JP6017693B2 - Distribution management apparatus, distribution management method, and distribution management program - Google Patents

Description

  The present invention relates to a logistics management apparatus, a logistics management method, and a logistics management program.

  Recently, a technique for managing the sales quantity and the inventory quantity of products in a store using a computer has been widely used. In addition, a technique for efficiently storing products in a warehouse using a computer is also widely used. From the standpoint of the store, it is a big concern how to maximize the sales volume of the product by holding a minimum inventory of products that does not cause a shortage. From the standpoint of the warehouse, it is of great concern how to achieve a series of operations of receiving, storing and shipping with the lowest cost, that is, with the minimum human and material resources.

  In Patent Literature 1, an inventory level at which a store must place an order for goods from a warehouse is defined as a “lower limit value”. The stock level immediately after placing an order is the “upper limit”. The ordering instruction system determines the lower limit value based on the sales performance of products and statistical theory so that no shortage occurs in the period until the products arrive at the store after ordering. And an upper limit is determined based on a lower limit and statistical theory. Further, when the inventory level falls below the lower limit, the recommended order quantity that is the difference between the inventory level and the upper limit is calculated.

JP 2007-200185 A (Claim 1 etc.)

  Ingenuity for avoiding shortages in stores using existing technologies, including the technology of Patent Document 1, maximizing sales volume, and reducing costs in warehouses is approaching its limit, and its effects are also saturated. It is becoming. In order to get out of this state and expect a further effect, for example, it is important that stores and warehouses, which are usually different management entities, can exchange information with each other. However, Patent Document 1 does not describe the cooperative relationship between the store and the warehouse, and a separate measure is required to establish such a cooperative relationship. And in order for other management entities that do not have the same interests to cooperate with each other, it is a major premise that economic benefits will arise in both parties. However, in the existing technology including the technology of Patent Document 1, there is no specific device for realizing a cooperative relationship that induces the enjoyment of such economic merit.

  Then, an object of this invention is to implement | achieve the cooperative relationship which invites enjoyment of an economic merit between a store and a warehouse.

The physical distribution management device of the present invention includes a data analysis unit that analyzes information related to products sold together based on time-series sales performance information related to sales of products in stores, and a plurality of types of products sold in stores. Based on the information on the storage location of the product in the warehouse where the product is stored and the information analyzed by the data analysis unit, the product is stored in the warehouse so that it is easy to pick the products that are sold together. A work review section that creates a review plan for location, and a calculation section that calculates the cost saved by applying the review plan to the warehouse based on the work performance information before the review in the warehouse and the work performance information after the review And.
Other means will be described in the embodiment for carrying out the invention.

  ADVANTAGE OF THE INVENTION According to this invention, it becomes possible to implement | achieve the cooperative relationship which invites enjoyment of an economic merit between a store and a warehouse.

It is a figure explaining the timing of arrival, shipment, and sale. (A), (b) and (c) is a figure explaining the layout etc. in a warehouse. (A) is a figure explaining the shelf in a warehouse. (B) is a figure explaining the cargo handling equipment in a warehouse. (A) And (b) is a figure explaining the example of arrangement | positioning of the goods in a warehouse. It is a figure explaining composition of a physical distribution management device etc. It is a figure which shows an example of POS information. (A) is a figure showing an example of WMS information. (B) is a figure showing an example of worker arrangement information. It is a figure which shows an example of work log information. It is a figure which shows an example of a work review plan. It is a figure which shows an example of a work review plan. (A), (b) and (c) is a figure explaining the relationship between environmental conditions and productivity. It is a flowchart of a work review processing procedure. It is a flowchart of an order review processing procedure. It is a flowchart of a procurement ratio determination processing procedure. It is a figure which shows an example of a simultaneous sale goods display screen. It is a figure which shows an example of a work review plan display screen. It is a figure which shows an example of a manual arrangement change screen. It is a figure which shows an example of a physical distribution display screen. (A), (b) and (c) is a figure explaining the input value etc. of a physical distribution network. It is a figure explaining the route etc. of a distribution network.

Hereinafter, a mode for carrying out the present invention (referred to as “the present embodiment”) will be described with reference to the drawings and the like. There are various cooperative relationships between stores and warehouses. In the present embodiment, the following is roughly assumed as a typical example.
(1) The warehouse analyzes POS (Point of Sales System) information and finds a plurality of products sold simultaneously. The warehouse proposes to sell these products in combination with the store, and further increases the sales quantity. In addition, the warehouse changes the arrangement of a plurality of products sold at the same time in the warehouse so that cargo can be handled efficiently.
(2) The store analyzes WMS (Warehouse Management System) information and places an order for goods at the point where productivity for cargo handling is expected to be improved, thereby further improving warehouse productivity.
(3) The store and the warehouse receive the consideration for providing information to the other party from the other party.

(Timing for shipping etc.)
The timing of arrival, shipment and sales will be described with reference to FIG. At a store, egg sand and orange juice are simultaneously sold at a certain time zone “t”. In particular, during the lunch hours, the sales volume peaks for both. The store wants to avoid the out-of-stock occurrence of both in that time zone. For this reason, the warehouse sets a time point that is “lead time” after the start time of the lunch time period as the time of shipment from the warehouse to the store. Furthermore, the warehouse sets the point in time that is required for “storage” from the time of shipment to the point of arrival from the manufacturer to the warehouse.

(Layout in the warehouse)
The layout in the warehouse will be described with reference to FIGS. As shown in the vertical sectional view of FIG. 2A, the warehouse has a plurality of floors. The first floor is a cargo area where trucks can go in and out, and the other floors are spaces for storing goods. And an elevator (EV) operates in the up-down direction. As shown in the horizontal cross-sectional view of FIG. 2B, shelves 411 to 484 for storing commodities are arranged in a grid pattern over 8 rows and 4 columns. Incidentally, the code | symbol "411" attached | subjected to the shelf has shown that the shelf is located in the 1st line 1st column of the 4th floor. The backs of the shelf 411 and the shelf 421 are in contact with each other. The same applies to the other shelves 412 and shelves 422. The shelf 421 and the shelf 431 are opposed to each other with one flow line (immediately described later) interposed therebetween. The same applies to the other shelves 422 and shelves 432 and the like. The arrangement of the shelves is exactly the same for the second and third floors.

  As shown in FIG. 2 (c), the worker picks up the goods from the shelves and stores them in the cart while pushing and moving the carts by hand, and transports the goods to the loading site via the elevator. This series of operations is generally called “picking”. In a narrower sense, only the operation of picking up a product and storing it in a cart may be called picking. The flow line through which the cart can pass is limited, and the flow line is indicated by a broken line in FIG. There are five flow lines in the horizontal direction in the figure and two in the vertical direction in the figure. The flow line in the left-right direction is called “street”, and the flow line in the vertical direction is called “strip”. Paying attention to the street, street 1 is between the wall and shelf in the first row, street 23 is between the shelf in the second row and shelf in the third row, ..., shelf and wall in the eighth row There is a street 8 in between. When attention is paid to the streak, the streak 1 exists between the wall surface and the first-row shelf, and the streak 4 exists between the fourth-row shelf and the elevator.

  As shown in FIG. 3A, each shelf has an upper level, a middle level, and a lower level, and each level uses an initial letter of the alphabet, It is called as “421U”. And this 421U etc. is also an identifier which specifies uniquely the storage position of goods in a warehouse. An example of picking is not limited to an example in which an operator performs picking while moving a cart. When handling a heavier product, the cargo handling facility may be a winch with a hook as shown in FIG. The worker stores and transports the goods in a pallet suspended from the hook.

