Delivery support device
The delivery support device enhances vehicle utilization and reduces emissions by aligning delivery timings and maximizing cargo space, thereby decreasing the number of vehicles needed for store inventory replenishment.
Patent Information
- Authority / Receiving Office
- JP · JP
- Patent Type
- Applications
- Current Assignee / Owner
- D4ALL CO LTD
- Filing Date
- 2024-12-18
- Publication Date
- 2026-06-30
AI Technical Summary
Conventional delivery systems for replenishing store inventory suffer from low vehicle utilization efficiency, leading to a high number of vehicles being used and increased greenhouse gas emissions.
A delivery support device that optimizes the loading rate of delivery vehicles by using product information storage, inventory forecasting, and candidate extraction means to align delivery timings and maximize cargo space utilization.
Reduces the number of delivery vehicles and associated labor hours while minimizing greenhouse gas emissions by optimizing the loading rate of delivery vehicles.
Smart Images
Figure 2026106937000001_ABST
Abstract
Description
Technical Field
[0001] It relates to a delivery technology when replenishing the inventory of goods to a store.
Background Art
[0002] In retail stores such as drugstores, the inventory of goods sold is managed so that the goods displayed and sold at the storefront do not run out of stock. When the inventory level drops below a certain amount, the goods are shipped from the manufacturer, wholesaler, or company's own warehouse, etc., and the storefront goods are replenished.
[0003] Under such circumstances, for example, in Patent Document 1, when placing an order for goods, an order determination device that can present a quantitative criterion for determining an appropriate order quantity and verify the validity of the order quantity has been proposed.
Prior Art Documents
Patent Documents
[0004]
Patent Document 1
Summary of the Invention
Problems to be Solved by the Invention
[0005] However, when replenishing goods to a store, a vehicle equipped with a loading platform for goods is used. In the above - mentioned conventional technology, since the delivery work is carried out with empty space remaining on the loading platform, the utilization efficiency of the vehicle is low, and there is a problem that a large number of vehicles need to be used. (
[0006] Therefore, in view of the above problems, the present invention aims to provide a delivery support device that contributes to reducing the labor time of people involved in logistics and reducing the emission of greenhouse gases by improving the loading rate of the loading platform of a delivery vehicle for replenishing goods to a retail store, thereby reducing the number of delivery vehicles.
Means for Solving the Problems
[0007] One form of the disclosed delivery support device is characterized by comprising: product information storage means for storing store inventory levels and store sales trends for each store and each product sold at that store; delivery threshold storage means for storing a first threshold and a second threshold greater than the first threshold for each product regarding the store inventory level; first inventory level forecasting means for calculating an estimated value of the store inventory level after a predetermined period for each product based on the information stored in the product information storage means for one of the stores; first candidate extraction means for extracting products for which the store inventory level for one of the stores falls below the first threshold as first delivery candidate products; second candidate extraction means for extracting products for which the estimated value of the store inventory level for one of the stores falls below the second threshold as second delivery candidate products; and delivery means for performing delivery arrangement processing to deliver the first delivery candidate products and the second delivery candidate products to one of the stores using one vehicle. [Effects of the Invention]
[0008] The disclosed delivery support device aims to reduce the number of delivery vehicles by optimizing the loading rate of delivery vehicles that replenish goods at retail stores, thereby contributing to a reduction in the working hours of people involved in logistics and a reduction in greenhouse gas emissions. [Brief explanation of the drawing]
[0009] [Figure 1] This diagram illustrates the overview of the delivery support device according to this embodiment. [Figure 2] This is a functional block diagram of the delivery support device according to this embodiment. [Figure 3] This figure shows an example of the hardware configuration of the delivery support device according to this embodiment. [Figure 4] This flowchart shows an example of the processing flow by the delivery support device according to this embodiment. [Modes for carrying out the invention]
[0010] The embodiments for carrying out the present invention will be described with reference to the drawings. (Operating principle of the delivery support device according to this embodiment)
[0011] The operating principle of the delivery support device (hereinafter simply referred to as "this device") 100 according to this embodiment will be explained using Figures 1 and 2. Figure 1 is a diagram showing the connection relationship between this device 100 and other devices, and Figure 2 is a functional block diagram of this device 100.
