Delivery support device

Abstract

This invention improves the loading efficiency of delivery vehicles replenishing goods to retail stores, reducing delivery vehicle shifts and thus helping to reduce labor hours for logistics personnel and greenhouse gas emissions. The delivery support device of this invention includes: a storage unit for storing trends in store inventory and sales volume for each store and for each product sold in that store; a storage unit for storing a first threshold related to store inventory and a second threshold greater than the first threshold for each product; a unit for calculating a predicted value of store inventory for each product after a specified period for a given store; a unit for extracting products with store inventory below the first threshold as first delivery candidate products; a unit for extracting products with predicted store inventory below the second threshold as second delivery candidate products; and a unit for processing delivery arrangements to deliver the first and second delivery candidate products to a store using a single vehicle.

Description

Technical Field

[0001] This invention relates to delivery technology for replenishing merchandise inventory in stores. Background Technology

[0002] To prevent stockouts of products sold in retail stores such as drugstores, inventory is managed. When inventory falls below a certain level, the product is shipped from the manufacturer, wholesaler, or the store's own warehouse to replenish the stock.

[0003] In this context, for example, Patent Document 1 proposes an order determination device that can prompt a quantitative benchmark for determining the appropriate order quantity when ordering goods, thereby verifying the reasonableness of the order quantity.

[0004] Existing technical documents Patent documents Patent Document 1: Japanese Patent Application Publication No. 2024-049832 Summary of the Invention

[0005] The technical problem that the invention aims to solve However, when replenishing goods to stores, vehicles equipped with loading platforms are used. But in the aforementioned prior art, delivery operations are carried out while there is still empty space on the loading platform, resulting in low vehicle utilization efficiency and the need to use a large number of vehicles.

[0006] Therefore, in view of the above problems, the present invention aims to provide a delivery support device that reduces the shifts of delivery vehicles by efficiently increasing the loading rate of delivery vehicles replenishing goods to retail stores, thereby helping to reduce the working hours of logistics-related personnel and reduce greenhouse gas emissions.

[0007] Technical solutions for solving technical problems One aspect of the delivery support device disclosed herein is characterized by comprising: a product information storage unit that stores trends in store inventory and sales volume for each store and for each product sold in that store; a delivery threshold storage unit that stores a first threshold related to the store inventory and a second threshold greater than the first threshold for each product; a first inventory prediction unit that, for one store, calculates a predicted value of the store inventory after a specified period for each product based on the information stored in the product information storage unit; a first candidate extraction unit that extracts products whose store inventory related to the store is lower than the first threshold as first delivery candidate products; a second candidate extraction unit that extracts products whose predicted store inventory related to the store is lower than the second threshold as second delivery candidate products; and a delivery unit that performs delivery arrangement processing to deliver the first delivery candidate products and the second delivery candidate products to the store using a single vehicle.

[0008] Invention Effects The delivery support device disclosed herein reduces the shifts of delivery vehicles by improving the loading rate of delivery vehicles that replenish goods to retail stores, thereby helping to reduce the working hours of logistics-related personnel and reduce greenhouse gas emissions. Attached Figure Description

[0009] Figure 1 This is a diagram illustrating the outline of the delivery support device in this embodiment.

[0010] Figure 2 This is a functional block diagram of the delivery support device in this embodiment.

[0011] Figure 3 This is a diagram illustrating an example of the hardware configuration of the delivery support device according to this embodiment.

[0012] Figure 4 This is a flowchart illustrating the processing flow of the delivery support device in this embodiment. Detailed Implementation

[0013] The embodiments for carrying out the present invention will be described with reference to the accompanying drawings.

[0014] (The working principle of the delivery support device in this embodiment) use Figure 1 and Figure 2 The working principle of the delivery support device (hereinafter referred to as "this device") 100 of this embodiment will be explained. Figure 1 This diagram shows the connection relationship between this device 100 and other devices. Figure 2 This is a functional block diagram of device 100.