  An example of the arrangement of products in the warehouse will be described with reference to FIG. For the sake of simplicity, it is assumed that the same product is stored in the upper, middle and lower stages of one shelf. It is assumed that the worker pushes the cart, picks the egg sand, picks the orange juice, then picks the orange juice, and then heads to the cargo area (1st floor). Now, the product arrangement is as shown in FIG. Then, the worker proceeds to the front of the shelf 421 via the street 23. The egg sand is picked from the shelf 421. Next, while pushing the cart, it proceeds to the front of the shelf 451 via the line 1 and the street 45. Then, pick orange juice from the shelf 451. Finally, proceed to the loading station via the elevator EV45 on the street 45 extension.

  As another example, assume that the arrangement of products is as shown in FIG. Then, the worker proceeds to the front of the shelf 421 via the street 23. The egg sand is picked from the shelf 421. Next, the orange juice is picked from the opposite shelf 431 without moving the cart. Next, the elevator EV 23 on the extension of the street 23 is advanced to the loading hall. Comparing the example of FIG. 4A and the example of FIG. 4B, the distance on the flow line where the worker and the cart move is clearly shorter in the example of FIG. 4B.

  The configuration of the physical distribution management device 1 will be described with reference to FIG. The distribution management device 1 is a general computer. The physical distribution management device 1 includes a central control device 11, an input device 12 such as a keyboard and a mouse, an output device 13 such as a display and a speaker, a main storage device 14, an auxiliary storage device 15, and a communication device 16. These are connected to each other by a bus. The data analysis unit 21, work review unit 22, consideration calculation unit 23, and procurement rate determination unit 24 in the main storage device 14 are programs. Thereafter, when the subject is described as “XX section”, the central control device 11 reads each program from the auxiliary storage device 15 and loads it into the main storage device 14, and then the function of each program (detailed later). Shall be realized. The auxiliary storage device 15 stores POS information 31, WMS information 32, worker arrangement information 33, and work history information 34 (details will be described later). The distribution management device 1 can be connected to the warehouse terminal device 2, the store management device 3, and the store terminal device 4 via the network 5. The “calculation unit” corresponds to the consideration calculation unit 23.

  The distribution management device 1 is disposed, for example, at the head office of a distribution company that operates a warehouse. The warehouse terminal device 2 is disposed, for example, at a site office in the warehouse. The store management device 3 is disposed, for example, at the head office of a distribution company that operates stores such as convenience stores. Store terminal device 4 is arranged in a store, for example.

The warehouse terminal device 2, the store management device 3, and the store terminal device 4 are also general computers. These devices include a central control device, an input device, an output device, a main storage device, an auxiliary storage device, and a communication device (not shown). The auxiliary storage device of the store management device 3 stores the POS information 31b and the POS information selection unit 25 as a program. The store terminal device 4 creates the POS information 31a. The POS information selection unit 25 of the store management device 3 receives the POS information 31a of each store from the store terminal device 4, and integrates and aggregates them to create the POS information 31b. Further, the POS information selection unit 25 creates POS information 31 by deleting unnecessary information from the POS information 31 b in response to a request from the data analysis unit 21 of the distribution management device 1, and transmits it to the distribution management device 1.
The auxiliary storage device of the warehouse terminal device 2 stores WMS information 32, worker arrangement information 33, and work history information 34. The warehouse terminal device 2 creates WMS information 32, worker arrangement information 33, and work history information 34 and transmits them to the distribution management device 1.

(POS information)
The POS information 31 will be described with reference to FIG. In the POS information 31, in association with the store ID stored in the store ID column 101, the product ID column 102 has a product ID, the product name column 103 has a product name, the sales unit price column 104 has a sales unit price, The sales number field 105 stores the sales number, the sales time field 106 stores the sales time, the transaction ID field 107 stores the transaction ID, and the set ID field 108 stores the set ID.

The store ID in the store ID column 101 is an identifier that uniquely identifies the store.
The product ID in the product ID column 102 is an identifier that uniquely identifies the product.
The product name in the product name column 103 is the name of the product.
The sales unit price in the sales unit price column 104 is the unit price (unit: yen) of the product.
The sales quantity in the sales quantity column 105 is the number of products sold in the transaction.
The point of sale in the point of sale column 106 is the year, month, day, hour, minute and second when the transaction occurs.
The transaction ID in the transaction ID column 107 is an identifier that uniquely identifies the transaction. The transaction ID may be a receipt number, for example.
The set ID in the set ID column 108 is an identifier that uniquely identifies the set. A plurality of different products may be combined into one package and used as one sales unit. This unit is called a “set”. When selling a set, a promotional campaign such as placing a prize such as a speed lottery in the package or doubling the purchase point of the purchase may be performed.

When the records of the POS information 31 (FIG. 6) are viewed in order from the top, the following can be understood.
(1) At the store “M001”, one egg sand and one orange juice are sold at the time “20130510 12:00:00”. The customer involved in the transaction may be, for example, a business person who came to buy lunch (lines 2 and 3).
(2) At the time point “20130510 19:00:00”, two squids and two canned beers are sold at the store. The customer involved in the transaction may be, for example, a business person after work (lines 5 and 6).
(3) At the point of time “20130510 23:00:00”, one cup fried noodle and one canned coffee are sold at the store. The customer related to the transaction may be, for example, an examinee who wants to change his mood (lines 8 and 9).
(4) A sales promotion campaign for selling the set “JJ01” was performed at the store at the time point “20130515”. The set includes 1 egg sand, 1 orange juice and speed lottery. On the same day, three sets are sold every minute from “12:00:00” (11th to 16th lines).

(WMS information)
The WMS information 32 will be described with reference to FIG. In the WMS information 32, in association with the storage position stored in the storage position column 111, the product ID column 112 stores the product ID, the product name column 113 stores the product name, and the storage quantity column 114 stores the storage quantity. Has been.
The storage position in the storage position column 111 is an identifier that uniquely specifies the storage position of the product in the warehouse.
The product ID in the product ID column 112 is the same as the product ID in FIG.
The product name in the product name column 113 is the same as the product name in FIG.
The storage quantity in the storage quantity column 114 is the quantity of goods stored at the storage position. The WMS information 32 statically indicates the storage state of the product at a certain point in time. The WMS information 32 is updated to the latest information every time the information content changes. A time point 115 indicates the latest update time point. The auxiliary storage device 15 may store not only the latest WMS information 32 but also past WMS information 32 (the same applies to the worker arrangement information 33 described later).

(Labor allocation information)
The worker arrangement information 33 will be described with reference to FIG. In the worker arrangement information 33, the street name is stored in the street column 122 and the number of workers is stored in the worker number column 123 in association with the floor name stored in the floor column 121.
The floor name in the floor column 121 is a number indicating the floor (floor) of the warehouse. The street name in the street column 122 is the name of the flow line in the left-right direction described above.
The number of workers in the number-of-workers column 123 is the number of workers to be arranged. The number of workers is defined for each combination of floor name and street name.
The worker arrangement information 33 is updated to the latest information every time the number of workers changes according to the busyness of the work. A time point 124 indicates the latest update time point.

(Work history information)
The work history information 34 will be described with reference to FIG. In the work history information 34, in association with the work ID stored in the work ID column 131, the work category column 132 has a work category, the product ID column 133 has a product ID, and the number column 134 has a number. The column 135 is the starting point, the via point column 136 is the via point, the end point column 137 is the end point, the distance column 138 is the distance, the total work time column 139 is the total work time, and the work time point column 140 is Is the work store time, and the contributing store ID column 141 stores the contributing store ID.

The work ID in the work ID column 131 is an identifier that uniquely identifies the work.
The work classification in the work classification column 132 is the type of work, and is one of “arrival”, “shipment”, and “relocation”. “Receiving” is an operation of bringing a product from a manufacturer into a warehouse. “Shipment” is an operation to carry out a product from a warehouse to a store. “Relocation” is an operation of moving products from one shelf in the warehouse to another.
The product ID in the product ID column 133 is the same as the product ID in FIG. Here, it is a product ID that specifies a plurality of products to be worked simultaneously. In the following, in order to simplify the description, an example in which two types of merchandise are to be worked simultaneously will be described in principle.
The number in the number column 134 is the number of each of a plurality of products to be worked.