[0012] As shown in Figure 1, the device 100 is connected to the store terminal 370 via a communication network 380. The communication network 380 may be either wired or wireless. The store terminal 370 is a device that informs the device 100 of the sales status and inventory status of the products 240 sold at the store 210, and may be, for example, a POS (Point of Sales) system.
[0013] As shown in Figure 2, the device 100 includes a product information storage means 110, a delivery threshold storage means 120, a nearby store storage means 130, a first inventory quantity prediction means 140, a first candidate extraction means 150, a second candidate extraction means 160, a second inventory quantity prediction means 170, a third candidate extraction means 180, a vacant space determination means 190, and a delivery means 200.
[0014] The product information storage means 110 stores the store inventory quantity 250 and the store sales volume trend 260 for each product 240 sold at the store 210. The store sales volume trend 260 includes, for example, the recent sales performance, seasonal characteristics of sales volume, and weather-related characteristics of sales volume for each product 240, and is information necessary to predict the future store inventory quantity 250 of product 240.
[0015] The delivery threshold storage means 120 stores a first threshold 270 and a second threshold 280 greater than the first threshold 270 for each product 240 sold at the store 210, relating to the store inventory quantity 250. Alternatively, the delivery threshold storage means 120 may store the first threshold 270 and the second threshold 280 for each store 210. This allows for handling cases where the store inventory quantity 250 to be held and the trends in store sales volume 260 differ from store to store 210.
[0016] The neighboring store memory means 130 stores store grouping information 330 that groups stores 210 based on a predetermined criterion. Here, the predetermined criterion is a concept including that the delivery routes are the same and the distance between stores 210 is less than or equal to a predetermined value. By doing so, when delivering using the same vehicle, it is possible to know stores 210 to which goods can be efficiently delivered.
[0017] The first inventory quantity prediction means 140 calculates, for each product 240, a predicted value 290 of the future (after a predetermined period) store inventory quantity 250 for a single store 220 based on the information 250 and 260 stored in the product information storage means 110. The predicted value 290 is, for example, the store inventory quantity 250 three days later or one week later. Also, the predicted value 290 is calculated based on a general prediction method, and the prediction method is not particularly limited.
[0018] The first candidate extraction means 150 extracts products 240 for which the store inventory quantity 250 for a single store 220 is less than the first threshold value 270 as first delivery candidate products 300. This is a general process for selecting products 240 to be replenished in a single store 220.
[0019] The second candidate extraction means 160 extracts products 240 for which the predicted value 290 of the store inventory quantity for a single store 220 is less than the second threshold value 280 as second delivery candidate products 310. Note that products 240 extracted as first delivery candidate products 300 by the first candidate extraction means 150 are excluded from the second delivery candidate products 310. This is a process for selecting products that still have a margin in the store inventory quantity 250 compared to the first delivery candidate products 300 but whose product replenishment time is near (will be delivered soon).
[0020] In this way, if the delivery timings for each product 240 are made as uniform as possible, the number of products 240 that can be loaded onto a single delivery vehicle 340 increases, and as a result, the number of operating vehicles of the delivery vehicle 340 can be reduced. This can also contribute to reducing the labor time of people involved in logistics and reducing the emissions of greenhouse gases emitted during the operation of the delivery vehicle 340.
[0021] The second inventory prediction means 170 calculates, for each product 240, a predicted value 290 of the future (after a predetermined period) store inventory quantity 250 for other stores 230 based on the information 250, 260 stored in the product information storage means 110. The predicted value 290 is, for example, the store inventory quantity 250 three days later or one week later. Also, the predicted value 290 is calculated based on a general prediction method, and the prediction method is not particularly limited.
