WO2019127979A1 - 自助售货机的补货方法、装置、存储介质和计算机设备 - Google Patents

自助售货机的补货方法、装置、存储介质和计算机设备 Download PDF

Info

Publication number
WO2019127979A1
WO2019127979A1 PCT/CN2018/082779 CN2018082779W WO2019127979A1 WO 2019127979 A1 WO2019127979 A1 WO 2019127979A1 CN 2018082779 W CN2018082779 W CN 2018082779W WO 2019127979 A1 WO2019127979 A1 WO 2019127979A1
Authority
WO
WIPO (PCT)
Prior art keywords
vending machine
self
replenishment
service vending
current
Prior art date
Application number
PCT/CN2018/082779
Other languages
English (en)
French (fr)
Inventor
李宣儒
叶伟
宋泽阳
Original Assignee
深圳友宝科斯科技有限公司
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by 深圳友宝科斯科技有限公司 filed Critical 深圳友宝科斯科技有限公司
Publication of WO2019127979A1 publication Critical patent/WO2019127979A1/zh

Links

Images

Classifications

    • G—PHYSICS
    • G07—CHECKING-DEVICES
    • G07F—COIN-FREED OR LIKE APPARATUS
    • G07F9/00—Details other than those peculiar to special kinds or types of apparatus
    • G07F9/001—Interfacing with vending machines using mobile or wearable devices
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/06—Buying, selling or leasing transactions
    • G06Q30/0601—Electronic shopping [e-shopping]
    • G06Q30/0605—Supply or demand aggregation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/06—Buying, selling or leasing transactions
    • G06Q30/0601—Electronic shopping [e-shopping]
    • G06Q30/0621—Item configuration or customization
    • G—PHYSICS
    • G07—CHECKING-DEVICES
    • G07F—COIN-FREED OR LIKE APPARATUS
    • G07F9/00—Details other than those peculiar to special kinds or types of apparatus
    • G07F9/002—Vending machines being part of a centrally controlled network of vending machines
    • G—PHYSICS
    • G07—CHECKING-DEVICES
    • G07F—COIN-FREED OR LIKE APPARATUS
    • G07F9/00—Details other than those peculiar to special kinds or types of apparatus
    • G07F9/02—Devices for alarm or indication, e.g. when empty; Advertising arrangements in coin-freed apparatus
    • G07F9/026—Devices for alarm or indication, e.g. when empty; Advertising arrangements in coin-freed apparatus for alarm, monitoring and auditing in vending machines or means for indication, e.g. when empty