[0015] like Figure 1 As shown, this device 100 is connected to the store terminal 370 via a communication network 380. The communication network 380 can be wired or wireless. The store terminal 370 is a device that notifies this device 100 of the sales and inventory status of the goods 240 sold in the store 210, such as a POS (Point of Sales) system.

[0016] like Figure 2 As shown, the device 100 includes: a product information storage unit 110, a delivery threshold storage unit 120, a nearby store storage unit 130, a first inventory prediction unit 140, a first candidate retrieval unit 150, a second candidate retrieval unit 160, a second inventory prediction unit 170, a third candidate retrieval unit 180, a spare space determination unit 190, and a delivery unit 200.

[0017] The product information storage unit 110 stores the store inventory 250 and the store sales trend 260 for each product 240 sold in the store 210. The store sales trend 260 includes, for example, the recent sales situation of each product 240, the seasonal characteristics of sales, and the weather-related characteristics of sales, which is the information needed to predict the future store inventory 250 of the products 240.

[0018] The delivery threshold storage unit 120 stores a first threshold 270 related to the store's inventory level 250 and a second threshold 280 greater than the first threshold 270 for each product 240 sold in store 210. Alternatively, the delivery threshold storage unit 120 can store the first threshold 270 and the second threshold 280 for each store 210. This approach addresses situations where the required store inventory level 250 or the trend 260 of store sales volume differs depending on the store 210.

[0019] The neighboring store storage unit 130 stores store grouping information 330 based on a predetermined criterion that groups stores 210. Here, the predetermined criterion includes concepts such as stores having the same delivery route or stores 210 having a distance of less than a predetermined value between them. In this way, it is possible to identify stores 210 that can efficiently deliver goods when using the same vehicle for delivery.

[0020] The first inventory forecasting unit 140, for a store 220, calculates a predicted value 290 for the future (after a specified period) store inventory 250 based on the information 250 and 260 stored in the product information storage unit 110, for each product 240. The predicted value 290 is, for example, the store inventory 250 after 3 days or 1 week. Furthermore, the predicted value 290 is calculated based on a common forecasting method, which is not particularly limited.

[0021] The first candidate extraction unit 150 extracts goods 240 whose store inventory 250 associated with a store 220 is lower than a first threshold 270 as first delivery candidate goods 300. This is the usual process for selecting goods 240 that should be replenished to a store 220.

[0022] The second candidate extraction unit 160 extracts goods 240 whose predicted store inventory value 290 associated with a store 220 is lower than the second threshold 280 as second delivery candidate goods 310. Furthermore, goods 240 extracted by the first candidate extraction unit 150 as first delivery candidate goods 300 are excluded from the second delivery candidate goods 310. This is the process of selecting goods whose store inventory 250 is still surplus compared to the first delivery candidate goods 300, but whose replenishment period is approaching (imminent delivery).

[0023] By unifying the delivery times of each item 240 as much as possible, the number of items 240 that can be carried in a single delivery vehicle 340 can be increased, thus reducing the number of delivery vehicles 340 in operation. This helps to reduce the working hours of logistics personnel and reduce greenhouse gas emissions associated with the operation of delivery vehicles 340.

[0024] The second inventory forecasting unit 170, for other stores 230, calculates a predicted value 290 for the future (after a specified period) store inventory 250 based on the information 250 and 260 stored in the product information storage unit 110, for each product 240. The predicted value 290 is, for example, the store inventory 250 3 days or 1 week later. Furthermore, the predicted value 290 is calculated based on a common forecasting method, which is not particularly limited.

[0025] The second inventory prediction unit 170 can also calculate the predicted value 290 of the store inventory 250 by considering other stores 230 belonging to the same group as a store 220 in the store grouping information 330 stored in the neighboring store storage unit 130. By screening other stores 230 as candidates from the perspective of logistics efficiency, the operating efficiency of the delivery vehicle 340 can be improved, thereby helping to reduce the labor time of logistics-related personnel and reduce greenhouse gas emissions accompanying the operation of the delivery vehicle 340.