  The product flow is expressed by a combination of a starting point, a waypoint, and an end point. For example, it is assumed that the work is “arrival” and the product “J001” and the product “J011” are the work targets. As an actual work, first, for example, the product “J001” and the product “J011” are carried from the manufacturer A to the loading site in the warehouse by a truck, and the product “J001” and the product “J011” are stored in the cart at the loading site. . Then, the cart is moved to the first shelf, and the product “J001” is transferred from the cart to the first shelf. Further, the cart is moved to the second shelf, and the product “J011” is transferred from the cart to the second shelf. This series of product flows is expressed as “starting point: manufacturer A, waypoint: identifier of first shelf, end point: identifier of second shelf”.

As another example, it is assumed that the work is “departure” and the same two types of products are to be worked. As an actual work, the product “J001” is stored in the cart from the first shelf. Then, the cart is moved to the second shelf, and the product “J011” is stored in the cart from the second shelf. The cart is moved to the cargo handling area, and the products “J001” and “J011” are transferred to a truck and carried out to, for example, the store “M001”. This series of merchandise flows is expressed as “starting point: identifier of first shelf, via point: identifier of second shelf, end point: M001”.
The starting point in the starting point column 135, the way point in the way point column 136, and the end point in the end point column 137 are the starting point, way point, and end point, respectively, of the above-described product flow.
The distance in the distance column 138 is the length (unit: m) on the flow line on which the cart moves with the product mounted.

  The total work time in the total work time column 139 is the total time (unit: time) spent by the worker to perform the work. A plurality of workers may be mobilized for one task. For example, the worker a may move the cart exclusively, and the worker b may exclusively pick the product from the shelf and store it in the cart. Also, worker a moves the cart exclusively, worker b exclusively picks the product from the shelf on one side of the flow line and stores it in the cart, and worker c exclusively picks the product from the shelf on the opposite side and stores it in the cart. It may be. When the work time is 7.5 minutes as a result of the mobilization of two workers for one work, the total work time is “0.25”. “0.25” is a calculation result of 7.5 minutes × 2 persons / 60.

The total work time is determined by various factors. The main factors are the number of product types, the number of products, the distance the cart has moved, and so on. Generally, the total work time increases as the number of types of products or the number of products increases. The total work time increases as the distance increases. Furthermore, environmental conditions in the warehouse such as temperature and humidity are factors that determine the total work time. As a result of the efficient movement of the worker's body and increased attention, it is desirable that the work be performed under environmental conditions that maximize productivity and minimize the probability of an accident (detailed below).
The work time point in the work time point column 140 is the year, month, day, hour, minute, and second when the work starts.
The contribution store ID in the contribution store ID column 141 is a store ID indicating for which store the work was performed.

(productivity)
“Productivity” is a value obtained by dividing the total number in the number field 134 by the total work time in the total work time field 139. Productivity can be defined for each operation. For example, the productivity of the work “W101” is calculated based on the record in the first line in FIG. The result is (150 + 100) /0.25=1,000. The highest value of the productivity of each work is called the maximum productivity value. Furthermore, productivity can also be defined for a group of consecutive operations. For the operations in the first to ninth lines in FIG. 8, the total number is “900” for “J001” and “600” for “J011”. The total work time is “1.95”. At this time, the productivity for the group of these nine operations is “769”. “769” is the calculation result of (900 + 600) /1.95. Thus, the productivity calculated for a group of a plurality of continuous operations is referred to as “productivity average value”.

With reference to the work history information 34 in FIG. 8 and FIG. 7A, the following can be understood.
-The goods sold in store "M001" are egg sand and orange juice.
The cart passes through the shelf “421U” and the shelf “451U”. Egg “sand” is stored in the shelf “421U”, and orange juice is stored in the shelf “451U”.
The distance is “30” m for all work.
The total work time is “0.25” for arrival and “0.20” for shipment.
・ One day, 18:00, 00 seconds, 150 and 100 pieces of egg sand and orange juice were received, and the next day and the next day, 13:00: 00, half of the shipments were repeated three times. ing.

(Work review proposal)
The work review plans 35a and 35b will be described with reference to FIGS. The work review unit 22 of the physical distribution management apparatus 1 creates work review plans 35a and 35b based on the work history information 34 (FIG. 8). The configuration of the work review plans 35a and 35b is the same as the work history information 34. However, in the work review plans 35a and 35b, as compared with the work history information 34, one of the work time points and the positions of the shelves as the start point, the via point, and the end point is reviewed. As a result, productivity is improved.

Attention is paid to the work review plan 35a of FIG. Compared with FIG. 8, the work review plan 35a is reviewed as follows.
In the “arrival” of the record in the first line, the end shelf where “J011” is stored has been changed to “431U”. The same applies to the records in the fourth and seventh rows. Both the shelf “421U” and the shelf “431U” face the street 23.
As a result, in the “shipment” records in the second and subsequent rows, the via point shelf for picking “J011” is changed to “431U”.
-As a result, in all work, the distance is shorter and the total work time is shorter. The productivity average value is improved from “769” to “1,162”.
・ The work time has been reviewed. That is, “150” and “100” of “J001” and “J011” are received at 09:00:00 on one day, respectively, and half are shipped at 10:00:00 on the same day and the next day. The work has been changed to be repeated three times. This review does not change productivity directly. However, the review plan in FIG. 9 in which goods are received and shipped immediately before the peak time when the product is sold is more desirable from the standpoint of the store.

  When there are many empty shelves, it is easy for the work review unit 22 to create a review plan 35a as shown in FIG. However, even if it is desired to change the storage position of a certain product from the first shelf to the second shelf, the second shelf may not be empty. In such a case, it is necessary to wait for the second shelf to become empty. Or, when an arbitrary third shelf becomes empty, the product stored in the second shelf is transferred to the third shelf, and then the certain product is transferred from the first shelf. It must be transferred to a second shelf that is empty.

The work review plan 35b in FIG. 10 is an example of such a so-called “ball repositioning”. Compared with FIG. 8, the work review plan 35b is reviewed as follows.
・ The work time has been reviewed. The contents are the same as in FIG.
The product “J002” is moved from the shelf “431U” to the shelf “4xxU” at the work time “20130512 09:30”. As a result, the shelf “431U” becomes empty. At the same time, the product “J011” is moved from the shelf “451U” to the shelf “431U”. The work classification of these work is “relocation”.

As a result, in the “shipment” record in the seventh and subsequent rows, the via point shelf for picking “J011” is changed to “431U”. In the record on the ninth line, the end shelf for storing “J011” is changed to “431U”.
-As a result, in the work after the seventh line, the distance is shorter and the total work time is shorter.
-Extra work time is generated due to work "relocation". However, the productivity average value is still improved from “769” (see FIG. 8) to “1,005”.

(Environmental condition)
The relationship between environmental conditions and productivity will be described with reference to FIG. The data analysis unit 21 can calculate the productivity at each work point from the work history information 34 (FIG. 8). Then, the data analysis unit 21 can create a productivity time series graph as shown in FIG. On the other hand, for example, the data analysis unit 21 accesses an external public database, acquires time-series information regarding environmental conditions, and from the acquired information (actual values in the near past), FIG. A time series graph like this can be created. The environmental conditions include, for example, natural conditions such as temperature, humidity, wind speed, atmospheric pressure, precipitation probability, sunshine duration, and concentration of any substance (dust, pollen, chemical substance, etc.) in the atmosphere at the warehouse location. Furthermore, the environmental conditions may include non-natural conditions such as noise and road congestion at the warehouse location.
Comparing the time series graphs of FIG. 11A and FIG. 11B, it can be seen that productivity is improved in a time zone where the temperature is above a certain level. Of course, the room temperature in the warehouse is different from the outside temperature. However, generally, the higher the outside temperature, the higher the room temperature.