[0022] The second inventory prediction means 170 may be configured to calculate a predicted value 290 of the store inventory quantity 250 for other stores 230 belonging to the same group as a certain store 220 in the store group classification information 330 stored in the neighboring store storage means 130. By narrowing down the candidates for other stores 230 from the perspective of logistics efficiency, the operating efficiency of the delivery vehicle 340 can be improved, and this can also contribute to reducing the working hours of people involved in logistics and reducing the emissions of greenhouse gases emitted during the operation of the delivery vehicle 340.
[0023] The third candidate extraction means 180 extracts, as the third delivery candidate products 320, the products 240 for which the predicted value 290 of the store inventory quantity 250 for other stores 230 is below the second threshold value 280.
[0024] In this way, if the delivery timings for each product 240 are made as uniform as possible, the number of products 240 that can be loaded onto one delivery vehicle 340 increases, and as a result, the number of operating delivery vehicles 340 can be reduced. This can also contribute to reducing the working hours of people involved in logistics and reducing the emissions of greenhouse gases emitted during the operation of the delivery vehicle 340.
[0025] The free space determination means 190 checks and determines whether there is a free space 350 on the loading platform when the first delivery candidate products 300 and the second delivery candidate products 310 are loaded on the loading platform of a certain delivery vehicle 340.
[0026] Furthermore, the available space determination means 190 checks the size 360 of the available space on the cargo bed of one delivery vehicle 340 when the first delivery candidate product 300 and the second delivery candidate product 310 are loaded onto the cargo bed. If the available space determination means 190 can confirm that the size 360 of the available space is larger than the size of the third delivery candidate product 320, it determines that the third delivery candidate product 320 can be delivered by the delivery vehicle 340.
[0027] The delivery means 200 performs a delivery arrangement process to deliver the first delivery candidate product 300 and the second delivery candidate product 310 to one store 220 using one delivery vehicle 340. Furthermore, in addition to the above process, the delivery means 200 may also perform a delivery arrangement process to deliver the third delivery candidate product 320 to another store 230 using one delivery vehicle 340.
[0028] In this way, by aligning the delivery timings for every 240 items or for different stores (220, 230), the number of items that can be loaded onto a single delivery vehicle (340) increases, which in turn reduces the number of delivery vehicles (340) in operation. This contributes to reducing the working hours of people involved in logistics and to reducing greenhouse gas emissions associated with the operation of delivery vehicles (340).
[0029] Furthermore, in addition to the above processing, the delivery means 200 may also perform a delivery arrangement process to deliver the third delivery candidate product 320 to another store 230 using a single delivery vehicle 340 if the available space determination means 190 determines that there is available space 350.
[0030] In addition to the above processing, the delivery means 200 also performs a delivery arrangement process to deliver the third delivery candidate product 320 to another store 230 using the same delivery vehicle 340 if the available space determination means 190 determines that the third delivery candidate product 320 can be delivered using one delivery vehicle 340.
[0031] Based on the operating principle described above, this device 100 aims to reduce the number of delivery vehicles 340 that replenish goods 240 at retail stores 210 by optimizing the loading rate of the delivery vehicles 340, thereby contributing to a reduction in the working hours of people involved in logistics and a reduction in greenhouse gas emissions. (Hardware configuration of the delivery support device according to this embodiment)
[0032] An example of the hardware configuration of the device 100 will be explained using Figure 3. Figure 3 is a diagram showing an example of the hardware configuration of the device 100. As shown in Figure 3, the device 100 has a 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.
[0033] The CPU 510 is a device that executes programs stored in the ROM 520. It processes data loaded into the RAM 530 according to program instructions and controls the entire device 100. The ROM 520 stores the programs and data that the CPU 510 will execute. When the CPU 510 executes a program stored in the ROM 520, the RAM 530 loads the programs and data to be executed and temporarily holds the calculation data during the calculation.
[0034] The auxiliary storage device 540 is a device that stores the operating system (OS), which is the basic software, and application programs related to this embodiment, along with related data, and includes, for example, product information storage means 110, delivery threshold storage means 120, and nearby store storage means 130. The auxiliary storage device 540 is, for example, an HDD (Hard Disk Drive) or flash memory.
[0035] The communication interface 550 is an interface for exchanging data with other devices (such as POS systems) 370 that provide communication functions, by connecting to a communication network 380 such as a wired or wireless LAN (Local Area Network) or the Internet.