[0026] The third candidate extraction unit 180 extracts the products 240 whose predicted value 290 of the store inventory 250 related to other stores 230 is lower than the second threshold 280 as the third delivery candidate products 320.

[0027] By unifying the delivery times of each item 240 as much as possible, the number of items 240 that can be carried in a single delivery vehicle 340 can be increased, thus reducing the number of delivery vehicles 340 in operation. This helps to reduce the working hours of logistics personnel and reduce greenhouse gas emissions associated with the operation of delivery vehicles 340.

[0028] The empty space determination unit 190 confirms and determines whether there is empty space 350 on the loading platform of a delivery vehicle 340 when the first delivery candidate product 300 and the second delivery candidate product 310 are loaded.

[0029] Furthermore, the spare space determination unit 190 confirms the size 360 ​​of the spare space on the delivery platform of a delivery vehicle 340 when the first delivery candidate item 300 and the second delivery candidate item 310 are loaded. And, if the spare space determination unit 190 can confirm that the size 360 ​​of the spare space is greater than the size of the third delivery candidate item 320, it determines that the third delivery candidate item 320 can be delivered by a delivery vehicle 340.

[0030] Delivery unit 200 performs delivery arrangement processing by using a delivery vehicle 340 to deliver the first delivery candidate item 300 and the second delivery candidate item 310 to a store 220. Alternatively, delivery unit 200 may also perform delivery arrangement processing by using a delivery vehicle 340 to deliver the third delivery candidate item 320 to other stores 230, in addition to the above processing.

[0031] By unifying the delivery times of various goods 240 or different stores 220 and 230 as much as possible, the number of goods 240 that can be carried in a single delivery vehicle 340 can be increased, thus reducing the number of delivery vehicles 340 in operation. This helps to reduce the working hours of logistics personnel and reduce greenhouse gas emissions associated with the operation of delivery vehicles 340.

[0032] In addition, the delivery unit 200 may also adopt a delivery arrangement process other than the above-mentioned process, in which the empty space determination unit 190 determines that there is empty space 350, and uses a delivery vehicle 340 to deliver the third delivery candidate product 320 to other stores 230.

[0033] In addition to the above processing, when the available space determination unit 190 determines that the third delivery candidate product 320 can be delivered by a delivery vehicle 340, the delivery unit 200 will perform a delivery arrangement process to deliver the third delivery candidate product 320 to other stores 230 using a delivery vehicle 340.

[0034] Based on the above working principle, this device 100 improves the loading efficiency of the delivery vehicle 340 that replenishes goods 240 to retail stores 210, thereby reducing the shifts of the delivery vehicle 340 and helping to reduce the working hours of logistics personnel and reduce greenhouse gas emissions.

[0035] (Hardware configuration of the delivery support device in this embodiment) use Figure 3 Here is an example of the hardware configuration of this device 100. Figure 3 This diagram illustrates an example of the hardware configuration of this device 100. (As shown...) Figure 3 As shown, the device 100 includes: CPU (Central Processing Unit) 510, ROM (Read-Only Memory) 520, RAM (Random Access Memory) 530, auxiliary storage device 540, communication I / F 550, input device 560, display device 570, and storage medium I / F 580.

[0036] CPU 510 is a device that executes the program stored in ROM 520. It processes the data expanded (loaded) in RAM 530 according to the program's instructions, controlling the entire device 100. ROM 520 stores the program and data executed by CPU 510. When CPU 510 executes the program stored in ROM 520, RAM 530 expands (loads) the program and data to be executed and temporarily holds the data during the computation.

[0037] The auxiliary storage device 540 is a device that stores the operating system (OS) as basic software, the application programs of this embodiment, and related data. For example, it includes a product information storage unit 110, a delivery threshold storage unit 120, and a nearby store storage unit 130. The auxiliary storage device 540 is, for example, an HDD (Hard Disk Drive) or flash memory.

[0038] The Communication I / F550 is an interface for connecting to wired / wireless LAN (Local Area Network), the Internet, and other communication networks 380, and for transmitting and receiving data with other devices (POS systems, etc.) 370 that provide communication functions.