Definitions

  • the present application relates to a replenishing method, apparatus, storage medium and computer device for a self-service vending machine.
  • the self-service vending machine refers to a machine that self-services and self-service payment by customers.
  • Self-service vending machines can be seen in major shopping malls and large public places. Self-service vending machines bring a lot of convenience to people's travel.
  • the replenishment of the self-service vending machine is usually determined by the operator's own intuition and experience to determine which machines need replenishment and replenishment time, but the inventor realizes that this replenishment method may be related to the actual replenishment time. There are large differences, resulting in unnecessary waste of human and material resources and inefficient operation.
  • a replenishment method for a self-service vending machine comprising:
  • the at least one replenishment parameter in the first replenishment parameter set exceeds its corresponding preset threshold, determining that the current self-service vending machine is a self-service vending machine to be replenished and using the first replenishment time point as The replenishment time point of the current self-service vending machine.
  • a replenishing device for a self-service vending machine comprising:
  • the sales speed estimation module is configured to obtain a historical sales speed set corresponding to the current self-service vending machine, and obtain the first estimated sales of the current self-service vending machine from the current time point to the first replenishment time point according to the historical sales speed set.
  • Speed set a historical sales speed set corresponding to the current self-service vending machine, and obtain the first estimated sales of the current self-service vending machine from the current time point to the first replenishment time point according to the historical sales speed set.
  • a replenishment parameter calculation module configured to obtain current state data of the current self-service vending machine, and obtain a first replenishment parameter set corresponding to the first replenishment time point according to the first estimated sales speed set and current state data;
  • a determining module configured to determine, when the at least one replenishment parameter in the first replenishment parameter set exceeds a corresponding preset threshold thereof, the current self-service vending machine as a self-service vending machine to be replenished and the first The replenishment time point serves as the replenishment time point of the current self-service vending machine.
  • a computer device comprising a memory and one or more processors, the memory storing computer readable instructions, the computer readable instructions being executed by the processor to implement the replenishment method of the self-service vending machine provided in any one of the embodiments of the present application A step of.
  • One or more non-volatile storage media storing computer readable instructions that, when executed by one or more processors, cause one or more processors to implement the self-service provided in any one of the embodiments herein The steps of the replenishment method of the vending machine.
  • FIG. 1 is an application environment diagram of a replenishment method of a self-service vending machine in accordance with one or more embodiments
  • FIG. 2 is a flow chart of a replenishment method of a self-service vending machine in accordance with one or more embodiments
  • FIG. 3 is a flow chart of a replenishing method of a self-service vending machine in another embodiment
  • step S210 of FIG. 2 is a flow chart showing the steps of step S210 of FIG. 2 in accordance with one or more embodiments
  • Figure 5 is a flow chart showing a replenishing method of the self-service vending machine in still another embodiment
  • FIG. 6 is a diagram showing a displayed replenishment recommendation list interface of a terminal corresponding to an operator in accordance with one or more embodiments
  • FIG. 7 is a flow chart showing the steps of obtaining current status data of a current self-service vending machine in accordance with one or more embodiments
  • FIG. 8 is a diagram of an inventory reporting interface displayed by a terminal corresponding to an operator in accordance with one or more embodiments
  • FIG. 9 is a structural block diagram of a replenishing device of a self-service vending machine in accordance with one or more embodiments.
  • Figure 10 is a block diagram showing the structure of a replenishing device of a self-service vending machine in another embodiment
  • Figure 11 is a block diagram showing the structure of a replenishing device of the self-service vending machine in still another embodiment
  • FIG. 12 is a schematic diagram of the internal structure of a computer device in accordance with one or more embodiments.
  • FIG. 1 is an application environment diagram of a replenishing method of a self-service vending machine provided in an embodiment, as shown in FIG. 1, in which the self-service vending machine 110, the server 120, and the terminal 130, the self-service vending machine 110 and the The server 120 is connected through a network, and the server 120 is connected to the terminal through a network.
  • the server 120 may be an independent physical server or terminal, or may be a server cluster composed of multiple physical servers, and may be a cloud server that provides basic cloud computing services such as a cloud server, a cloud database, a cloud storage, and a CDN.
  • the terminal 110 may be a smartphone, a tablet, a notebook, a desktop computer, a smart phone, a smart watch, etc., but is not limited thereto.
  • a replenishing method of a self-service vending machine is provided.
  • the method is applied to the server 120 in FIG. 1 as an example, and includes:
  • Step S210 Acquire a historical sales speed set corresponding to the current self-service vending machine, and obtain a first estimated sales speed set of the current self-service vending machine from the current time point to the first replenishment time point according to the historical sales speed set.
  • the server corresponds to at least one self-service vending machine, and when there are more than two self-service vending machines, each self-service vending machine can be sequentially used as the current vending machine.
  • Each of the self-service vending machines is provided with a plurality of cargo lanes, and the cargo lanes are identified by numbers, and one cargo is placed in each cargo lane.
  • a self-service vending machine includes 20 cargo lanes 01, 02, 03, ..., 20, of which 01 cargo lanes are placed Pepsi, 02 cargo lanes are placed pulsating pure water, 03 cargo lanes are placed Wang Laoji herbal teas, ..., 20 goods Place the uniform ice black tea.
  • the sales speed refers to the accumulated value of the sales speed of each cargo lane within one hour.
  • the freight lane sales speed refers to the sales volume of the goods corresponding to a single cargo lane within one hour, such as the cargo lane that accommodates Pepsi in one day. At 13 o'clock, Pepsi's sales volume was 3, and the freight lane sold at 3 o'clock on the same day.
  • the historical sales speed collection refers to a set of sales speeds corresponding to the current time points of the current self-service vending machine in the preset time period before the current time point.
  • the self-service vending machine reports to the server every time the product is sold, and the server counts the sales speed of the cargo lane corresponding to each cargo lane according to the received report information, and accumulates the sales speed of each cargo lane to obtain the corresponding self-service vending machine. Sales speed.
  • the first replenishment time refers to the first replenishment time set by the operator in advance, such as some operators replenishing twice a day, replenishing at 13 o'clock in the morning, and replenishing at 24 o'clock in the afternoon. Once, the 13:00 am is the first replenishment time.
  • the future sales speed of the time point can be estimated to obtain an estimated sales speed, for example, according to the sales speed of 12 o'clock every day in the previous four days.
  • the 12-point sales rate is estimated to get the estimated sales speed at 12 o'clock the next day.
  • Step S220 Acquire current state data of the current self-service vending machine, and obtain a first replenishment parameter set corresponding to the first replenishment time point according to the first estimated sales speed set and the current state data.
  • the current state data refers to data related to the state of the kiosk.
  • the current status data includes the current stock-out amount and the current stock quantity, wherein the current stock-out quantity refers to the sum of the current cargo lane shortages corresponding to the respective cargo lanes of the self-service vending machine, and the current cargo lane is out of stock.
  • the quantity refers to the difference between the cargo lane capacity and the current stock quantity.
  • the server obtains a first replenishment parameter set corresponding to the first replenishment time point according to the obtained current state data and the estimated sales speed set, wherein the first replenishment parameter is the current self-service vending machine from the current
  • the set of replenishment parameters up to the first replenishment time point is used to determine whether the current vending machine needs replenishment at the first replenishment time point.
  • the first replenishment parameter includes at least one of an estimated out-of-stock amount, a stock-out loss, a stock-out loss ratio, a stock-out commodity ratio, and a cargo lane-sale time.
  • the estimated out-of-stock quantity refers to the estimated out-of-stock quantity of the self-service vending machine from the current time point to the first replenishment time point.
  • the estimated sales speed of the segment is + the sum of the estimated sales speeds corresponding to the time points of the first replenishment time point in the early morning of the next day.
  • the current time is 22 points
  • the first replenishment time is At 6 o'clock
  • the estimated sales speed is 10 at 23 o'clock today
  • the estimated sales speed is 6:7,6,2,0,1 in the early morning of the next day
  • the current stock shortage is 15.
  • the out-of-stock loss is the accumulated value of the cargo shortage loss corresponding to each cargo lane.
  • the out-of-stock loss ratio is the ratio of stock-out loss to ideal sales.
  • the proportion of out-of-stock items is the ratio of the quantity corresponding to the out-of-stock item type to the quantity corresponding to the total item type. Since each cargo lane corresponds to one type of product, the proportion of out-of-stock items can also be the number of out-of-stock goods.
  • the ratio of the total number of goods lanes, such as the current number of out-of-stock lanes for self-service vending machines is 5, and the total number of goods lanes is 20, the proportion of out-of-stock items is 40%.
  • the cargo road sales time refers to the difference between the date of sale of all goods in a cargo lane and the current date.
  • the current sale date of all goods on a cargo lane of the current self-service vending machine is December 20, and the current date is December. 27, the goods are sold out for one week.
  • Step S230 when at least one replenishment parameter in the first replenishment parameter set exceeds its corresponding preset threshold, determining that the current self-service vending machine is a self-service vending machine to be replenished and using the first replenishment time point as the current self-sale.
  • the replenishment time of the cargo plane when at least one replenishment parameter in the first replenishment parameter set exceeds its corresponding preset threshold, determining that the current self-service vending machine is a self-service vending machine to be replenished and using the first replenishment time point as the current self-sale.
  • the server determines that the current self-service vending machine is to be replenished.
  • the self-service vending machine uses the first replenishment time point as the replenishment time point of the current self-service vending machine.
  • the server determines the current self-service kiosk as a self-service vending machine to be replenished when more than two replenishment parameters exceed a predetermined threshold. If the estimated out-of-stock quantity reaches its corresponding preset threshold and the stock-out loss reaches its corresponding preset threshold, the current self-service vending machine is determined as the self-service vending machine to be replenished.
  • the server first obtains a historical sales speed set corresponding to the current self-service vending machine, and obtains a first estimated sales speed set of the current self-service vending machine from the current time point to the first replenishment time point according to the historical sales speed set.
  • the replenishing method of the above self-service vending machine further includes:
  • Step S310 when each of the first replenishment parameter sets in the first replenishment parameter set does not exceed the corresponding preset threshold, the current self-service vending machine is obtained from the current time point to the second replenishment time point according to the historical sales speed set.
  • the second estimated sales speed collection when each of the first replenishment parameter sets in the first replenishment parameter set does not exceed the corresponding preset threshold, the current self-service vending machine is obtained from the current time point to the second replenishment time point according to the historical sales speed set. The second estimated sales speed collection.
  • Step S320 obtaining a second replenishment parameter set of the current vending machine to the second replenishment time point according to the second estimated sales speed set and the current state data.
  • Step S330 when at least one second replenishment parameter in the second replenishment parameter set exceeds its corresponding preset threshold, determining that the current self-service vending machine is a self-service vending machine that needs to replenish and will place a second replenishment time point. As the replenishment time point of the current self-service vending machine.
  • the second replenishment time refers to the second replenishment time set by the operator in advance, such as some operators replenishing the goods twice a day, replenishing at 13 o'clock in the morning, and replenishing at 24 o'clock in the afternoon. Once the goods are in stock, the second replenishment time point is 24 o'clock in the afternoon.
  • the current self-service vending machine does not need to replenish at the first replenishment time.
  • the sales speed set obtains a second estimated sales speed set of the current self-service vending machine from the current time point to the second replenishment time point, and then the current vending machine is determined according to the second estimated sales speed set and the current state data.
  • the second replenishment parameter set of the second replenishment time point wherein the calculation method of each replenishment parameter in the second replenishment parameter set is the same as the calculation method of each parameter in the first replenishment set, and therefore will not be described herein.
  • S210 in FIG. 2 includes the following steps.
  • Step S211 calculating, according to the historical sales speed set, a first average sales speed corresponding to each time point in the preset number of days and a second average sales speed corresponding to each time point in the preset number of weeks.