[0036] The input device 560 is a device for inputting data into the main device 100, such as a keyboard. The display device (output device) 570 is a device consisting of an LCD (Liquid Crystal Display) or the like, and functions as a user interface for the user to use the functions of the main device 100 and to make various settings. The storage medium I / F 580 is an interface for sending and receiving data with storage media 590 such as CD-ROMs, DVD-ROMs, and USB memory.
[0037] Each of the means of this device 100 may be realized by the CPU 510 executing a program corresponding to each means stored in the ROM 520 or auxiliary storage device 540. Alternatively, each of the means of this device 100 may be realized by the processing related to each means being implemented as hardware. Furthermore, the program according to the present invention may be read from an external server device via a communication I / F 550, or read from a storage medium 590 via a storage medium I / F 580, and the device 100 may execute the program. (Example of processing by the delivery support device according to this embodiment) An example of processing performed by this device 100 will be explained using Figure 4. Figure 4 is a flowchart showing the flow of processing performed by this device 100.
[0038] In S10, the first candidate extraction means 150 extracts products 240 for which the store inventory quantity 250 for a particular store 220 falls below the first threshold 270 as the first candidate products 300 for delivery. This is a general process for selecting products 240 to be replenished in a particular store 220.
[0039] In S20, the first inventory quantity forecasting means 140 calculates a forecast value 290 for the future (after a predetermined period) store inventory quantity 250 for each product 240 with respect to a single store 220, based on the information 250 and 260 stored in the product information storage means 110. The forecast value 290 is, for example, the store inventory quantity 250 three days or one week later. Furthermore, the forecast value 290 is calculated based on a general forecasting method, and the forecasting method is not particularly limited.
[0040] Furthermore, in S20, the second candidate extraction means 160 extracts products 240 as second delivery candidate products 310, where the estimated store inventory quantity 290 for one store 220 is below the second threshold 280. Note that product 240, which was extracted as the first delivery candidate product 300 in S10, is excluded from the second delivery candidate products 310. This is a process to select products that still have more leeway in store inventory quantity 250 than the first delivery candidate product 300, but whose replenishment time is approaching (will be delivered soon).
[0041] In this way, by aligning the delivery timing of each 240-pack of goods as much as possible, the number of 240 items that can be loaded onto a single delivery vehicle 340 increases, and as a result, the number of delivery vehicles 340 in operation can be reduced. This contributes to reducing the working hours of people involved in logistics and to reducing greenhouse gas emissions associated with the operation of delivery vehicles 340.
[0042] In S30, the second inventory quantity forecasting means 170 calculates a forecast value 290 for the future (after a predetermined period) store inventory quantity 250 for each product 240 with respect to other stores 230, based on the information 250 and 260 stored in the product information storage means 110. The forecast value 290 is, for example, the store inventory quantity 250 three days or one week later. Furthermore, the forecast value 290 is calculated based on a general forecasting method, and the forecasting method is not particularly limited.
[0043] The second inventory quantity forecasting means 170 may also calculate an estimated value 290 for store inventory quantity 250 for other stores 230 that belong to the same group as one store 220 in the store grouping information 330 stored in the nearby store memory means 130. By narrowing down the candidates for other stores 230 from the perspective of logistics efficiency, the operational efficiency of delivery vehicles 340 can be improved, thereby contributing to a reduction in the working hours of people involved in logistics and a reduction in greenhouse gas emissions associated with the operation of delivery vehicles 340.
[0044] Furthermore, in S30, the third candidate extraction means 180 extracts products 240 as third delivery candidate products 320 whose estimated store inventory quantity 250 for other stores 230 is below the second threshold 280.
[0045] In this way, by aligning the delivery timing of each 240-pack of goods as much as possible, the number of 240 items that can be loaded onto a single delivery vehicle 340 increases, and as a result, the number of delivery vehicles 340 in operation can be reduced. This contributes to reducing the working hours of people involved in logistics and to reducing greenhouse gas emissions associated with the operation of delivery vehicles 340.