The data analysis unit 21 creates a number of combinations of temperature and productivity at the same time, and plots the created combinations with a symbol “◯” on a two-dimensional plane with the temperature and productivity as coordinate axes (FIG. 11 (c )). Then, the following matters are clearly clarified.
• There is no significant correlation between temperature and productivity when the temperature is below Ta.
-When temperature is Ta or more and less than Tb, there is a positive correlation between temperature and productivity. In other words, productivity increases as the temperature rises.
-When temperature is Tb or more and less than Tc, there is a negative correlation between temperature and productivity. In other words, productivity decreases as the temperature rises.
• There is no significant correlation between temperature and productivity when the temperature is above “Tc”.

  The warehouse operator itself may not be aware of this correlation. Even if it is recognized, it is impossible to control the temperature in the first place. In addition, there are circumstances where work must be performed in an environment where productivity is low due to convenience of the store. If the cooperation of the store can be obtained and the work can be concentrated in an environment with high productivity, it is preferable for the warehouse (detailed later).

(Processing procedure)
Hereinafter, the processing procedure of this embodiment will be described. There are three processing procedures: an operation review processing procedure (FIG. 12), an order review processing procedure (FIG. 13), and a procurement ratio determination processing procedure (FIG. 14). The logistics management apparatus 1 executes a work review processing procedure in response to an operation of a logistics company user. The distribution management device 1 executes an order review processing procedure in response to a user operation of a distribution company. The procurement ratio determination processing procedure is a procedure for simulating the flow rate of goods for each route of a distribution network including a store in response to an operation of an arbitrary user. There is no anteroposterior relationship between the three procedures.

(Work review process procedure)
The work review processing procedure will be described with reference to FIG.
In step S301, the data analysis unit 21 of the physical distribution management apparatus 1 receives POS information. Specifically, the data analysis unit 21 first accepts that the user inputs the store ID of the store where the user wants to analyze the sales of the product via the input device 12. This store ID is hereinafter referred to as “analysis target store ID”. The following description will be continued on the assumption that the analysis target store ID is “M001”.
Second, the data analysis unit 21 transmits the analysis target store ID to the store management device 3. Then, the POS information selection unit 25 of the store management device 3 extracts a portion related to the analysis target store ID from the POS information 31 b and transmits it to the distribution management device 1 as the POS information 31. The transmitted POS information 31 is in a state as shown in the first to tenth lines in FIG. 6, for example.
Thirdly, the data analysis unit 21 receives the POS information 31 from the store management device 3.

In step S302, the data analysis unit 21 receives WMS information 32 and the like. Specifically, first, the data analysis unit 21 accesses the warehouse terminal device 2 and acquires WMS information 32 (FIG. 7A) and worker placement information 33 (FIG. 7B). As for the WMS information 32, all the information after the time point that is traced back from the present time by a predetermined period is acquired. As for the worker arrangement information 33, the current information is acquired.
Second, the data analysis unit 21 accesses the warehouse terminal device 2 and acquires a record having the analysis target store ID in the contribution store ID column 141 in the work history information 34 (FIG. 8). An example of the record of the work history information 34 acquired here is shown in FIG.

In step S303, the data analysis unit 21 identifies products that are simultaneously sold. Specifically, first, the data analysis unit 21 includes the sales point of time in the time zone having a predetermined length from the record of the POS information 31 (FIG. 6) received in “third” in step S301. Get all recorded records. The predetermined time zone is a time zone such as “00:00:00 to 01:00:00”, for example. The data analysis unit 21 can accept that the user sets a predetermined length in advance or can accept a change.
Second, the data analysis unit 21 totals the number of records sold in “first” in step S303 for each product ID.
Thirdly, the data analysis unit 21 obtains n combinations of the first to nth product IDs and the sales numbers counted in descending order of the total sales number in “second” in step S303. The value of n is not particularly limited, but the description will be continued below assuming that n = 2. The combinations acquired at this time are, for example, (product ID, number sold) = (J001, 30), (J011, 20).

  Fourthly, the data analysis unit 21 compares the sales value of the two combinations acquired in “third” in step S303 with a predetermined threshold value. If the smaller value of the sales numbers does not reach the threshold value, the two combinations are deleted. For example, when the threshold value is “15”, 20> 15, and therefore “(J001, 30), (J011, 20)” remains without being erased. The data analysis unit 21 can accept that the user sets a predetermined threshold in advance or can accept a change.

  The data analysis unit 21 changes the time zone of a predetermined length from “00: 00: 00: 00 to 01: 00: 0” → “01: 00: 00: 00 to 02: 00: 0” → “02: 00: 00: 00-03 After changing to “00:00”, the processing of “first” to “fourth” in step S303 is repeated. When the repetitive processing is completed, the data analysis unit 21 stores in the main storage device 14 (the time zone, the product ID with the largest sales quantity, the product ID with the second sales quantity, and the smaller value). A plurality of pieces of information such as (12:00:00 to 13: 00: 10: 00, J001, J011, 20) are temporarily held by time.

  Fifth, the data analysis unit 21 temporarily identifies the information held temporarily from the first to the pth, counting in descending order of the “number of sales with the smaller value”. Keep and erase what was not specified. The value of p is not particularly limited, but the description will be continued below assuming that p = 3. Here, the information held by the data analysis unit 21 is, for example, “(12:00: 00 to 13:00: 00, J001, J011, 20), (19:00: 00 to 20:00: 00, J002, J012, 18), (23: 00: 0 to 24: 00: 00: 00, J003, J013, 16) ".

  In step S304, the data analysis unit 21 displays products sold at the same time. Specifically, the data analysis unit 21 first displays the co-sale product display screen 51 (FIG. 15) on the output device 13. The co-sale product display screen 51 includes a store ID column 151, co-sale product name columns 152a, 152b, and 152c, and co-sale product time series graph columns 153a, 153b, and 154c. The data analysis unit 21 displays the analysis target store ID in the store ID column 151. The data analysis unit 21 displays the names and time zones of the products specified by the two product IDs in the information stored in “fifth” in step S303 in the simultaneously sold product name columns 152a, 152b, and 152c. The simultaneously sold product name column 152a of “No. 1” corresponds to “(12:00:00 to 13: 00: 00: 00, J001, J011, 20)” having the largest sales quantity. The “second-ranked” simultaneously sold product name field 152b corresponds to “(19:00:00 to 20: 00: J, J002, J012, 18)”. The “third place” co-sale product name field 152c corresponds to “((23: 00: 0 to 24: 00: 00: 00, J003, J013, 16)”.

  The data analysis unit 21 displays the time series graph for “J001” in the left part of the simultaneously sold product time series graph column 153a, and displays the time series graph for “J011” in the central part of the column 153a. . The data analysis unit 21 can create these time series graphs using the POS information 31 (FIG. 6). Furthermore, the data analysis unit 21 displays both time-series graphs on the same coordinate axis in the right part of the column 153a. Furthermore, among the overlapping parts of both time series graphs, the part belonging to the time zone displayed in the simultaneously sold product name column 152a is highlighted. The data analysis unit 21 displays “J002” and “J012” in the same time in the simultaneously sold product time series graph column 153b. The data analysis unit 21 displays “J003” and “J013” in the same time on the simultaneously sold product time series graph column 153c.

  Secondly, the data analysis unit 21 accepts that the user presses one of the recommended arrangement buttons in the simultaneously sold product name columns 152a, 152b, and 152c. Here, it is assumed that the recommended arrangement button in the “first place” co-sale product name field 152a has been pressed, and the explanation of egg sandwich and orange juice will be continued.

  In step S305, the work review unit 22 creates a work review plan. Specifically, the work review unit 22 creates a work review plan by partially correcting the work history information 34 (FIG. 8) acquired in “second” in step S <b> 302 according to the following conditions. . The creation of the work review plan includes the creation of the productivity average value and the productivity maximum value.