[0039] Input device 560 is a device such as a keyboard that inputs data into device 100. Display device (output device) 570 is a device composed of LCD (Liquid Crystal Display) or the like, and functions as a user interface when the user uses the functions of device 100 or makes various settings. Storage medium I / F 580 is an interface for transmitting and receiving data with storage media 590 such as CD-ROM, DVD-ROM, and USB memory.

[0040] Each unit of the device 100 can also be implemented by the CPU 510 executing a program corresponding to each unit stored in the ROM 520 or the auxiliary storage device 540. Alternatively, each unit of the device 100 can be implemented by hardware processing related to each unit. Furthermore, the device 100 can execute the program by reading it from an external server device via communication I / F 550 or from storage medium 590 via storage medium I / F 580.

[0041] (A processing example of the delivery support device in this embodiment) use Figure 4 The processing example of this device 100 will be described. Figure 4 This is a flowchart illustrating the processing flow of this device 100.

[0042] In S10, the first candidate extraction unit 150 extracts goods 240 whose store inventory 250 associated with a store 220 is lower than a first threshold 270 as first delivery candidate goods 300. This is the usual process for selecting goods 240 that should be replenished to a store 220.

[0043] In S20, the first inventory prediction unit 140, for a store 220, calculates a predicted value 290 for the future (after a specified period) store inventory 250 based on the information 250 and 260 stored in the product information storage unit 110, for each product 240. The predicted value 290 is, for example, the store inventory 250 after 3 days or 1 week. Furthermore, the predicted value 290 is calculated based on a general prediction method, which is not particularly limited.

[0044] Furthermore, in S20, the second candidate extraction unit 160 extracts goods 240 whose predicted store inventory value 290 associated with a store 220 is lower than the second threshold 280 as second delivery candidate goods 310. Additionally, goods 240 extracted as first delivery candidate goods 300 in S10 are excluded from the second delivery candidate goods 310. This is the process of selecting goods whose store inventory 250 is still surplus compared to the first delivery candidate goods 300, but whose replenishment period is approaching (imminent delivery).

[0045] By unifying the delivery times of each item 240 as much as possible, the number of items 240 that can be carried in a single delivery vehicle 340 can be increased, thus reducing the number of delivery vehicles 340 in operation. This helps to reduce the working hours of logistics personnel and reduce greenhouse gas emissions associated with the operation of delivery vehicles 340.

[0046] In S30, the second inventory forecasting unit 170, for other stores 230, calculates a predicted value 290 for the future (after a specified period) store inventory 250 based on the information 250 and 260 stored in the product information storage unit 110, for each product 240. The predicted value 290 is, for example, the store inventory 250 after 3 days or 1 week. Furthermore, the predicted value 290 is calculated based on a common forecasting method, which is not particularly limited.

[0047] The second inventory prediction unit 170 can also calculate the predicted value 290 of the store inventory 250 by considering other stores 230 belonging to the same group as a store 220 in the store grouping information 330 stored in the neighboring store storage unit 130. By screening other stores 230 as candidates from the perspective of logistics efficiency, the operating efficiency of the delivery vehicle 340 is improved, which can help reduce the labor time of logistics-related personnel and reduce greenhouse gas emissions accompanying the operation of the delivery vehicle 340.

[0048] Furthermore, in S30, the third candidate extraction unit 180 extracts the goods 240 whose predicted value 290 of the store inventory 250 related to other stores 230 is lower than the second threshold 280 as the third delivery candidate goods 320.

[0049] By unifying the delivery times of each item 240 as much as possible, the number of items 240 that can be carried in a single delivery vehicle 340 can be increased, thus reducing the number of delivery vehicles 340 in operation. This helps to reduce the working hours of logistics personnel and reduce greenhouse gas emissions associated with the operation of delivery vehicles 340.

[0050] In S40, the empty space determination unit 190 confirms and determines whether there is empty space 350 on the loading platform of a delivery vehicle 340 when the first delivery candidate product 300 and the second delivery candidate product 310 are loaded.