  • the preset number of days refers to consecutive days before the date of the day. If the current date is December 26, the preset number of days may be four consecutive days from December 21 to December 25.
  • the second average selling speed is an average value of the sales speed of the same week in the preset number of weeks at a certain time point. If the current week is Monday, the preset number of weeks is 2, and the second average speed corresponding to the zero point is The average sales speed of the last week and the sales speed of the last week.
  • Step S212 obtaining an estimated sales speed corresponding to each time point according to the first average sales speed and the second average sales speed.
  • the first average sales speed corresponding to each time point is multiplied by a certain weight plus the second sales speed multiplied by a certain weight to obtain an estimated sales speed corresponding to each time point, wherein the weight setting can be operated by The merchants set in advance according to different sales situations.
  • the first average sales speed can be multiplied by 0.4, and the second sales speed multiplied by 0.6 to obtain an estimated sales speed.
  • the server obtains the historical sales speed set
  • the first average sales speed and the second average sales corresponding to each time point from the current time point to the first replenishment time point are calculated according to the historical sales speed set.
  • the speed is then obtained based on the first average sales speed and the second average sales speed to obtain an estimated sales speed corresponding to each time point.
  • the replenishment method of the self-service vending machine includes the following steps:
  • step S510 the first self-service vending machine in the self-service vending machine set is used as the current self-service vending machine.
  • the self-service vending machine set refers to a set of a plurality of self-service vending machines corresponding to the same server.
  • the server first uses the first self-service vending machine in the collection as the current self-service vending machine, wherein the ordering of the self-service vending machines can be sorted from small to large according to the number of the self-service vending machine.
  • Step S520 Acquire a historical sales speed set corresponding to the current self-service vending machine, and obtain a first estimated sales speed set of the current self-service vending machine from the current time point to the first replenishment time point according to the historical sales speed set.
  • Step S530 Acquire current state data of the current self-service vending machine, and obtain a first replenishment parameter set corresponding to the first replenishment time point according to the first estimated sales speed set and the current state data.
  • Step S540 when at least one replenishment parameter in the first replenishment parameter set exceeds its corresponding preset threshold, determining that the current self-service vending machine is a self-service vending machine to be replenished and using the first replenishment time point as the current self-sale.
  • the replenishment time of the cargo plane when at least one replenishment parameter in the first replenishment parameter set exceeds its corresponding preset threshold, determining that the current self-service vending machine is a self-service vending machine to be replenished and using the first replenishment time point as the current self-sale.
  • Step S550 determining whether the current self-service vending machine is the last self-service vending machine
  • step S560 if yes, the process proceeds to step S580.
  • step S570 if not, the next self-service vending machine is used as the current self-service vending machine, and the process proceeds to step S520.
  • Step S580 Acquire a replenishment time point of all the self-service vending machines to be replenished, generate a replenishment recommendation form, and send the replenishment recommendation form to the terminal corresponding to the operation personnel.
  • the server may also obtain address information of all the self-service vending machines to be replenished, and generate a replenishment recommendation table according to the address information and the replenishment time.
  • step S580 of FIG. 5 includes: obtaining a set of self-service kiosks to be repaired based on the fault data.
  • the server uses the self-service vending machine corresponding to the fault data as the self-service vending machine to be repaired, and obtains the self-service vending machine to be repaired. set.
  • step S580 in FIG. 5 includes generating a replenishment recommendation list according to the set of self-service vending machines to be replenished, the time points to be replenished of the respective self-service vending machines, and the set of self-service vending machines to be repaired.
  • the set of self-service vending machines to be replenished refers to a collection of all self-service vending machines to be replenished.
  • the server generates and supplements the address information and the fault data of each self-service vending machine to be repaired according to the self-service vending machine set to be replenished, the replenishment time point of each self-service vending machine in the set of self-service vending machines to be replenished, and the self-service vending machine set to be repaired. Recommended list of goods.
  • FIG. 6 is a replenishment recommendation list displayed by the terminal corresponding to the operator in an embodiment, wherein 1710016, 1710076, 1710488, etc. are self-service vending machine numbers, and the first replenishment is preset in the morning and afternoon.
  • the self-service vending machine is arranged in descending order according to the calculated stock-out loss, and according to the relationship between the stock-out loss and the preset threshold, the severity of the stock-out is classified as: “serious”,
  • the four levels of “medium”, “slight” and “none” enable the operator to know the out-of-stock level of each self-service vending machine according to the replenishment list. For example, when the out-of-stock loss is greater than 25, it is marked as “serious” and lacking.
  • the step of acquiring the current state data of the current self-service vending machine in step S220 of FIG. 2 includes:
  • Step S221 receiving the cargo shortage data of the cargo lane sent by the terminal corresponding to the operator.
  • the terminal can scan the two-dimensional code on the self-service vending machine, the terminal displays the replenishment interface, and the replenishment interface displays the current self-service vending machine.
  • the terminal enters the inventory reporting interface corresponding to the selection instruction when the terminal receives the selection instruction of the operator.
  • the operator can select the out-of-stock condition according to the actual situation of the current cargo lane after replenishment. For example, if the cargo lane capacity of the current cargo lane is 20, and the stock quantity after replenishment is 18, the stock shortage is 2, and “Nick 2” can be selected for reporting.
  • Step S222 obtaining the current inventory quantity of the current vending machine and the preset cargo path capacity.
  • step S223 the current stock out quantity is obtained according to the shortage of the goods lane, the preset cargo lane capacity and the current stock quantity.
  • the inventory of the default cargo lane of the server is the cargo lane capacity after each replenishment of the operator, in fact, some of the vending machines are not necessarily full after replenishment, so it is necessary to The quantity of goods, the preset cargo lane capacity, and the current stock quantity are currently out of stock.
  • the current stock quantity cargo lane capacity - current stock quantity + reported stock quantity.
  • steps in the flowcharts of FIGS. 2-5 and 7 are sequentially displayed as indicated by the arrows, these steps are not necessarily performed in the order indicated by the arrows. Except as explicitly stated herein, the execution of these steps is not strictly limited, and the steps may be performed in other orders. Moreover, at least some of the steps in FIGS. 2-5 and 7 may include a plurality of sub-steps or stages, which are not necessarily performed at the same time, but may be executed at different times. The order of execution of the steps or stages is not necessarily performed sequentially, but may be performed alternately or alternately with at least a portion of the sub-steps or stages of the other steps or other steps.
  • a replenishing device 900 for a self-service vending machine comprising:
  • the first sales speed estimation module 902 is configured to obtain a historical sales speed set corresponding to the current self-service vending machine, and obtain a first estimate of the current self-service vending machine from the current time point to the first replenishment time point according to the historical sales speed set. Sales speed collection;
  • the first replenishment parameter calculation module 904 is configured to obtain current state data of the current self-service vending machine, and obtain a first replenishment parameter set corresponding to the first replenishment time point according to the first estimated sales speed set and current state data;
  • the first determining module 906 is configured to determine that the current self-service vending machine is a self-service vending machine to be replenished and the first replenishment time when at least one replenishment parameter in the first replenishment parameter set exceeds its corresponding preset threshold Point as the replenishment time point of the current self-service vending machine.
  • the first set of replenishment parameters includes at least one of an estimated out-of-stock amount, a stock-out loss, a stock-out loss ratio, a stock-out commodity ratio, and a cargo lane-sale time.
  • the foregoing apparatus further includes:
  • the second sales speed estimation module 908 is configured to: when each of the first replenishment parameters in the first replenishment parameter set does not exceed the corresponding preset threshold, obtain the current self-service vending machine from the current time point according to the historical sales speed set. a second estimated sales speed set up to the second replenishment time point;
  • the second replenishment parameter calculation module 910 obtains, according to the second estimated sales speed set and the current state data, a second replenishment parameter set of the current vending machine to the second replenishment time point;
  • the second determining module 912 determines that the current self-service vending machine is a self-service vending machine that needs to be replenished and will make a second supplement when at least one second replenishment parameter in the second replenishment parameter set exceeds its corresponding preset threshold.
  • the goods time point is used as the replenishment time point of the current self-service vending machine.
  • the first sales speed estimation module is configured to calculate, according to the historical sales speed set, a first average sales speed corresponding to each time point within the preset number of days and a second average sales corresponding to each time point within the preset number of weeks. The speed, and the estimated sales speed corresponding to each time point are obtained according to the first average sales speed and the second average sales speed.
  • the foregoing apparatus further includes:
  • the looping module 914 is configured to sequentially use the other self-service vending machines in the self-service vending machine set as the current self-service vending machine and enter the step of obtaining the historical sales speed set corresponding to the current self-service vending machine, and obtain the replenished self-service vending machine set and the to-be-replenished goods.
  • a replenishment recommendation list generating module 916 configured to generate a replenishment recommendation list according to the replenishment self-service vending machine set and the replenishment time point of each self-service vending machine;
  • the replenishment recommendation list sending module 918 is configured to send the replenishment recommendation list to the terminal corresponding to the operator.
  • the current status data includes fault data
  • the apparatus further includes: a self-service vending machine set acquisition module to be repaired, configured to obtain a set of self-service vending machines to be repaired according to the fault data; and the replenishment recommendation list generating module is further configured to The replenishment self-service vending machine collection, the replenishment time points of each self-service vending machine, and the self-service vending machine collection to be repaired generate a replenishment recommendation list.
  • the first replenishment parameter calculation module is further configured to receive the cargo out-of-stock quantity data sent by the terminal corresponding to the operator, obtain the current inventory quantity of the current vending machine, and preset the cargo lane capacity, according to the cargo lane. Out-of-stock quantities, preset cargo lane capacity, and current stock levels are currently out of stock.
  • the various modules in the replenishment device of the self-service vending machine described above may be implemented in whole or in part by software, hardware, and combinations thereof.
  • Each of the above modules may be embedded in or independent of the processor in the computer device, or may be stored in a memory in the computer device in a software form, so that the processor invokes the operations corresponding to the above modules.
  • the computer device can be used as a server.
  • the computer device connects the processor, the non-volatile storage medium, the internal memory, and the network interface through a system connection bus.
  • the non-volatile storage medium of the computer device can store an operating system and computer readable instructions that, when executed, can cause the processor to perform a replenishment method of the self-service kiosk.
  • the processor of the computer device is used to provide computing and control capabilities to support the operation of the entire computer device.
  • the internal memory can store computer readable instructions that, when executed by the processor, cause the processor to perform a replenishment method of the self-service kiosk.
  • the network interface of the computer device is used for network communication, such as receiving voice data packets, sending stop control commands, and the like.
  • FIG. 12 is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation of the computer device to which the solution of the present application is applied.
  • the specific computer device may It includes more or fewer components than those shown in the figures, or some components are combined, or have different component arrangements.
  • a computer device comprising a memory and one or more processors, the memory storing computer readable instructions, the computer readable instructions being executed by the processor to implement a replenishment method of the self-service vending machine provided in any one of the embodiments of the present application A step of.
  • One or more non-volatile storage media storing computer readable instructions that, when executed by one or more processors, cause one or more processors to implement the self-service provided in any one of the embodiments herein The steps of the replenishment method of the vending machine.
  • the storage medium may be a magnetic disk, an optical disk, a read-only memory (ROM), or the like.