(Position condition 1) In the work review plan, the distance between the shelf where the egg sand is stored and the cargo handling area is shorter than the work history information 34.
(Position condition 2) In the work review plan, the distance between the shelf where orange juice is stored and the cargo handling area is shorter than the work history information 34.
(Position condition 3) In the work review plan, the distance between the shelf storing the egg sand and the shelf storing orange juice is shorter than the work history information 34.
(Position condition 4) In the work review plan, the street facing the shelf where the egg sand is stored coincides with the street facing the shelf where the orange juice is stored.
(Position condition 5) In the work review plan, the position of a product with a small number is changed, and the position of the other product is not changed. In the example of FIG. 8, there are 900 egg sands, while there are 600 orange juices. Therefore, the position of the orange juice is changed.

(Timing condition 1) In the work review plan, the shipping time = sales start time (12:00) −predetermined lead time.
(Timing condition 2) In the work review plan, the time of arrival = the time of shipment−the predetermined storage time.
(Timing condition 3) In the work review plan, if there is an empty shelf at the earliest arrival time that faces the shelf where one product is stored, The other product is received.
(Timing condition 4) In the work review plan, if there is no empty shelf at the earliest arrival time as the shelf where one product is stored faces, the other shelf will have the other shelf at that time. The goods arrive. After that, when an empty shelf is generated as described above, the other product is transferred from the previous shelf to the empty shelf.

  The work review unit 22 creates a predetermined number (for example, two) of work review plans that satisfy all of the position conditions 1 to 5 and the timing conditions 1 to 4 described above. There are cases where the conditions are too strict and the work review unit 22 cannot create a predetermined number of work review plans. In preparation for such a case, the work review unit 22 sets the priority between the position conditions 1 to 5 (first priority) and the priority between the timing conditions 1 to 4 (second priority). You may receive from a user beforehand. When such a case actually occurs, the work review unit 22 may exclude the position condition having the lowest first priority and / or the timing condition having the lowest second priority. Then, a work review plan is created again under relaxed conditions. If it is still not possible to create a predetermined number of work review proposals, the work review proposals are created again after relaxing the conditions. The work review unit 22 creates a work review plan that satisfies at least one position condition. In other words, the timing does not need to be reviewed, but the location must be reviewed to contribute to a direct improvement in productivity.

  In step S306, the work review unit 22 displays a work review plan. Specifically, the work review unit 22 first displays a work review plan display screen 52 (FIG. 16) on the output device 13. The work review plan display screen 52 includes target product columns 161 and 162, a current status column 163, a change plan 1 column 164, a change plan 2 column 165, confirmation buttons 166 and 167, and a manual change button 168. The work review unit 22 displays the names of two types of products (egg sand and orange juice) corresponding to the recommended placement button pressed in “second” in step S304 in the target product columns 161 and 162. Based on the WMS information 32 (FIG. 7A), the work review unit 22 displays a plan view near the shelf where the egg sand and orange juice are currently stored in the current status column 163. Then, the productivity average value and the productivity maximum value are calculated based on the work history information 34 (FIG. 8), and then displayed in the current status column 163. Next, the work review unit 22 changes the plan view near the shelf where the egg sand and orange juice are stored at the time after review based on the two work review plans created in step S305 and the change plan 1 column 164 and the change. Displayed in the plan 2 column 165. Then, the calculated productivity average value and productivity maximum value are also displayed in the change plan 1 column 164 and the change plan 2 column 165. Note that the “plan view” is described on the assumption that the same type of goods is stored in all the steps of the same shelf for the sake of simplicity.

  Secondly, the work review unit 22 accepts that the user presses any one of the confirmation buttons 166 and 167 and the manual change button 168. When the user approves the work review plan displayed in the change plan 1 column 164, the user presses the confirmation button 166. When the work review plan displayed in the change plan 2 column 165 is approved, the confirmation button 167 is pressed. If it is desired to manually create a work review plan without approving any work review plan, the manual change button 168 is pressed.

  In step S307, the work review unit 22 determines whether or not the confirmation button has been pressed. Specifically, when the user presses either the confirmation button 166 or the confirmation button 167 (step S307 “YES”), the work review unit 22 proceeds to step S309 and the user presses the manual change button 168. In the case (“NO” in step S307), the process proceeds to step S308.

  In step S308, the work review unit 22 receives a manual arrangement change. Specifically, the work review unit 22 displays the manual arrangement change screen 53 (FIG. 17) on the output device 13 and accepts that the user inputs a change instruction via the input device 12. When changing the storage position of a product that is already stored in the warehouse, the user first displays in the FROM column 173a of the rearrangement column 171 the shelf level on which the product that is symmetrical to the rearrangement is currently stored. Let Then, in the TO column 173b of the rearrangement column 171, the previous shelf stage where the product to be rearranged is to be transferred is displayed. Next, the user designates a product to be rearranged with the mouse in the FROM column 173a (reference numeral 174) and moves (drags) it to an arbitrary position in the TO column 173b. Finally, the user presses the OK button 175.

  When changing the storage position of a product at the time of arrival, the user first inputs a product ID for specifying a product for reviewing the shelf of the arrival destination in the product ID column 176 of the arrival column 172. In the receiving destination shelf column 177a, 177b, 177c,..., The position of the receiving destination shelf is input as “422”. In the example of FIG. 17, first, “422” is received. If “422” has no empty space, “423” is received. If “423” has no empty space, “422” is received. Show. Next, the user inputs the order of arrival in the same shelf in the vertical position column 178. In the example of FIG. 17, the user fills the received products in order from the top to the bottom, “top to bottom”, and vice versa, “bottom to top”, and randomly fills “random”. You can choose from home. Finally, the user presses the OK button 179.

  In step S309, the work review unit 22 transmits a work review instruction. Specifically, the work review unit 22 first transmits a work review instruction to the warehouse terminal device 2. The work review instruction corresponds to the confirmation button pressed in “second” in step S306 among the work review plans created in step S305, or the contents of the manual layout change accepted in step S308.

Secondly, the work review unit 22 modifies the worker arrangement information 33 (FIG. 7B) received in “first” in step S302 according to the following process.
(1) The work review unit 22 adds up the total work time of the work history information 34 (FIG. 8) for each “street” in which the work has occurred. In the example of FIG. 8, all work occurs on “street 23” and “street 45”. Therefore, the total value of the total work time is “0.975” for “street 23” and “0.975” for “street 45”. Incidentally, “0.975” is a value obtained by dividing “1.95” by “2”.

(2) It is assumed that the work review plan included in the work review instruction transmitted in “first” in step S309 is, for example, as shown in FIG. The work review unit 22 totals the total work time of the work review plan 35a for each street where the work has occurred. In the example of FIG. 9, all work occurs on street 23. Therefore, the total value of the total work time is “1.29” for “street 23” and “0” for “street 45”.
(3) The work review unit 22 calculates, for each street, a value obtained by subtracting the total value (actual value) of the total work time of the work history information from the total value (assumed value) of the total work time of the work review plan. The calculation result is 1.29−0.975 = 0.315 for “street 23”, and 0−0.975 = Δ0.975 for “street 45”.

(4) The work review unit 22 multiplies “0.315” and “Δ0.975” by a predetermined conversion coefficient, and calculates the number of review workers for each street. It is assumed that the number of review workers calculated here is “1” for “street 23” and “Δ2” for “street 45”.
(5) The work review unit 22 adds “1” to the number of workers “5” on the second line of the worker arrangement information 33 (FIG. 7B) and overwrites it. As a result, the number of workers is “6”. In addition, “Δ2” is added to the number of workers “5” on the third line and overwritten. As a result, the number of workers is “3”.
Thirdly, the work review unit 22 transmits the worker arrangement information 33 (excluding the time point 124) overwritten in “second” in step S309 to the warehouse terminal device 2. Thereafter, in the warehouse, the work time and the arrangement of the goods are reviewed according to the work review plan, and the number of workers and the arrangement of the workers are reviewed according to the changed worker arrangement information.