[0046] In S40, the available space determination means 190 checks and determines whether there is available space 350 on the cargo bed of a delivery vehicle 340 when the first delivery candidate product 300 and the second delivery candidate product 310 are loaded onto the cargo bed.
[0047] Alternatively, in S40, the available space determination means 190 checks the size 360 of the available space on the cargo bed of one delivery vehicle 340 when the first delivery candidate product 300 and the second delivery candidate product 310 are loaded onto the cargo bed. If the available space determination means 190 confirms that the size 360 of the available space is larger than the size of the third delivery candidate product 320, it determines that the third delivery candidate product 320 can be delivered by the first delivery vehicle 340.
[0048] In S50, the delivery means 200 performs a delivery arrangement process to deliver the first delivery candidate product 300 and the second delivery candidate product 310 to one store 220 using one delivery vehicle 340. In addition to the above process, the delivery means 200 may also perform a delivery arrangement process to deliver the third delivery candidate product 320 to another store 230 using one delivery vehicle 340.
[0049] Alternatively, in S50, if it is determined that there is available space 350 in S40, the delivery means 200 may perform a delivery arrangement process to deliver the third delivery candidate product 320 to another store 230 using a single delivery vehicle 340, in addition to the above processing.
[0050] In an alternative configuration, if the delivery means 200 determines in S40 that the third delivery candidate product 320 can be delivered by a single delivery vehicle 340, it performs a delivery arrangement process to deliver the third delivery candidate product 320 to another store 230 using the same delivery vehicle 340.
[0051] In this way, by aligning the delivery timings for every 240 items or for different stores (220, 230), the number of items that can be loaded onto a single delivery vehicle (340) increases, which in turn reduces the number of delivery vehicles (340) in operation. This contributes to reducing the working hours of people involved in logistics and to reducing greenhouse gas emissions associated with the operation of delivery vehicles (340).
[0052] By performing the above-described processing, the device 100 aims to reduce the number of delivery vehicles 340 that replenish goods 240 at retail stores 210 by optimizing the loading rate of the delivery vehicles 340, thereby contributing to a reduction in the working hours of people involved in logistics and a reduction in greenhouse gas emissions.
[0053] Although embodiments of the present invention have been described in detail above, the present invention is not limited to these specific embodiments, and various modifications and changes are possible within the scope of the gist of the present invention as described in the claims. [Explanation of symbols]
[0054] 100 Delivery support equipment 110 Product information storage means 120 Delivery threshold storage means 130 Nearby Store Memory 140 First Inventory Forecasting Method 150 First candidate extraction means 160 Second candidate extraction means 170 Second Inventory Forecasting Method 180 Third candidate extraction means 190. Means for determining available space 200 Means of delivery 210 stores 220 store 230 other stores 240 products Inventory at 250 stores Trends in sales volume at 260 stores 270 First threshold 280 Second threshold 290 Estimated store inventory levels after a specified period 300 1st delivery candidate product 310 2nd delivery candidate product 320 3rd delivery candidate product 330 Store Group Classification Information 340 vehicles 350 available space in the cargo area 360 The size of the available space in the cargo bed 370 store terminals (POS (Point of Sales) systems) 380 Communication Networks 510 CPU 520 ROM 530 RAM 540 Auxiliary storage 550 Communication Interfaces 560 Input Device 570 Output device 580 Storage Media Interface 590 Storage medium
Claims
1. A product information storage means that stores the store inventory volume and the trends in store sales volume for each store and for each product sold at that store, A delivery threshold storage means that stores a first threshold related to the store inventory quantity and a second threshold greater than the first threshold for each of the aforementioned products, With respect to one of the aforementioned stores, a first inventory quantity forecasting means calculates an estimated value for the store's inventory quantity after a predetermined period based on the information stored in the product information storage means, A first candidate extraction means for extracting products as first delivery candidate products for which the store inventory quantity for the aforementioned store falls below the first threshold, A second candidate extraction means for extracting products as second delivery candidate products for which the estimated value of the store inventory for the first store falls below the second threshold, A delivery support device characterized by having a delivery means that performs delivery arrangement processing for delivering the first delivery candidate product and the second delivery candidate product to the one store using one vehicle.
