a ratio Obtaining a plurality of types of candidate classification boxes;
Deriving a type and a quantity of a classification box that minimizes a difference between a quantity of each product and a quantity of each product according to the predicted demand of each of the plurality of stores when distributing the product among the plurality of types of candidate classification boxes; And
The kind and quantity of the classification boxes necessary for the entire store are displayed on the screen so that the kinds and quantity of the classification boxes necessary for the whole store are supplied to the factory Transmitting to the terminal;
Lt; RTI ID = 0.0 > of: < / RTI >

The method according to claim 6,
The step of deriving
The type and quantity of the classification box are derived using the following equation,

Is the demand for size k of store i,
remind

Is the number of the size k of the classification box j,
remind

Is the number of classification boxes (j) distributed to the store (i).

The method according to claim 6,
The step of deriving
A minimum quantity of the sort box distributed to each of the stores,
A maximum number of sorting boxes distributed to each of the stores,
The maximum value of the kind of the classification box and
Limiting at least one of the maximum values of the quantities of the classification box
Wherein the type and quantity of the classification box are derived.

delete

The method according to claim 6,
After the step of deriving the kind and quantity of the classification box,
And transmitting to the warehouse terminal the type and quantity of the sort box corresponding to the demand of each store so that the goods are distributed according to the demand of each store.

A program for executing a method for distributing a product according to any one of claims 6, 7, 8, and 10.