[0051] Alternatively, in S40, the spare space determination unit 190 confirms the size 360 ​​of the spare space on the delivery platform of a delivery vehicle 340 when the first delivery candidate item 300 and the second delivery candidate item 310 are loaded. Furthermore, if the spare space determination unit 190 can confirm that the size 360 ​​of the spare space is greater than the size of the third delivery candidate item 320, it determines that the third delivery candidate item 320 can be delivered by a delivery vehicle 340.

[0052] In S50, the delivery unit 200 performs a delivery arrangement process that uses a delivery vehicle 340 to deliver the first delivery candidate item 300 and the second delivery candidate item 310 to a store 220. The delivery unit 200 may also perform a delivery arrangement process that uses a delivery vehicle 340 to deliver the third delivery candidate item 320 to another store 230, in addition to the above process.

[0053] Alternatively, in S50, in addition to the above processing, when it is determined in S40 that there is spare space 350, the delivery unit 200 may arrange to deliver the third delivery candidate product 320 to other stores 230 using a delivery vehicle 340.

[0054] As another approach, in addition to the above-mentioned processing, when it is determined in S40 that the third delivery candidate product 320 can be delivered by a delivery vehicle 340, the delivery unit 200 can arrange to deliver the third delivery candidate product 320 to other stores 230 using a delivery vehicle 340.

[0055] By unifying the delivery times of various goods 240 or different stores 220 and 230 as much as possible, the number of goods 240 that can be carried in a single delivery vehicle 340 can be increased, thus reducing the number of delivery vehicles 340 in operation. This helps to reduce the working hours of logistics personnel and reduce greenhouse gas emissions associated with the operation of delivery vehicles 340.

[0056] By performing the process described above, the device 100 reduces the shifts of the delivery vehicle 340 by making the loading rate of the delivery vehicle 340 that replenishes goods 240 to the retail store 210 more efficient, thereby helping to reduce the working hours of logistics personnel and reduce greenhouse gas emissions.

[0057] The embodiments of the present invention have been described in detail above, but the present invention is not limited to this specific embodiment. Various modifications and alterations can be made within the scope of the spirit of the present invention as set forth in the claims.

[0058] Explanation of reference numerals in the attached figures 100 Delivery Support Devices 110 Product Information Storage Unit 120 Delivery Threshold Storage Unit 130 neighboring store storage units 140 First Inventory Forecasting Unit 150 First Candidate Extraction Unit 160 Second Candidate Extraction Unit 170 Second Inventory Forecasting Unit 180 Third Candidate Extraction Unit 190 Empty Space Determination Unit 200 delivery units Shop 210 220 for a shop 230 Other Shops 240 products 250 Store Inventory 260 Store Sales Trends 270 First threshold 280 Second threshold 290 Forecast value of store inventory after the specified period 300 First Delivery Candidate Products 310 Second Delivery Candidate Items 320 Third-Party Delivery Candidate Products 330 Store Grouping Information 340 vehicles 350 cubicle empty space The size of the empty space on the 360° countertop 370 Store Terminal (POS (Point of Sales) System) 380 communication network 510 CPU 520 ROM 530 RAM 540 Auxiliary storage device 550 communication interface 560 Input Device 570 Output Device 580 Storage Media Interface 590 Storage medium.

Claims

1. A delivery support device, characterized in that, have: The product information storage unit stores the inventory and sales trends of each store and each product sold in that store. A delivery threshold storage unit, for each of the aforementioned products, stores a first threshold related to the store's inventory level and a second threshold greater than the first threshold; The first inventory prediction unit, for a given store, calculates a predicted value of the store's inventory after a specified period based on the information stored in the product information storage unit for each of the products. The first candidate extraction unit extracts the products associated with the store whose inventory is lower than the first threshold as the first delivery candidate products; The second candidate extraction unit extracts products whose predicted inventory value associated with the store is lower than the second threshold as second delivery candidate products; as well as The delivery unit performs delivery arrangement processing for delivering the first delivery candidate item and the second delivery candidate item to the store using a single vehicle.