2. With respect to other stores, a second inventory quantity forecasting means calculates an estimated value for the store inventory quantity after a predetermined period based on the information stored in the product information storage means for each product, The system includes a third candidate extraction means for extracting products as third delivery candidate products for which the estimated value of the store inventory for the other stores falls below the second threshold, The delivery support device according to claim 1, characterized in that the delivery means performs a delivery arrangement process to deliver the third delivery candidate product to the other store using the one vehicle.
3. The system has a nearby store storage means that stores store grouping information, which is obtained by grouping the stores based on predetermined criteria, including having the same delivery route or being located within a predetermined distance. The delivery support device according to claim 2, characterized in that the second inventory quantity forecasting means calculates an estimated value of the store inventory quantity with respect to the other stores that belong to the same group as the first store in the store grouping information.
4. The vehicle has a means for determining available space on its cargo bed when the first and second delivery candidate products are loaded onto the cargo bed, The delivery support device according to claim 3, characterized in that the delivery means performs a delivery arrangement process to deliver the third delivery candidate product to the other store using the one vehicle when there is available space.
5. The empty space determination means checks the size of the empty space on the cargo bed, and if it can confirm that the size of the empty space is larger than the size of the third candidate product for delivery, it determines that the third candidate product for delivery can be delivered. The delivery support device according to claim 4, characterized in that, when the delivery means is determined to be deliverable, it performs a delivery arrangement process to deliver the third delivery candidate product to the other store using the one vehicle.
6. A delivery support method performed on a computer comprising: product information storage means for storing store inventory levels and sales trends for each store and each product sold at that store; and delivery threshold storage means for storing a first threshold and a second threshold greater than the first threshold for each product relating to the store inventory level, The first inventory quantity forecasting means includes the step of calculating an estimated value for the inventory quantity of a store after a predetermined period, for each product, based on the information stored in the product information storage means, with respect to one of the stores. The first candidate extraction means includes the step of extracting products as first delivery candidate products for which the store inventory quantity for one store falls below the first threshold, The second candidate extraction means includes the step of extracting products as second delivery candidate products for which the expected value of the store inventory for the first store falls below the second threshold, A delivery support method comprising the step of performing a delivery arrangement process for the delivery of the first delivery candidate product and the second delivery candidate product to the one store using one vehicle.
7. The second inventory quantity forecasting means calculates an estimated value for the inventory quantity of each product in the store after a predetermined period, based on information stored in the product information storage means, with respect to other stores. The third candidate extraction means includes the step of extracting products as third delivery candidate products for which the expected value of the store inventory quantity for the other stores falls below the second threshold, The delivery support method according to claim 6, characterized in that the delivery means performs a delivery arrangement process to deliver the third delivery candidate product to the other store using the one vehicle.
8. The computer has a nearby store storage means that stores store grouping information, which groups the stores based on predetermined criteria including having the same delivery route or being located within a predetermined distance. The delivery support method according to claim 7, characterized in that the second inventory quantity forecasting means calculates an estimated value of the store inventory quantity with respect to the other stores that belong to the same group as the first store in the store grouping information.
9. The available space determination means includes the step of checking whether there is available space on the cargo bed of the vehicle when the first delivery candidate product and the second delivery candidate product are loaded onto the cargo bed of the vehicle, The delivery support method according to claim 8, characterized in that the delivery means performs a delivery arrangement process to deliver the third delivery candidate product to the other store using the one vehicle if there is available space.
10. The empty space determination means checks the size of the empty space on the cargo bed, and if it can confirm that the size of the empty space is larger than the size of the third candidate product for delivery, it determines that the third candidate product for delivery can be delivered. The delivery support method according to claim 9, characterized in that, when the delivery means is determined to be capable of delivery, a delivery arrangement process is performed to deliver the third delivery candidate product to the other store using the one vehicle.
11. A delivery support program for causing a computer to perform the method according to any one of claims 6 to 10.