Landscapes

  • Business, Economics & Management (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Accounting & Taxation (AREA)
  • Finance (AREA)
  • Economics (AREA)
  • Development Economics (AREA)
  • Marketing (AREA)
  • Strategic Management (AREA)
  • General Business, Economics & Management (AREA)
  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Control Of Vending Devices And Auxiliary Devices For Vending Devices (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)

Abstract

一种自助售货机的补货方法，包括：获取当前自助售货机对应的历史销售速度集合，根据所述历史销售速度集合得到当前自助售货机从当前时间点截止到第一补货时间点的第一预估销售速度集合；获取当前自助售货机的当前状态数据，根据所述第一预估销售速度集合和当前状态数据得到所述第一补货时间点对应的第一补货参数集合；当所述第一补货参数集合中至少一个补货参数超过其对应的预设阈值时，判定所述当前自助售货机为待补货的自助售货机并将所述第一补货时间点作为所述当前自助售货机的补货时间点。

Description

自助售货机的补货方法、装置、存储介质和计算机设备
相关申请的交叉引用
本申请要求于2017年12月30日提交中国专利局，申请号为2017114917452，申请名称为“自助售货机的补货方法、装置、存储介质和计算机设备”的中国专利申请的优先权，其全部内容通过引用结合在本申请中。
技术领域
本申请涉及一种自助售货机的补货方法、装置、存储介质和计算机设备。
背景技术
自助售货机指的是一种由顾客自助取货、自助付款的机器，在各大商场及大型的公共场所均能见到自助售货机，自助售货机给人们的出行带来了很多方便。
传统技术中，自助售货机的补货通常是由运营人员依靠自身直觉和经验判断哪些机器需要补货以及补货的时间，但是发明人意识到，这种补货方法可能与实际合理补货时间存在较大差异，造成不必要的人力物力浪费，运营效率低下。
发明内容
根据本申请公开的各种实施例，提供一种自助售货机的补货方法、装置、存储介质和计算机设备。一种自助售货机的补货方法，包括：
获取当前自助售货机对应的历史销售速度集合，根据所述历史销售速度集合得到当前自助售货机从当前时间点截止到第一补货时间点的第一预估销售速度集合；
获取当前自助售货机的当前状态数据，根据所述第一预估销售速度集合和当前状态数据得到所述第一补货时间点对应的第一补货参数集合；及
当所述第一补货参数集合中至少一个补货参数超过其对应的预设阈值时，判定所述当前自助售货机为待补货的自助售货机并将所述第一补货时间点作为所述当前自助售货机 的补货时间点。
一种自助售货机的补货装置，包括：
销售速度预估模块，用于获取当前自助售货机对应的历史销售速度集合，根据所述历史销售速度集合得到当前自助售货机从当前时间点截止到第一补货时间点的第一预估销售速度集合；
补货参数计算模块，用于获取当前自助售货机的当前状态数据，根据所述第一预估销售速度集合和当前状态数据得到所述第一补货时间点对应的第一补货参数集合；及
判定模块，用于当所述第一补货参数集合中至少一个补货参数超过其对应的预设阈值时，判定所述当前自助售货机为待补货的自助售货机并将所述第一补货时间点作为所述当前自助售货机的补货时间点。
一种计算机设备，包括存储器和一个或多个处理器，存储器中存储有计算机可读指令，计算机可读指令被处理器执行时实现本申请任意一个实施例中提供的自助售货机的补货方法的步骤。
一个或多个存储有计算机可读指令的非易失性存储介质，计算机可读指令被一个或多个处理器执行时，使得一个或多个处理器实现本申请任意一个实施例中提供的自助售货机的补货方法的步骤。
本申请的一个或多个实施例的细节在下面的附图和描述中提出。本申请的其它特征和优点将从说明书、附图以及权利要求书变得明显。
附图说明
为了更清楚地说明本申请实施例中的技术方案，下面将对实施例中所需要使用的附图作简单地介绍，显而易见地，下面描述中的附图仅仅是本申请的一些实施例，对于本领域普通技术人员来讲，在不付出创造性劳动的前提下，还可以根据这些附图获得其它的附图。
图1为根据一个或多个实施例中自助售货机的补货方法的应用环境图；
图2为根据一个或多个实施例中自助售货机的补货方法的流程图；
图3为另一个实施例中自助售货机的补货方法的流程图；
图4为根据一个或多个实施例中图2中步骤S210的步骤流程图；
图5为又一个实施例中自助售货机的补货方法的流程图；
图6为根据一个或多个实施例中运营人员对应的终端的所显示的补货推荐列表界面图；
图7为根据一个或多个实施例中获取当前自助售货机的当前状态数据的步骤流程图；
图8为根据一个或多个实施例中运营人员对应的终端所显示的库存上报界面图；
图9为根据一个或多个实施例中自助售货机的补货装置的结构框图；
图10为另一个实施例中自助售货机的补货装置的结构框图；
图11为又一个实施例中自助售货机的补货装置的结构框图；
图12为根据一个或多个实施例中计算机设备的内部结构示意图。
具体实施方式
为使本申请的特征和优点能够更加明显易懂，下面结合附图对本申请的具体实施方式做详细的说明。在下面的描述中阐述了很多具体细节以便于充分理解本申请。但是本申请能够以很多不同于在此描述的其它方式来实施，本领域技术人员可以在不违背本申请内涵的情况下做类似改进，因此本申请不受下面公开的具体实施的限制。
除非另有定义，本文所使用的所有的技术和科学术语与属于本申请的技术领域的技术人员通常理解的含义相同。本文中在本申请的说明书中所使用的术语只是为了描述具体的实施例的目的，不是旨在限制本申请。
图1为一个实施例中提供的自助售货机的补货方法的应用环境图，如图1所示，在该应用环境中，包括自助售货机110、服务器120以及终端130，自助售货机110与服务器120通过网络连接，服务器120与终端通过网络连接。
需要说明的是，服务器120可以是独立的物理服务器或终端，也可以是多个物理服务器构成的服务器集群，可以是提供云服务器、云数据库、云存储和CDN等基础云计算服务的云服务器。终端110可以是智能手机、平板电脑、笔记本电脑、台式计算机、智能音 箱、智能手表等，但并不局限于此。
在一些实施例中，如图2所示，提供了一种自助售货机的补货方法，以该方法应用于图1中的服务器120为例进行说明，包括：
步骤S210，获取当前自助售货机对应的历史销售速度集合，根据历史销售速度集合得到当前自助售货机从当前时间点截止到第一补货时间点的第一预估销售速度集合。
具体地，服务器对应至少一个自助售货机，当存在两个以上自助售货机时，可依次将各个自助售货机作为当前售货机。每一个自助售货机机内设置多个货道，货道通过编号进行标识，每一个货道内放置一种商品。如某个自助售货机包括20个货道01、02、03、……，20，其中，01货道放置百事可乐、02货道放置脉动纯净水，03货道放置王老吉凉茶，……，20货道放置统一冰红茶。销售速度指的是一个小时内各个货道销售速度的累加值，其中，货道销售速度指的是单个货道对应的商品在一个小时内的销售数量，如容纳百事可乐的货道在某一天的13点这段时间内百事可乐的销售数量为3，则该货道在当天13点的销售速度为3。历史销售速度集合指的是当前自助售货机在当前时间点之前的预设时间段内各个时间点对应的销售速度组成的集合。
在本实施例中，自助售货机每销售一次商品，都会上报服务器，服务器根据接收到的上报信息，统计各个货道对应的货道销售速度，将各个货道销售速度累加即得到自助售货机对应的销售速度。
进一步，第一补货时间指的是运营商事先设定的相对于当前的第一次补货时间，如某些运营商每天补货两次，上午13点补货一次，下午24点补货一次，则上午13点为第一补货时间点。在本实施例中，根据某一个时间点的历史销售速度服务器可以对该时间点未来的销售速度进行预估得到预估销售速度，如根据前四天中每一天12点的销售速度对次日12点的销售速度进行预估得到次日12点的预估销售速度。