  In step S310, the consideration calculation unit 23 transmits a proposal for set sales. Specifically, the consideration calculation unit 23 transmits a proposal for set sales to the store management device 3. The proposal for set sales includes a product ID that identifies the two products displayed in the simultaneously sold product name column corresponding to the recommended placement button pressed in “second” in step S304.

  In step S311, the consideration calculation unit 23 confirms the effect. Specifically, the consideration calculation unit 23 receives a productivity improvement report from the warehouse terminal device 2 and receives a sales increase report from the store management device 3. The productivity improvement report shows that, for example, “Production average value of“ Tamago Sand ”and“ Orange Juice ”for the store“ M001 ”has improved by“ 393 ”. As a result, the distribution cost has been reduced by “5,000 yen”. As for the sales increase report, for example, “Tamago Sand” and “Orange Juice” were sold as a set at the store “M001”. As a result, the sales amount increased by “10,000 yen”. ].

  In step S312, the consideration calculation unit 23 calculates the consideration. Specifically, the consideration calculation unit 23 calculates the consideration for the store by multiplying “5,000 yen” in the productivity improvement report by the first reward coefficient. Generally, 0 <first reward coefficient <1. Further, the user may set the first reward coefficient so that the first reward coefficient increases as the amount of decrease in the distribution cost increases in order to increase the incentive for the store. Further, the first reward coefficient may be set such that the first reward coefficient increases as the increase in the sales amount increases. The consideration calculation unit 23 may calculate the consideration for the store without receiving the productivity improvement report from the warehouse terminal device 2. For example, the value obtained by multiplying the difference in productivity average value (“393”, which is the result of subtracting “769” in FIG. 8 from “1,162” in FIG. 9) as a consideration for the store Good.

  In step S313, the consideration calculation unit 23 settles the consideration. Specifically, the consideration calculation unit 23 transmits a settlement instruction to the financial institution server, and transmits a report to the store management apparatus 3 that the settlement instruction has been transmitted to the financial institution server. The settlement instruction is, for example, “Draw out 2,500 yen from the account in the name of our company (number yy) and deposit the same amount into the account in the name of XX store (number zz)”. Thereafter, the work review procedure ends.

(Order review processing procedure)
The order review processing procedure will be described with reference to FIG.
In step S <b> 351, the physical distribution management device 1 establishes communication with the store management device 3. Thereafter, a user of the store management device 3 (a user of a distribution company) can operate the distribution management device 1.

In step S352, the data analysis unit 21 of the physical distribution management apparatus 1 receives the work history information 34 (FIG. 8). Specifically, the data analysis unit 21 first accepts that the user inputs the analysis target store ID through the input device.
Second, the data analysis unit 21 accesses the warehouse terminal device 2 and acquires a record having the analysis target store ID in the contribution store ID column 141 in the work history information 34. An example of the record of the work history information 34 acquired here is shown in FIG.

  In step S353, the data analysis unit 21 receives external data. Specifically, the data analysis unit 21 accesses an arbitrary external public database and acquires time-series information regarding, for example, temperature, humidity, and the like. It is assumed that the information includes actual values in the near past and expected values in the near future.

  In step S354, the data analysis unit 21 investigates the relationship between external data and productivity. The details of the processing of the investigation have been described above with reference to FIG. Here, the data analysis part 21 shall acquire Ta, Tb, and Tc of FIG.11 (c) as a result.

In step S355, the work review unit 22 reviews the order quantity and the order point. Specifically, the work review unit 22 first displays, for example, the following information on the output device of the store management device 3 by an arbitrary method.
・ It is May 20 at present.
・ According to time series information on temperature, the expected temperature on May 21 (average during the day) is 15 ° C, the expected temperature on May 22 is 16 ° C, and the expected temperature on May 23 is The expected temperature on May 24 is 15 ° C.
Ta = 17 ° C., Tb = 20 ° C., Tc = 23 ° C.

The user is now thinking about the following.
-Originally, I would like to order 100 items from the warehouse at 9:00 on May 21 and receive them at the store at 17:00 on May 21. Furthermore, I would like to place an order for 100 items from the warehouse at 9:00 on May 24 and receive them at the store at 17:00 on May 24. Note that “a certain product” may be anything. However, the user is assumed to be “Issip Day” (product ID is “Jxxx”).
・ Orders for goods may be concentrated on May 23 in the sense of cooperating in improving warehouse productivity.
Secondly, the work review unit 22 should deliver 200 ordering instructions “200 products“ Jxxx ”to the store“ M001 ”at 8:00 on May 23rd. ”Is accepted.

  In step S356, the work review unit 22 transmits an ordering instruction. Specifically, the work review unit 22 transmits to the warehouse terminal device 2 the ordering instruction received in “second” in step S355.

  In step S357, the consideration calculation unit 23 confirms the effect. Specifically, the consideration calculation unit 23 receives a productivity improvement report from the warehouse terminal device 2 and receives a sales increase report from the store management device 3. The productivity improvement report, for example, “200 products“ Jxxx ”were shipped to the store“ M001 ”at 7:00 on May 23rd. As a result, logistics costs have been reduced by "2,000 yen". The sales increase report is, for example, “200 products“ Jxxx ”were sold out on May 23rd. There were no unsold items or missing items, and the ordering work was saved once. As a result, the total amount of increase in sales amount and reduction in store operating costs was “20,000 yen”.

  In step S358, the consideration calculation unit 23 calculates the consideration. Specifically, the consideration calculating unit 23 calculates the consideration for the warehouse by multiplying “20,000 yen” in the sales increase report by the second reward coefficient. Generally, 0 <second reward coefficient <1. Furthermore, the user may set the second reward coefficient so that the second reward coefficient increases as the amount of decrease in the distribution cost increases. In addition, the second reward coefficient may be set such that the second reward coefficient increases as the total amount of the increase in sales amount and the reduction in store operation cost increases. The consideration calculation unit 23 may calculate the consideration for the store without receiving a sales increase report from the warehouse terminal device 2. For example, an amount obtained by multiplying a fixed amount by the number of times an order instruction different from the previous pattern is accepted may be used as a consideration for the warehouse.

  In step S359, the consideration calculation unit 23 settles the consideration. The processing in step S359 is the same as the processing in step S313 of the work review processing procedure. Thereafter, the order review procedure is terminated.

(Logistics network)
In general, a product passes through many economic agents (players) before reaching a consumer. It is possible to grasp a lot of routes until a product reaches a consumer as a network composed of links between a plurality of nodes. Then, in order to minimize the overall cost and / or the overall time required for logistics, it can be determined what ratio the flow rate of each route should be set. Furthermore, it is possible to know how the ratio changes when external factors such as temperature change.

The logistics network will be described with reference to FIG. A distribution network 55 is displayed on the distribution display screen 54. The players related to logistics are production (1), wholesale (2), retail (3), store (4), consumer (5), overseas (6) and net (7). The net (7) is a virtual store on the Internet. These players are shown at nodes 181-187. A directed line segment connecting two nodes is called a link. The direction of the link indicates the direction in which the product flows. The thickness of the link indicates the amount (product flow rate) through which the product flows. The numbers in parentheses attached to the players of each node, for example, “1” for “production”, “2” for “wholesale”, “3” for “retail”, etc. are codes indicating the respective players. is there.
It is up to the user to decide what kind of “product” is to be made and what kind of shape the physical distribution network is to be made.

(About players and warehouses)
These players, except for the store (4) and the consumer (5), each have a warehouse and have inventory. In this sense, each of these players corresponds to the “warehouse” described before FIG. That is, it can be said that the distribution network 55 of FIG. 18 embodies the player who owns the warehouse by extending the mutual use of information by the warehouse and the store to the entire flow of goods.

(Link, cost, flow rate and time required)
Cost, flow rate and time required are defined for one link. For example, C12 is a cost (unit: yen) when goods are distributed from production (1) to wholesale (2). P12 is the quantity (unit: piece) of goods distributed from production (1) to wholesale (2). T12 is a required time (unit: hour) when goods are distributed from production (1) to wholesale (2). More generally, Cij is a cost when a product is distributed from the node “i” to the node “j”. Pij is the amount of the product distributed from the node “i” to the node “j”. Tij is the time required for the product to circulate from the node “i” to the node “j”.

