WO2023134189A1 - Procédé et appareil de génération d'informations de réapprovisionnement, dispositif électronique et support lisible par ordinateur - Google Patents

Procédé et appareil de génération d'informations de réapprovisionnement, dispositif électronique et support lisible par ordinateur Download PDF

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WO2023134189A1
WO2023134189A1 PCT/CN2022/118579 CN2022118579W WO2023134189A1 WO 2023134189 A1 WO2023134189 A1 WO 2023134189A1 CN 2022118579 W CN2022118579 W CN 2022118579W WO 2023134189 A1 WO2023134189 A1 WO 2023134189A1
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target
information
inventory
historical
turnover
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PCT/CN2022/118579
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English (en)
Chinese (zh)
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申欣冉
高振羽
庄晓天
吴盛楠
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北京京东振世信息技术有限公司
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    • 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
    • G06Q10/00—Administration; Management
    • G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
    • 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
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
    • G06Q10/06315—Needs-based resource requirements planning or analysis
    • 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
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0635—Risk analysis of enterprise or organisation activities
    • 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
    • G06Q10/00—Administration; Management
    • G06Q10/08—Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
    • G06Q10/087—Inventory or stock management, e.g. order filling, procurement or balancing against orders
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02W—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO WASTEWATER TREATMENT OR WASTE MANAGEMENT
    • Y02W90/00—Enabling technologies or technologies with a potential or indirect contribution to greenhouse gas [GHG] emissions mitigation