步骤S220，获取当前自助售货机的当前状态数据，根据第一预估销售速度集合和当前状态数据得到第一补货时间点对应的第一补货参数集合。
具体地，当前状态数据指的是与自助售货机的状态相关的数据。在一个实施例中，当前状态数据包括当前缺货量和当前库存量，其中，当前缺货量指的是自助售货机各个货道对应的当前货道缺货量的总和，当前货道缺货量指的是货道容量与当前库存量的差值。
在本实施例中，服务器根据获取到的当前状态数据及预估销售速度集合得到第一补货时间点对应的第一补货参数集合，其中，第一补货参数为当前自助售货机从当前时间点截止到第一补货时间点的补货参数所组成的集合，用于判断当前售货机在第一补货时间点是否需要补货。
在一些实施例中，第一补货参数包括预估缺货量、缺货损失、缺货损失占比、缺货商品占比、货道售空时间中的至少一种。
预估缺货量指的是自助售货机从当前时间点截止到第一补货时间点的预估的缺货数量，其计算方法为：预估缺货量＝当前缺货量+今日剩余时间段的预估销售速度累加+次日凌晨截止到次日第一补货时间点的各个时间点对应的预估销售速度之和，举例说明，当前时间是22点，第一补货时间为次日6点，今日23点预估销售速度为10，次日凌晨截止到6点的预估销售速度分别为：8,7,6,2,0,1，当前缺货量为15，则预计缺货量为：15+10+8+7+6+2+0+1＝49。
缺货损失为各个货道对应的货道缺货损失的累加值，其中货道缺货损失可通过以下方式计算：货道缺货损失＝理想销售量–当前库存量，其中，理想销售量为从当前时间点截止到第一补货时间的各个时间点的预估销售速度之和。
缺货损失占比为缺货损失与理想销量的比值。缺货商品占比为缺货商品种类对应的数量与总的商品种类对应的数量的比值，由于每一个货道对应一个种类的商品，因此，缺货商品占比也可以为缺货货道数与总的货道数的比值，如当前自助售货机的缺货货道数为5，总的货道数为20，则缺货商品占比为40％。
货道售空时间指的是某个货道内所有商品售空的日期与当前日期之差，如当前自助售货机某个货道的所有商品售空的日期为12月20，当前日期为12月27，则货道售空时间为一周。
步骤S230，当第一补货参数集合中至少一个补货参数超过其对应的预设阈值时，判定当前自助售货机为待补货的自助售货机并将第一补货时间点作为当前自助售货机的补货时间点。
具体地，对于每一个补货参数都有一个预设的阈值，当第一补货参数集合中任意一个补货参数超过其对应的预设阈值时，则服务器判定当前自助售货机为待补货的自助售货 机，并将第一补货时间点作为当前自助售货机的补货时间点。
在一些实施例中，为了尽量减少补货次数，在两个以上的补货参数超过预设阈值时，服务器才将当前自助售货机判定为待补货的自助售货机。如在预估缺货量达到其对应的预设阈值同时缺货损失达到其对应的预设阈值时，将当前自助售货机判定为待补货的自助售货机。
本实施例中，服务器首先获取当前自助售货机对应的历史销售速度集合，根据历史销售速度集合得到当前自助售货机从当前时间点截止到第一补货时间点的第一预估销售速度集合，然后获取当前自助售货机的当前状态数据，根据第一预估销售速度集合和当前状态数据得到第一补货时间点对应的第一补货参数集合，当第一补货参数集合中至少一个补货参数超过其对应的预设阈值时，判定当前自助售货机为待补货的自助售货机并将第一补货时间点作为当前自助售货机的补货时间点，由于通过服务器自动判断是否需要补货，相对于传统技术中由运营人员根据经验及直觉进行判断，节省了人力物力，提高了运营效率。
在一些实施例中，如图3所示，上述自助售货机的补货方法还包括：
步骤S310，当第一补货参数集合中各个第一补货参数均不超过其对应的预设阈值时，根据历史销售速度集合得到当前自助售货机从当前时间点截止到第二补货时间点的第二预估销售速度集合。
步骤S320，根据第二预估销售速度集合和当前状态数据得到当前售货机截止到第二补货时间点的第二补货参数集合。
步骤S330，当第二补货参数集合中至少一个第二补货参数超过其对应的预设阈值时，判定当前自助售货机为需要进行补货的自助售货机并将将第二补货时间点作为当前自助售货机的补货时间点。
具体地，第二补货时间指的是运营商事先设定的相对于当前的第二次补货时间，如某些运营商每天补货两次，上午13点补货一次，下午24点补货一次，则下午24点为第二补货时间点。
在本实施例中，当第一补货参数集合中各个补货参数均不超过其对应的预设阈值，说明当前自助售货机在第一补货时间不需要补货，此时，可根据历史销售速度集合得到当前自助售货机从当前时间点截止到第二补货时间点的第二预估销售速度集合，然后可根据第 二预估销售速度集合和当前状态数据得到当前售货机截止到第二补货时间点的第二补货参数集合，其中，第二补货参数集合中各个补货参数的计算方法与第一补货集合中各个参数的计算方法相同，故在此不再赘述。
在一些实施例中，如图4所示，图2中S210包括以下步骤
步骤S211，根据历史销售速度集合计算预设天数内各个时间点对应的第一平均销售速度以及预设周数内各个时间点对应的第二平均销售速度。
具体地，预设天数指的是当天日期之前的连续若干天，如当前日期是12月26日，则预设天数可以是12月21日到12月25日的连续四天。第一平均销售速度指的自动收获机在预设天数内同一时间销售速度的平均值，如12月21日零点销售速度为11，12月22日零点销售速度为14，12月23日零点销售速度为14，12月24日零点销售速度为9，则第一平均销售速度为：(11+14+14+9)/4＝10。
第二平均销售速度为某个时间点在预设周数内同一礼拜日期的销售速度的平均值，如当前礼拜日期为礼拜一，预设周数为2，则零点对应的第二平均速度为上个礼拜一零点的销售速度、上上个礼拜一零点的销售速度的平均值。
步骤S212，根据第一平均销售速度及第二平均销售速度得到各个时间点对应的预估销售速度。
具体地，可将各个时间点对应的第一平均销售速度乘以一定的权重加上第二销售速度乘以一定的权重得到各个时间点对应的预估销售速度，其中，权重的设定可由运营商根据不同的销售情况事先设定。如，可将第一平均销售速度乘以0.4，第二销售速度乘以0.6得到预估销售速度。
在本实施例中，服务器获取到历史销售速度集合后，根据历史销售速度集合计算从当前时间点到第一补货时间点之间的各个时间点对应的第一平均销售速度和第二平均销售速度，然后根据第一平均销售速度和第二平均销售速度得到各个时间点对应的预估销售速度。
在一些实施例中，如图5所示，自助售货机的补货方法包括以下步骤：
步骤S510，将自助售货机集合中第一个自助售货机作为当前自助售货机。
具体地，自助售货机集合指的是同一个服务器对应的多个自助售货机组成的集合。在 本实施例中，服务器首先将该集合中的第一个自助售货机作为当前自助售货机，其中，自助售货机的排序可按照自助售货机的编号从小到大进行排序。
步骤S520，获取当前自助售货机对应的历史销售速度集合，根据历史销售速度集合得到当前自助售货机从当前时间点截止到第一补货时间点的第一预估销售速度集合。
步骤S530，获取当前自助售货机的当前状态数据，根据第一预估销售速度集合和当前状态数据得到第一补货时间点对应的第一补货参数集合。
步骤S540，当第一补货参数集合中至少一个补货参数超过其对应的预设阈值时，判定当前自助售货机为待补货的自助售货机并将第一补货时间点作为当前自助售货机的补货时间点。
步骤S550，判断当前自助售货机是否为最后一个自助售货机；
步骤S560，若是，则进入步骤S580。
步骤S570，若否，则将下一个自助售货机作为当前自助售货机，进入步骤S520。
步骤S580，获取所有待补货的自助售货机的补货时间点，生成补货推荐表，将补货推荐表发送至运营人员对应的终端。
在一些实施例中，服务器还可获取所有待补货的自助售货机的地址信息，根据地址信息、补货时间生成补货推荐表。
在一些实施例中，图5中步骤S580之前包括：根据故障数据得到待维修自助售货机集合。
在本实施例中，自助售货机出现故障后，会将故障数据上传到服务器，服务器接收到故障数据后，将故障数据对应的自助售货机作为待维修的自助售货机，得到待维修自助售货机集合。