(Route, total cost and total time required)
A route is a set of a plurality of continuous links. The most common route is “production (1) → wholesale (2) → retail (3) → store (4) → consumer (5)”. This route is referred to as a route “12345”. Of course, there may be a route of “production (1) → wholesale (2) → retail (3) → net (7) → consumer (5)”. This route is called route “12375”. Furthermore, there may be a route “overseas (6) → consumer (5)”. This route is called route “65”. The node that is the starting point of the route is either production (1) or overseas (6). The node that is the end point of the route is always the consumer (5).

  A total cost is defined for one route. The total cost is the sum of the costs of the links included in the route. For example, the total cost of the route “12345” is C12 + C23 + C34 + C45 (column 233 in the first line in FIG. 20). The total required time is defined for one route. The total time required is the sum of the time required for the links included in the route. For example, the total required time of the route “12345” is T12 + T23 + T34 + T45 (column 234 on the first line in FIG. 20).

(Input value, output value and parameters)
The procurement ratio determination unit 24 of the physical distribution management apparatus 1 is a program that functions a mathematical model that outputs an “output value” described later when an input of an “input value” described later is received.
The input values are the demand amount, the transportation cost, the tariff rate, the time / price priority ratio, the temperature, the necessity of delivery on the day, and the net usage described in the column 201 of FIG. These input values are displayed with symbols in the column 202 and have units in the column 203. However, on-the-day delivery necessity and net use are not used in the mathematical formula, so there is no corresponding symbol. The same-day delivery necessity and net use assume a value of “Yes” or “No”.
The output values are the procurement ratios “r1” to “r8” for each route described in the column 232 of FIG. The relationship r1 + r2 +... + R8 = 1 is established.

  The mathematical model includes a plurality of parameters. The parameters are a required time, an inventory coefficient, a system cost, and an import cost described in the column 211 of FIG. These parameters are displayed with symbols in column 212 and have units in column 213. The user can arbitrarily set the values of these parameters.

Of the parameters, for the required time, the value of the required time can be set for each link, reflecting the actual distance between the nodes as in T12 and T23, for example.
Among the parameters, the inventory safety factor (SE) will be described prior to describing the inventory coefficient (SEE). For a certain player, the ratio of the number of products flowing from the player at the immediately preceding node to the number of products flowing to the player at the immediately following node is defined. This ratio is called the inventory safety factor (SE) and is usually larger than “1”. In the mathematical model of this embodiment, the inventory safety factor (SE) for all players is the same value.
The inventory coefficient (SEE) is a coefficient for calculating an inventory safety factor (SE). The relationship “SE = SEE × TE” is established among the inventory safety factor (SE), the inventory coefficient (SEE), and the temperature (TE).

  The mathematical model further includes a cost calculation formula (column 226 in FIG. 19C) and a physical flow rate calculation formula (column 236 in FIG. 20). The standard cost calculation formula is “cost = material flow rate × required time × transportation cost” (columns 223 to 226 in the first to fourth lines in FIG. 19C). However, when the player who supplies the product is “overseas”, the cost calculation formula is “cost = material flow rate × (1 + tariff rate) × import cost” (FIGS. 19C, 5, 6, 10). Lines 223, 224, 226). It is assumed that the tariff rate is equal to the tariff amount / import cost. Further, when the player who supplies or receives the product is “net”, the cost calculation formula is “cost = material flow rate × required time × (transportation cost + system cost)” (7 in FIG. 19C). -9th column 223-226).

The material flow rate calculation formula is “material flow rate = procurement ratio × demand amount × inventory safety factor” for the link at the end of the route. For the other links, “material flow rate = physical flow rate of the link immediately after the current × stock safety factor” (columns 235 and 236 in FIG. 20).
The distribution network 55 in the example of FIG. 18 has eight routes (column 231 in FIG. 20). In addition, r1 to r8 correspond to the respective routes. Referring to the record in the first row in FIG. 20, it can be seen that r1 corresponds to the route “12345”. Suppose now that demand = 100 and r1 = 0.25. This is because, firstly, the consumer (5) needs 100 items, and secondly, the consumer (5) has a demand amount × r1 = 100 × 0.25 = 25 items. Is acquired (purchased) via the route “12345”.

  The user can know how the output values r1 to r8 change each time after changing the input values variously. Further, it is possible to know how the thickness of the link indicating the flow rate between nodes and the total value (total cost) of the total cost of each route change.

(Procurement rate determination procedure)
The procurement rate determination processing procedure will be described with reference to FIG. It is assumed that the distribution network 55 has been completed prior to the start of the procurement ratio determination processing procedure.
In step S381, the procurement rate determination unit 24 of the physical distribution management apparatus 1 receives parameters. Specifically, the procurement rate determination unit 24 accepts that the user inputs the value of each parameter in FIG. 19B via the input device 12.
In step S382, the procurement rate determination unit 24 displays the physical distribution display screen 54 (FIG. 18) on the output device 13.

  In step S383, the procurement rate determination unit 24 receives an input value. The user grasps the upper side of the shaded bars of the demand display box 188, the tariff rate input box 189, the air temperature input box 192, the transportation cost input box 193 and the time / price priority ratio input box 194 on the distribution display screen 54 with the mouse. Enter the demand amount, tariff rate, temperature, transportation cost and time / price priority ratio respectively. Further, the user presses the “Yes” button or the “No” button in the net use input box 190 and the same day delivery necessity input box 191, respectively to input the presence / absence of necessity of the net use and the same day delivery.

  In step S384, the procurement ratio determination unit 24 generates an arbitrary procurement ratio. The procurement ratio is “r1, r2,..., R8”. However, r1 + r2 +... + R8 = 1. It is assumed that the procurement ratio determination unit 24 generates these values at random.

  In step S385, the procurement ratio determination unit 24 calculates the overall cost and the like. Specifically, the procurement ratio determination unit 24 calculates the total cost and / or the total time required for the physical distribution network 55 using input values, parameters, cost calculation formulas, and physical flow rate calculation formulas. The total cost is the sum of the total costs of all the rows in the column 233 of FIG. The total time required is the sum of the total time required for all rows in column 234 of FIG.

  However, when the necessity of delivery on the day of the input value is “Yes”, the procurement rate determination unit 24 ignores routes whose total required time is longer than a predetermined time (for example, 12 hours). When the net usage of the input value is “none”, the procurement ratio determination unit 24 ignores the route in which “net” is included in the node. The time / price priority ratio “q”, which is an input value, takes a value of 0 ≦ q ≦ 1. When q = 1 (prioritizing time), the procurement ratio determining unit 24 calculates only the total required time. When q = 0 (priority is given to the price), the procurement ratio determination unit 24 calculates only the total cost. When 0 <q <1, the procurement ratio determination unit 24 calculates a blend value “total cost × (1−q) + total required time × q × v”. v is a conversion coefficient for converting time into cost. Further, instead of using the conversion factor, the procurement ratio determination unit 24 may normalize the total cost and the total required time to numerical values in the same range and add the values to the blend value. The total cost, the total required time and the blend value are collectively referred to as “total cost etc.”.

  The procurement ratio determination unit 24 repeats the processes of steps S384 and S385 a predetermined number of times after generating another procurement ratio (inner loop). At the stage of exiting the inner loop, the procurement ratio determination unit 24 temporarily holds the combination of the procurement ratio and the total cost, the same number as the number of repetitions.

  In step S386, the procurement rate determination unit 24 determines an optimal procurement rate. Specifically, the procurement ratio determination unit 24 specifies a combination having the smallest overall cost, etc., from among the temporarily held combinations. At this time, the procurement ratio of the specified combination is “(r1, r2,..., R8) = (0.5, 0.1,..., 0.1)”, and the overall cost is , "1,000,000 yen".