2. The delivery support device according to claim 1, characterized in that, have: The second inventory prediction unit, based on the information stored in the product information storage unit, calculates the predicted inventory value of the store after a specified period for each of the other stores and for each of the products. as well as The third candidate extraction unit extracts products whose predicted inventory levels related to the other stores are lower than the second threshold as third delivery candidate products. The delivery unit performs delivery arrangement processing by using the vehicle to deliver the third delivery candidate product to the other stores.

3. The delivery support device according to claim 2, characterized in that, It has a neighboring store storage unit, which stores store information based on a predetermined benchmark that groups stores together according to the same delivery route or at a distance of less than a specified distance. The second inventory prediction unit calculates the predicted inventory value of the other stores that belong to the same group as the store in the store grouping information.

4. The delivery support device according to claim 3, characterized in that, The system includes a space determination unit that determines whether there is any space available on the loading platform of a vehicle when the first and second delivery candidate goods are loaded. When there is available space, the delivery unit will arrange for the third delivery candidate item to be delivered to the other stores using one of the vehicles.

5. The delivery support device according to claim 4, characterized in that, The spare space determination unit confirms the size of the spare space on the delivery platform. If it can be confirmed that the size of the spare space is greater than the size of the third delivery candidate item, it determines that the third delivery candidate item can be delivered. When a delivery unit is determined to be deliverable, it will arrange for the third delivery candidate item to be delivered to the other store using one of the vehicles.

6. A delivery support method, which is a delivery support method executed in a computer, the computer having: a product information storage unit that stores trends in store inventory and store sales for each store and for each product sold in that store; And a delivery threshold storage unit, which, for each of the aforementioned products, stores a first threshold related to the store's inventory level and a second threshold greater than the first threshold. The delivery support method is characterized by including: The first inventory prediction unit, for a given store, calculates the predicted inventory level of the store after a specified period based on the information stored in the product information storage unit for each of the products. The first candidate extraction unit extracts products whose inventory quantity in the store associated with the store is lower than the first threshold as first delivery candidate products; The second candidate extraction unit extracts products whose predicted inventory value for the store associated with the store is lower than the second threshold as second delivery candidate products; and The delivery unit performs the step of arranging a delivery of the first delivery candidate item and the second delivery candidate item to the store using a single vehicle.

7. The delivery support method according to claim 6, characterized in that, include: The second inventory prediction unit, for the other stores, calculates the predicted inventory value of the store after a specified period based on the information stored in the product information storage unit for each product. as well as The third candidate extraction unit extracts products whose predicted inventory value for the stores associated with the other stores is lower than the second threshold as third delivery candidate products. The delivery unit performs delivery arrangement processing by using the vehicle to deliver the third delivery candidate product to the other stores.

8. The delivery support method according to claim 7, characterized in that, The computer has a nearby store storage unit, which stores store grouping information based on a predetermined criterion, including stores with the same delivery route or located within a specified distance. The second inventory prediction unit calculates the predicted inventory value of the other stores that belong to the same group as the store in the store grouping information.

9. The delivery support method according to claim 8, characterized in that, include: The step of the spare space determination unit to determine whether there is spare space on the loading platform of a vehicle when the first delivery candidate item and the second delivery candidate item are loaded on the loading platform is a step of the vehicle's spare space determination unit. When there is available space, the delivery unit will arrange for the third delivery candidate item to be delivered to the other stores using one of the vehicles.

10. The delivery support method according to claim 9, characterized in that, The spare space determination unit confirms the size of the spare space on the delivery platform. If it can be confirmed that the size of the spare space is greater than the size of the third delivery candidate item, it determines that the third delivery candidate item can be delivered. When a delivery unit is determined to be deliverable, it will arrange for the third delivery candidate item to be delivered to the other store using one of the vehicles.

11. A delivery support procedure, characterized in that, Used to cause a computer to perform the method according to any one of claims 6 to 10.

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