在一些实施例中，图5中步骤S580包括：根据待补货自助售货机集合、各个自助售货机的待补货时间点及待维修自助售货机集合生成补货推荐列表。
具体地，待补货自助售货机集合指的是所有待补货的自助售货机所组成的集合。服务器根据待补货自助售货机集合、待补货自助售货机集合中各个自助售货机的待补货时间点及待维修自助售货机集合中各个待维修自助售货机的地址信息、故障数据生成补货推荐列表。
进一步，服务器将补货推荐列表发送至运营人员对应的终端。如图6所示为一个实施例中，运营人员对应的终端所显示的补货推荐列表，其中，1710016、1710076、1710488等为自助售货机编号，上午、下午为预先设定的第一补货时间、第二补货时间，在本实施例中，自助售货机按照计算出的缺货损失降序排列，并根据缺货损失与预设阈值的关系将缺货严重程度分为：“严重”、“中等”、“轻微”、“无”四个等级，使得运营人员可根据补货列表明确的知道各个自助售货机的缺货程度，如当缺货损失大于25时标记为“严重”、缺货损失大于11小于或等于25时标记为“中等”、缺货损失大于4小于或等于11时标记为“轻微”、缺货损失大于或等于0小于或等于4时标记为“无”。
在一些实施例中，如图7所示，图2中步骤S220获取当前自助售货机的当前状态数据的步骤包括：
步骤S221，接收运营人员对应的终端发送的货道缺货量数据。
具体地，运营人员到达预设的补货时间达到待补货自助售货机所在的位置时，可用终端扫描自助售货机上的二维码，终端显示补货界面，补货界面显示当前自助售货机所有货道正在售卖的商品种类，当终端接收到运营人员的选择指令时，进入选择指令对应的库存上报界面。如图8所示，为一个实施例中库存上报界面图，运营人员可根据补货后当前货道实际情况选择货道缺货情况。如当前货道的货道容量为20，补货后库存量为18，则缺货量为2，可选择“缺2”进行上报。
步骤S222，获取当前售货机的当前库存量及预设的货道容量。
步骤S223，根据货道缺货量、预设的货道容量及当前库存量得到当前缺货量。
在本实施例中，由于运营人员每一次补货后，服务器默认货道的库存量为货道容量，而实际上某些售货机补货后并不一定是满货，因此需要根据货道缺货量、预设的货道容量、当前库存量得到当前缺货量，当前缺货量＝货道容量-当前库存量+上报缺货量。
应该理解的是，虽然图2-5及图7的流程图中的各个步骤按照箭头的指示依次显示，但是这些步骤并不是必然按照箭头指示的顺序依次执行。除非本文中有明确的说明，这些步骤的执行并没有严格的顺序限制，这些步骤可以以其它的顺序执行。而且，图2-5及图7中的至少一部分步骤可以包括多个子步骤或者多个阶段，这些子步骤或者阶段并不必然是在同一时刻执行完成，而是可以在不同的时刻执行，这些子步骤或者阶段的执行顺序也 不必然是依次进行，而是可以与其它步骤或者其它步骤的子步骤或者阶段的至少一部分轮流或者交替地执行。
在一些实施例中，如图9所示，还提供了一种自助售货机的补货装置900，该装置包括：
第一销售速度预估模块902，用于获取当前自助售货机对应的历史销售速度集合，根据历史销售速度集合得到当前自助售货机从当前时间点截止到第一补货时间点的第一预估销售速度集合；
第一补货参数计算模块904，用于获取当前自助售货机的当前状态数据，根据第一预估销售速度集合和当前状态数据得到第一补货时间点对应的第一补货参数集合；及
第一判定模块906，用于当第一补货参数集合中至少一个补货参数超过其对应的预设阈值时，判定当前自助售货机为待补货的自助售货机并将第一补货时间点作为当前自助售货机的补货时间点。
在一些实施例中，第一补货参数集合包括预估缺货量、缺货损失、缺货损失占比、缺货商品占比、货道售空时间中的至少一种。
在一些实施例中，如图10所示，上述装置还包括：
第二销售速度预估模块908，用于当第一补货参数集合中各个第一补货参数均不超过其对应的预设阈值时，根据历史销售速度集合得到当前自助售货机从当前时间点截止到第二补货时间点的第二预估销售速度集合；
第二补货参数计算模块910，根据第二预估销售速度集合和当前状态数据得到当前售货机截止到第二补货时间点的第二补货参数集合；及
第二判定模块912，当第二补货参数集合中至少一个第二补货参数超过其对应的预设阈值时，判定当前自助售货机为需要进行补货的自助售货机并将将第二补货时间点作为当前自助售货机的补货时间点。
在一些实施例中，第一销售速度预估模块用于根据历史销售速度集合计算预设天数内各个时间点对应的第一平均销售速度以及预设周数内各个时间点对应的第二平均销售速度，及根据第一平均销售速度及第二平均销售速度得到各个时间点对应的预估销售速度。
在一些实施例中，如图11所示，上述装置还包括：
循环模块914，用于依次将自助售货机集合中其他自助售货机作为当前自助售货机并进入获取当前自助售货机对应的历史销售速度集合的步骤，得到待补货自助售货机集合及待补货自助售货机集合中各个自助售货机的待补货时间点；
补货推荐列表生成模块916，用于根据待补货自助售货机集合及各个自助售货机的待补货时间点生成补货推荐列表；及
补货推荐列表发送模块918，用于将补货推荐列表发送至运营人员对应的终端。
在一些实施例中，当前状态数据包括故障数据，上述装置还包括：待维修自助售货机集合获取模块，用于根据故障数据得到待维修自助售货机集合；补货推荐列表生成模块还用于根据待补货自助售货机集合、各个自助售货机的待补货时间点及待维修自助售货机集合生成补货推荐列表。
在一些实施例中，第一补货参数计算模块还用于接收运营人员对应的终端发送的货道缺货量数据，获取当前售货机的当前库存量及预设的货道容量，根据货道缺货量、预设的货道容量及当前库存量得到当前缺货量。
关于自助售货机的补货装置的具体限定可以参见上文中对于自助售货机的补货方法的限定，在此不再赘述。上述自助售货机的补货装置中的各个模块可全部或部分通过软件、硬件及其组合来实现。上述各模块可以硬件形式内嵌于或独立于计算机设备中的处理器中，也可以以软件形式存储于计算机设备中的存储器中，以便于处理器调用执行以上各个模块对应的操作。
如图12所示，为一个实施例中计算机设备的内部结构图，该计算机设备可用作服务器。该计算机设备通过***连接总线连接处理器、非易失性存储介质、内存储器和网络接口。该计算机设备的非易失性存储介质可存储操作***和计算机可读指令，该计算机可读指令被执行时，可使得处理器执行一种自助售货机的补货方法。该计算机设备的处理器用于提供计算和控制能力，支撑整个计算机设备的运行。该内存储器中可储存有计算机可读指令，该计算机可读指令被处理器执行时，可使得处理器执行一种自助售货机的补货方法。计算机设备的网络接口用于进行网络通信，如接收语音数据包，发送停止控制指令等。
本领域技术人员可以理解，图12中示出的结构，仅仅是与本申请方案相关的部分结构的框图，并不构成对本申请方案所应用于其上的计算机设备的限定，具体的计算机设备可以包括比图中所示更多或更少的部件，或者组合某些部件，或者具有不同的部件布置。
一种计算机设备，包括存储器和一个或多个处理器，存储器中存储有计算机可读指令，计算机可读指令被处理器执行时实现本申请任意一个实施例中提供的自助售货机的补货方法的步骤。
一个或多个存储有计算机可读指令的非易失性存储介质，计算机可读指令被一个或多个处理器执行时，使得一个或多个处理器实现本申请任意一个实施例中提供的自助售货机的补货方法的步骤。
本领域普通技术人员可以理解实现上述实施例方法中的全部或部分流程，是可以通过计算机可读指令来指令相关的硬件来完成，该计算机可读指令可存储于一非易失性计算机可读取存储介质中，该计算机可读指令在执行时，可包括如上述各方法的实施例的流程。其中，所述的存储介质可为磁碟、光盘、只读存储记忆体(Read-Only Memory，ROM)等。
以上所述实施例的各技术特征可以进行任意的组合，为使描述简洁，未对上述实施例中的各个技术特征所有可能的组合都进行描述，然而，只要这些技术特征的组合不存在矛盾，都应当认为是本说明书记载的范围。
以上所述实施例仅表达了本申请的几种实施方式，其描述较为具体和详细，但并不能因此而理解为对发明专利范围的限制。应当指出的是，对于本领域的普通技术人员来说，在不脱离本申请构思的前提下，还可以做出若干变形和改进，这些都属于本申请的保护范围。因此，本申请专利的保护范围应以所附权利要求为准。