In step S387, the procurement rate determination unit 24 displays the material flow rate and the overall cost. Specifically, the procurement ratio determination unit 24 first displays “1,000,000 yen” in the overall cost etc. column 195 of the physical distribution display screen 54.
Secondly, the procurement ratio determination unit 24 determines the link of each link based on the flow rate calculated in the processing of the inner loop where the procurement ratio is “0.5, 0.1,..., 0.1”. Calculate the material flow rate. For example, the flow rate between the store (4) and the consumer (5) is the sum of P45 on the route “12345”, P45 on the route “62345”, and P45 on the route “6345” (FIG. 20). 1, 4, 6).
Thirdly, the procurement ratio determining unit 24 displays each link with a thickness proportional to the sum of the material flow rates. Naturally, for the store (4), the consumer (5) wants to avoid receiving goods directly from the overseas (6) or the net (7) without going through the store (4).

  When the procurement rate determination unit 24 accepts that the user presses the recalculation button 196, the procurement rate determination unit 24 returns to step S383, accepts other input values, and repeats the processing of steps S383 to S387 (outer loop). When the procurement rate determination unit 24 accepts that the user inputs an instruction to end the processing, the procurement rate determination unit 24 exits from the outer loop and ends the procurement rate determination processing procedure.

(Effect of this embodiment)
(1) The warehouse can improve productivity by the POS information obtained from the store. The store may receive a consideration disclosing POS information to the warehouse.
(2) By using the work history information obtained from the warehouse, the store can place an order for products focusing on the time when productivity is improved in the warehouse. The warehouse may receive a consideration disclosing work history information to the store.
(3) The store can increase the number of products sold by receiving a proposal for set sales from the warehouse.
(4) The warehouse can change the number of workers and the arrangement of workers in the warehouse according to the POS information obtained from the store.
(5) By accepting a change in threshold value used when specifying simultaneously sold products, such products can be specified in detail according to the busyness of transactions.
(6) The store can simulate the state in which the product flows from overseas or the Internet to the consumer without going through the store.

In addition, this invention is not limited to an above-described Example, Various modifications are included. For example, the above-described embodiments have been described in detail for easy understanding of the present invention, and are not necessarily limited to those having all the configurations described. Further, a part of the configuration of one embodiment can be replaced with the configuration of another embodiment, and the configuration of another embodiment can be added to the configuration of one embodiment. Further, it is possible to add, delete, and replace other configurations for a part of the configuration of each embodiment.
Each of the above-described configurations, functions, processing units, processing means, and the like may be realized by hardware by designing a part or all of them with, for example, an integrated circuit. Each of the above-described configurations, functions, and the like may be realized by software by interpreting and executing a program that realizes each function by the processor. Information such as programs, tables, and files that realize each function can be stored in a recording device such as a memory, a hard disk, or an SSD (Solid State Drive), or a recording medium such as an IC card, an SD card, or a DVD.
In addition, the control lines and information lines are those that are considered necessary for the explanation, and not all the control lines and information lines on the product are necessarily shown. In practice, it may be considered that almost all the components are connected to each other.

DESCRIPTION OF SYMBOLS 1 Logistics management apparatus 2 Warehouse terminal apparatus 3 Store management apparatus 4 Store terminal apparatus 5 Network 11 Central control apparatus (control part)
12 Input device 13 Output device 14 Main storage device (storage unit)
15 Auxiliary storage device (storage unit)
DESCRIPTION OF SYMBOLS 16 Communication apparatus 21 Data analysis part 22 Work review part 23 Consideration calculation part 24 Procurement ratio determination part 25 POS information selection part 31, 31a, 31b POS information 32 WMS information 33 Worker arrangement information 34 Work history information 35a, 35b Work review plan 51 Simultaneous sale product display screen 52 Work review plan display screen 53 Manual layout change screen 54 Logistics display screen

Claims (10)

A data analysis unit that analyzes information about products sold together based on time-series sales performance information related to product sales at stores;
Based on information on the storage position of the product in a warehouse that stores a plurality of types of products sold in the store, and information analyzed by the data analysis unit, picking between the products sold together A work review unit that creates a review plan for the storage location of the product in the warehouse, so that the work is facilitated;
A calculation unit that calculates a cost saved by a result of applying the review plan to the warehouse based on work result information before the review in the warehouse and work result information after the review;
A logistics management apparatus comprising: The data analysis unit
Accept time series information of environmental conditions of the warehouse,
Investigate the correlation between the time series information of productivity in the warehouse and the time series information of the accepted environmental conditions,
The work review department
Based on the result of the investigation, an instruction to change the time when the store orders the product to the warehouse to the time when the productivity is improved is sent to the warehouse,
The calculation unit includes:
Calculating the consideration paid to the warehouse from the sales amount of the product increased as a result of changing the time when the store places the order;
The physical distribution management apparatus according to claim 1. The calculation unit includes:
Based on the information on the products sold together analyzed by the data analysis unit, sending a proposal to sell a plurality of products sold in a specific time zone as a set to the store;
The physical distribution management device according to claim 2, wherein: The work review department
Sending to the warehouse a proposal to change the number of workers and the placement of workers in the warehouse;
The physical distribution management device according to claim 3. The data analysis unit
Accepting a change in the threshold used to identify the product sold together,
The physical distribution management device according to claim 4. The physical distribution management device
Accepts input values including the presence or absence of virtual stores and the tariff rate on the inflow of the product from overseas,
Determining a ratio at which a consumer's demand for the product is distributed to a plurality of routes in the logistics network so as to minimize the cost of the entire logistics network including the store;
A procurement ratio determining unit that displays on the output device the cost of the entire minimized distribution network and the distribution amount of the goods between economic entities in the distribution network;
The physical distribution management device according to claim 5. The data analysis department
Based on time-series sales performance information on product sales at stores, we analyze information on products sold together,
The work review department
Based on information on the storage position of the product in a warehouse that stores a plurality of types of products sold in the store, and information analyzed by the data analysis unit, picking between the products sold together To make work easier, create a review plan for the storage location of the product in the warehouse,
The calculation unit
Calculating the cost saved by the result of applying the review plan to the warehouse based on the work result information before the review in the warehouse and the work result information after the review,
A logistics management method for a logistics management apparatus comprising the data analysis unit, the work review unit, and the calculation unit. The data analysis unit
Accept time series information of environmental conditions of the warehouse,
Investigate the correlation between the time series information of productivity in the warehouse and the time series information of the accepted environmental conditions,
The work review department
Based on the result of the investigation, an instruction to change the time when the store orders the product to the warehouse to the time when the productivity is improved is sent to the warehouse,
The calculation unit includes:
Calculating the consideration paid to the warehouse from the sales amount of the product increased as a result of changing the time when the store places the order;
The logistics management method according to claim 7. For the data analysis unit of the logistics management device,
Based on the time-series sales performance information related to product sales at the store, execute processing to analyze information related to products sold together,
For the work review department of the logistics management device,
Based on information on the storage position of the product in a warehouse that stores a plurality of types of products sold in the store, and information analyzed by the data analysis unit, picking between the products sold together In order to facilitate the work, execute a process of creating a review plan regarding the storage position of the product in the warehouse,
For the calculation unit of the logistics management device,
Executing a process of calculating a cost saved by a result of applying the review plan to the warehouse based on work result information before the review and work result information after the review in the warehouse;
A logistics management program for causing the logistics management apparatus to function. For the data analysis unit,
Accept time series information of environmental conditions of the warehouse,
A process for investigating the correlation between the time series information of productivity in the warehouse and the time series information of the received environmental conditions;
For the work review department,
Based on the result of the survey, the store executes an instruction to change the time when the store orders the product to the warehouse to the time when the productivity is improved, and sends the warehouse.
For the calculation unit
Causing the store to calculate a consideration paid to the warehouse from the sales amount of the product increased as a result of changing the ordering time;
The logistics management program according to claim 9.

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