Claims (20)

  1. 一种自助售货机的补货方法，包括：
    获取当前自助售货机对应的历史销售速度集合，根据所述历史销售速度集合得到当前自助售货机从当前时间点截止到第一补货时间点的第一预估销售速度集合；
    获取当前自助售货机的当前状态数据，根据所述第一预估销售速度集合和当前状态数据得到所述第一补货时间点对应的第一补货参数集合；及
    当所述第一补货参数集合中至少一个补货参数超过其对应的预设阈值时，判定所述当前自助售货机为待补货的自助售货机并将所述第一补货时间点作为所述当前自助售货机的补货时间点。
  2. 根据权利要求1所述的方法，其特征在于，所述第一补货参数集合包括预估缺货量、缺货损失、缺货损失占比、缺货商品占比、货道售空时间中的至少一种。
  3. 根据权利要求1所述的方法，其特征在于，还包括：
    当所述第一补货参数集合中各个第一补货参数均不超过其对应的预设阈值时，根据所述历史销售速度集合得到当前自助售货机从当前时间点截止到第二补货时间点的第二预估销售速度集合；
    根据所述第二预估销售速度集合和当前状态数据得到当前售货机截止到第二补货时间点的第二补货参数集合；及
    当所述第二补货参数集合中至少一个第二补货参数超过其对应的预设阈值时，判定所述当前自助售货机为需要进行补货的自助售货机并将将所述第二补货时间点作为所述当前自助售货机的补货时间点。
  4. 根据权利要求1所述的方法，其特征在于，所述获取当前自助售货机对应的历史销售速度集合，根据所述历史销售速度集合得到当前自助售货机从当前时间点截止到第一补货时间点的第一预估销售速度集合，包括：
    根据所述历史销售速度集合计算预设天数内各个时间点对应的第一平均销售速度以及预设周数内各个时间点对应的第二平均销售速度；及
    根据所述第一平均销售速度及第二平均销售速度得到各个时间点对应的预估销售速度。
  5. 根据权利要求1所述的方法，其特征在于，还包括：
    依次将自助售货机集合中其他自助售货机作为当前自助售货机并进入获取当前自助售货机对应的历史销售速度集合的步骤，得到待补货自助售货机集合及待补货自助售货机集合中各个自助售货机的待补货时间点；
    根据所述待补货自助售货机集合及所述各个自助售货机的待补货时间点生成补货推荐列表；及
    将所述补货推荐列表发送至运营人员对应的终端。
  6. 根据权利要求5所述的方法，其特征在于，在所述当前状态数据包括故障数据，所述根据所述待补货自助售货机集合及各个自助售货机的待补货时间点生成补货推荐列表之前，所述方法还包括：
    根据所述故障数据得到待维修自助售货机集合；
    所述根据所述待补货自助售货机集合及各个自助售货机的待补货时间点生成补货推荐列表包括：
    根据所述待补货自助售货机集合、待补货自助售货机集合中各个自助售货机的待补货时间点及待维修自助售货机集合生成补货推荐列表。
  7. 根据权利要求1所述的方法，其特征在于，所述获取当前自助售货机的当前状态数据包括：
    接收运营人员对应的终端发送的货道缺货量数据；
    获取当前售货机的当前库存量及预设的货道容量；及
    根据所述货道缺货量、预设的货道容量及当前库存量得到当前缺货量。
  8. 根据权利要求1所述的方法，其特征在于，所述当前状态数据包括当前缺货量和当前库存量。
  9. 根据权利要求5所述的方法，其特征在于，在所述根据所述待补货自助售货机集合及各个自助售货机的待补货时间点生成补货推荐列表之前，所述方法还包括：
    获取所述待补货自助售货机集合中各个自助售货机的地址信息；
    所述根据所述待补货自助售货机集合及各个自助售货机的待补货时间点生成补货推荐列表包括：
    根据所述待补货自助售货机集合、待补货自助售货机集合中各个自助售货机的待补货时间点及地址信息生成补货推荐列表。
  10. 一种自助售货机的补货装置，包括：
    第一销售速度预估模块，用于获取当前自助售货机对应的历史销售速度集合，根据所述历史销售速度集合得到当前自助售货机从当前时间点截止到第一补货时间点的第一预估销售速度集合；
    第一补货参数计算模块，用于获取当前自助售货机的当前状态数据，根据所述第一预估销售速度集合和当前状态数据得到所述第一补货时间点对应的第一补货参数集合；及
    第一判定模块，用于当所述第一补货参数集合中至少一个补货参数超过其对应的预设阈值时，判定所述当前自助售货机为待补货的自助售货机并将所述第一补货时间点作为所述当前自助售货机的补货时间点。
  11. 一种自助售货机的补货装置，其特征在于，所述第一补货参数集合包括预估缺货量、缺货损失、缺货损失占比、缺货商品占比、货道售空时间中的至少一种。
  12. 一个或多个存储有计算机可读指令的非易失性计算机可读存储介质，所述计算机可读指令被一个或多个处理器执行时，使得所述一个或多个处理器执行以下步骤：
    获取当前自助售货机对应的历史销售速度集合，根据所述历史销售速度集合得到当前自助售货机从当前时间点截止到第一补货时间点的第一预估销售速度集合；
    获取当前自助售货机的当前状态数据，根据所述第一预估销售速度集合和当前状态数据得到所述第一补货时间点对应的第一补货参数集合；及
    当所述第一补货参数集合中至少一个补货参数超过其对应的预设阈值时，判定所述当前自助售货机为待补货的自助售货机并将所述第一补货时间点作为所述当前自助售货机的补货时间点。
  13. 根据权利要求12所述的存储介质，其特征在于，所述第一补货参数集合包括预估缺货量、缺货损失、缺货损失占比、缺货商品占比、货道售空时间中的至少一种。
  14. 根据权利要求12所述的存储介质，其特征在于，所述计算机可读指令被所述处理器执行时还执行以下步骤：
    当所述第一补货参数集合中各个第一补货参数均不超过其对应的预设阈值时，根据所 述历史销售速度集合得到当前自助售货机从当前时间点截止到第二补货时间点的第二预估销售速度集合；
    根据所述第二预估销售速度集合和当前状态数据得到当前售货机截止到第二补货时间点的第二补货参数集合；及
    当所述第二补货参数集合中至少一个第二补货参数超过其对应的预设阈值时，判定所述当前自助售货机为需要进行补货的自助售货机并将将所述第二补货时间点作为所述当前自助售货机的补货时间点。
  15. 根据权利要求12所述的存储介质，其特征在于，所述获取当前自助售货机对应的历史销售速度集合，根据所述历史销售速度集合得到当前自助售货机从当前时间点截止到第一补货时间点的第一预估销售速度集合，包括：
    根据所述历史销售速度集合计算预设天数内各个时间点对应的第一平均销售速度以及预设周数内各个时间点对应的第二平均销售速度；及
    根据所述第一平均销售速度及第二平均销售速度得到各个时间点对应的预估销售速度。
  16. 一种计算机设备，包括存储器及一个或多个处理器，所述存储器中储存有计算机可读指令，所述计算机可读指令被所述一个或多个处理器执行时，使得所述一个或多个处理器执行以下步骤：
    获取当前自助售货机对应的历史销售速度集合，根据所述历史销售速度集合得到当前自助售货机从当前时间点截止到第一补货时间点的第一预估销售速度集合；
    获取当前自助售货机的当前状态数据，根据所述第一预估销售速度集合和当前状态数据得到所述第一补货时间点对应的第一补货参数集合；及
    当所述第一补货参数集合中至少一个补货参数超过其对应的预设阈值时，判定所述当前自助售货机为待补货的自助售货机并将所述第一补货时间点作为所述当前自助售货机的补货时间点。
  17. 根据权利要求16所述的计算机设备，其特征在于，所述第一补货参数集合包括预估缺货量、缺货损失、缺货损失占比、缺货商品占比、货道售空时间中的至少一种。
  18. 根据权利要求16所述的计算机设备，其特征在于，所述处理器执行所述计算机 可读指令时还执行以下步骤：
    当所述第一补货参数集合中各个第一补货参数均不超过其对应的预设阈值时，根据所述历史销售速度集合得到当前自助售货机从当前时间点截止到第二补货时间点的第二预估销售速度集合；
    根据所述第二预估销售速度集合和当前状态数据得到当前售货机截止到第二补货时间点的第二补货参数集合；及
    当所述第二补货参数集合中至少一个第二补货参数超过其对应的预设阈值时，判定所述当前自助售货机为需要进行补货的自助售货机并将将所述第二补货时间点作为所述当前自助售货机的补货时间点。
  19. 根据权利要求16所述的计算机设备，其特征在于，所述获取当前自助售货机对应的历史销售速度集合，根据所述历史销售速度集合得到当前自助售货机从当前时间点截止到第一补货时间点的第一预估销售速度集合，包括：
    根据所述历史销售速度集合计算预设天数内各个时间点对应的第一平均销售速度以及预设周数内各个时间点对应的第二平均销售速度；及
    根据所述第一平均销售速度及第二平均销售速度得到各个时间点对应的预估销售速度。
  20. 根据权利要求16所述的计算机设备，其特征在于，所述处理器执行所述计算机可读指令时还执行以下步骤：
    依次将自助售货机集合中其他自助售货机作为当前自助售货机并进入获取当前自助售货机对应的历史销售速度集合的步骤，得到待补货自助售货机集合及待补货自助售货机集合中各个自助售货机的待补货时间点；
    根据所述待补货自助售货机集合及所述各个自助售货机的待补货时间点生成补货推荐列表；及
    将所述补货推荐列表发送至运营人员对应的终端。
PCT/CN2018/082779 2017-12-30 2018-04-12 自助售货机的补货方法、装置、存储介质和计算机设备 WO2019127979A1 (zh)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
CN201711491745.2 2017-12-30
CN201711491745.2A CN108280930B (zh) 2017-12-30 2017-12-30 自助售货机的补货方法、装置、存储介质和计算机设备

Publications (1)

Publication Number Publication Date
WO2019127979A1 true WO2019127979A1 (zh) 2019-07-04

Family

ID=62802910

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/CN2018/082779 WO2019127979A1 (zh) 2017-12-30 2018-04-12 自助售货机的补货方法、装置、存储介质和计算机设备

Country Status (2)

Country Link
CN (1) CN108280930B (zh)
WO (1) WO2019127979A1 (zh)

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111275534A (zh) * 2020-02-27 2020-06-12 支付宝实验室(新加坡)有限公司 商品补货方法、装置、***及电子设备
CN112150189A (zh) * 2020-09-01 2020-12-29 深圳友宝科斯科技有限公司 商品销售判断方法和分配方法、装置、计算机和储存介质
CN115504264A (zh) * 2022-10-23 2022-12-23 北京云迹科技股份有限公司 利用机器人为智能货柜备货的方法及相关设备

Families Citing this family (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109472920A (zh) * 2018-09-12 2019-03-15 湖南金码智能设备制造有限公司 一种自动售货机智能库存管理***和方法
CN109635961B (zh) * 2018-12-17 2021-02-19 广州甘来信息科技有限公司 基于自贩机的运维调度方法、装置、设备及存储介质
CN109558991B (zh) * 2018-12-17 2021-02-19 广州甘来信息科技有限公司 基于自贩机的货道量推荐方法、装置、设备及存储介质
CN109658207A (zh) * 2019-01-15 2019-04-19 深圳友朋智能商业科技有限公司 自动售货机的商品推荐方法、***及装置
CN110458345A (zh) * 2019-07-31 2019-11-15 深圳蓝贝科技有限公司 确定机器损失出货量的方法、装置、设备及存储介质
CN111080899A (zh) * 2019-11-30 2020-04-28 嘉兴聚变信息科技有限公司 具有存量不足提醒的自助售货机及其提醒方法
CN111047773A (zh) * 2019-12-13 2020-04-21 广州通达汽车电气股份有限公司 公交售货机补货方法、装置、电子设备及存储介质
CN113096306A (zh) * 2021-03-04 2021-07-09 深圳友宝科斯科技有限公司 售货***补货方法、设备、可读存储介质及售货***
CN115423369A (zh) * 2022-10-10 2022-12-02 广东便捷神科技股份有限公司 一种基于区块链的物品管理***及方法
CN117314325B (zh) * 2023-09-25 2024-04-05 江苏多飞网络科技有限公司 一种基于图像识别的电商产品仓储全流程监控管理***

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2002109625A (ja) * 2000-09-28 2002-04-12 Casio Comput Co Ltd オーダ情報処理システム並びにこのシステムに用いられる情報処理装置及び自動販売装置
CN102915596A (zh) * 2011-08-01 2013-02-06 郑正春 自动贩卖机商品监控***
CN103544776A (zh) * 2013-10-25 2014-01-29 上海煦荣信息技术有限公司 自动售货***及自动售货终端
CN106910034A (zh) * 2015-12-22 2017-06-30 阿里巴巴集团控股有限公司 商品对象调拨方法及装置
CN107292724A (zh) * 2017-07-04 2017-10-24 北京惠赢天下网络技术有限公司 一种订单的自动生成方法、装置及服务器

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2002109625A (ja) * 2000-09-28 2002-04-12 Casio Comput Co Ltd オーダ情報処理システム並びにこのシステムに用いられる情報処理装置及び自動販売装置
CN102915596A (zh) * 2011-08-01 2013-02-06 郑正春 自动贩卖机商品监控***
CN103544776A (zh) * 2013-10-25 2014-01-29 上海煦荣信息技术有限公司 自动售货***及自动售货终端
CN106910034A (zh) * 2015-12-22 2017-06-30 阿里巴巴集团控股有限公司 商品对象调拨方法及装置
CN107292724A (zh) * 2017-07-04 2017-10-24 北京惠赢天下网络技术有限公司 一种订单的自动生成方法、装置及服务器

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111275534A (zh) * 2020-02-27 2020-06-12 支付宝实验室(新加坡)有限公司 商品补货方法、装置、***及电子设备
CN112150189A (zh) * 2020-09-01 2020-12-29 深圳友宝科斯科技有限公司 商品销售判断方法和分配方法、装置、计算机和储存介质
CN112150189B (zh) * 2020-09-01 2024-06-04 深圳友宝科斯科技有限公司 商品销售判断方法和分配方法、装置、计算机和储存介质
CN115504264A (zh) * 2022-10-23 2022-12-23 北京云迹科技股份有限公司 利用机器人为智能货柜备货的方法及相关设备

Also Published As

Publication number Publication date
CN108280930A (zh) 2018-07-13
CN108280930B (zh) 2021-06-15

Similar Documents

Publication Publication Date Title
WO2019127979A1 (zh) 自助售货机的补货方法、装置、存储介质和计算机设备
CN110363454B (zh) 用于确定商品补货量的方法及装置
WO2019095883A1 (zh) 信息生成方法和装置
US10636079B2 (en) Demand-based product sourcing
JP6468619B2 (ja) 動的に調整可能な購入予約の更新度合−製品消費入力
CN106991550B (zh) 商品对象补货信息处理方法及装置
US10817885B2 (en) Dynamically adjusted automated item replenishment
US10504128B2 (en) Systems and methods for improved billing and ordering
CN107705056A (zh) 一种库存状态监控方法及装置、服务器、客户端
WO2017087179A1 (en) System and method for providing a multi-channel inventory allocation approach for retailers
CN107230033A (zh) 一种基于数据分析技术的库存预警管理***及其方法
US10832195B2 (en) Automated procurement device
CN111047264B (zh) 一种物流任务分配方法及装置
CN112488602A (zh) 补货方法、装置和***
US20160148226A1 (en) System and method for forecasting and managing returned merchanidse in retail
TW202242735A (zh) 庫存自動化管理方法及其系統
US11915187B2 (en) Method and system for tracking inventory including inventory level reconciliation across inventory tracking system
CN108470261A (zh) 一种下单方法及装置
CN104866988A (zh) 一种电商分布式智能配送自助取货***技术设置方法
CN113177824A (zh) 补货任务处理方法、装置、计算机***和可读存储介质
CN113793081A (zh) 仓储监控方法、装置、计算机可读介质及电子设备
US8301301B2 (en) Distributed item dispenser management
CN114663015A (zh) 补货方法和装置
CN115699057A (zh) 短生命周期销售曲线估计
CN111724530A (zh) 全链路自动化补货方法及售货***

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 18894267

Country of ref document: EP

Kind code of ref document: A1

NENP Non-entry into the national phase

Ref country code: DE

32PN Ep: public notification in the ep bulletin as address of the adressee cannot be established

Free format text: NOTING OF LOSS OF RIGHTS PURSUANT TO RULE 112(1) EPC (EPO FORM 1205A DATED 10.11.2020)

122 Ep: pct application non-entry in european phase

Ref document number: 18894267

Country of ref document: EP

Kind code of ref document: A1