Definitions

  • the embodiments of the present disclosure relate to the field of computer technology, and in particular, to a method, device, electronic device, and computer-readable medium for generating replenishment information.
  • Some embodiments of the present disclosure provide a replenishment information generation method, device, electronic device, and computer-readable medium to solve the technical problems mentioned in the background art section above.
  • some embodiments of the present disclosure provide a method for generating replenishment information.
  • the method includes: acquiring a set of historical circulation volumes of target items in the first historical time period; According to the cumulative distribution function of each historical circulation volume included in the volume collection, the cumulative distribution function of the circulation volume is obtained; according to the above-mentioned cumulative distribution function of the circulation volume and the target confidence degree, the risk circulation volume information under the above-mentioned target confidence level is generated as the inventory target information; The unit replenishment information is generated based on the inventory target information and the existing inventory information of the target item.
  • some embodiments of the present disclosure provide an apparatus for generating replenishment information
  • the apparatus includes: an acquisition unit configured to acquire a set of historical circulation volumes of target items within a first historical time period; a fitting unit configured to It is configured to perform cumulative distribution fitting on each of the historical turnover volumes included in the above-mentioned historical turnover volume set according to the target distribution function type to obtain the cumulative distribution function of the turnover volume; Confidence, generating risk circulation information under the target confidence level as inventory target information; a second generation unit configured to generate unit replenishment information according to the inventory target information and existing inventory information of the target item.
  • some embodiments of the present disclosure provide an electronic device, including: at least one processor; and a storage device, on which at least one program is stored.
  • the device implements the method described in any implementation manner of the first aspect above.
  • some embodiments of the present disclosure provide a computer-readable medium on which a computer program is stored, wherein when the program is executed by a processor, the method described in any implementation manner of the above-mentioned first aspect is implemented.
  • Fig. 1 is a schematic diagram of an application scenario of a method for generating replenishment information according to some embodiments of the present disclosure
  • FIG. 2 is a flowchart of some embodiments of a method for generating replenishment information according to the present disclosure
  • Fig. 3 is a flow chart of another embodiment of a method for generating replenishment information according to the present disclosure
  • Fig. 4 is a flow chart of some other embodiments of methods for generating replenishment information according to the present disclosure
  • Fig. 5 is a schematic structural diagram of some embodiments of a device for generating replenishment information according to the present disclosure
  • FIG. 6 is a schematic structural diagram of an electronic device suitable for implementing some embodiments of the present disclosure.
  • Relevant replenishment information generation method for example, based on the historical circulation of the item and the SKU related information of the item to output the daily granularity circulation forecast result, and then further output the replenishment amount based on the predicted circulation and replenishment related parameters; Or determine the safety stock according to the historical circulation of the item, so as to supplement the safety stock in the warehouse, etc.
  • the determination of the replenishment amount and the safety stock are based on the predicted value of the historical circulation, and the forecast The accuracy of the value is low, and the accuracy of the determined replenishment quantity and safety stock is also low.
  • the determined replenishment quantity or safety stock is large, the items in the warehouse will be backlogged for a long time, resulting in loss of items.
  • the determined replenishment quantity or safety stock quantity is small, the items need to be rescheduled to meet the delivery demand, resulting in a waste of item transportation resources.
  • some embodiments of the present disclosure propose a method and device for generating replenishment information, which reduces the loss of items and saves transport resources for items.
  • Fig. 1 is a schematic diagram of an application scenario of a method for generating replenishment information according to some embodiments of the present disclosure.
  • the computing device 101 may acquire the historical circulation volume collection 102 of the target item within the first historical time period. Then, the computing device 101 may perform cumulative distribution fitting on each historical turnover volume included in the historical turnover volume set 102 according to the target distribution function type 103 to obtain the cumulative distribution function 104 of the turnover volume. Afterwards, the computing device 101 may generate the risk circulation amount under the above-mentioned target confidence level 105 as the inventory target information 106 according to the above-mentioned circulation volume cumulative distribution function 104 and the target confidence level 105 . Finally, the computing device 101 can generate unit replenishment information 108 according to the above-mentioned inventory quantity target information 106 and the above-mentioned existing inventory information 107 of the target item.
  • the above-mentioned computing device 101 may be hardware or software.
  • the computing device When the computing device is hardware, it can be realized as a distributed cluster composed of multiple servers or terminal devices, or as a single server or a single terminal device.
  • the computing device When the computing device is embodied as software, it can be installed in the hardware devices listed above. It can be implemented, for example, as a plurality of software or software modules for providing distributed services, or as a single software or software module. No specific limitation is made here.
  • the method for generating replenishment information includes the following steps:
  • Step 201 acquiring a set of historical circulation volumes of target items within a first historical time period.
  • the execution body of the replenishment information generation method can obtain the historical circulation volume of the target item in the first historical time period from the terminal through a wired connection or a wireless connection. gather.
  • the above-mentioned target item may be any item.
  • the historical circulation volume in the above-mentioned historical circulation volume collection may be the circulation quantity (for example, sales volume) of the above-mentioned target item in a certain unit period within the first historical time period.
  • Each historical turnover volume in the above historical turnover volume collection corresponds to a unit period.
  • the first historical time period is 2021/9/01-2021/9/07
  • one unit period is a day in 2021/9/01-2021/9/07.
  • the above wireless connection methods may include but not limited to 3G/4G connection, WiFi connection, Bluetooth connection, WiMAX connection, Zigbee connection, UWB (ultra wideband) connection, and other wireless connection methods known or developed in the future .
  • the acquired set of historical circulation volumes can represent each actual circulation-related information of the target item in the first historical time period.
  • the execution subject may perform filling processing on the above-mentioned historical turnover set to obtain the filled historical turnover set.
  • the above-mentioned executive body may fill the historical flow amount that is a null value in the above-mentioned historical flow amount set with the first preset value.
  • the above-mentioned first preset value may be 0.
  • the specific setting of the first preset value is not limited.
  • the above execution subject may also perform elimination processing on the above historical flow volume set to obtain the historical flow volume set after elimination processing.
  • the above-mentioned execution subject may remove historical turnover amounts that are greater than or equal to a second preset value from the above-mentioned historical turnover volume set.
  • the above-mentioned second preset value may be a value far exceeding the average value of the historical flow volume included in the historical flow volume set.
  • the specific setting of the second preset value is not limited.
  • Step 202 perform cumulative distribution fitting on each historical turnover volume included in the historical turnover volume set to obtain a cumulative distribution function of the turnover volume.
  • the execution subject may perform cumulative distribution fitting on each historical turnover volume included in the historical turnover volume set according to the type of the target distribution function to obtain a cumulative distribution function of the turnover volume.
  • the above target distribution function type may be a preselected distribution function type received by the execution subject.
  • the above target distribution function type can be Pareto distributions (Pareto distributions).
  • Pareto distributions there is no limitation on the setting of the target distribution function type.
  • the above-mentioned executive body can perform cumulative distribution fitting on each historical turnover volume by calling the package library to obtain the cumulative distribution function of the turnover volume.
  • the scipy package of Python can be called, and according to the Pareto distribution and the parameter set, the cumulative distribution of each historical turnover included in the above-mentioned historical turnover set can be fitted to obtain the cumulative distribution function of the turnover.
  • the above-mentioned parameter set may include: the maximum historical circulation volume, the minimum historical circulation volume, and the number of equal shares.
  • the above-mentioned maximum historical turnover may be the largest historical turnover among the above-mentioned various historical turnovers.
  • the aforementioned minimum historical turnover may be the smallest historical turnover among the aforementioned historical turnovers.
  • the number of equally divided shares may be the number of shares used to equally divide the value range formed by the minimum historical circulation amount and the maximum historical circulation amount.
  • the number of aliquots can be preset.
  • the number of equally divided shares may also be the ratio of the difference between the maximum historical circulation volume and the minimum historical circulation volume after rounding up or down to a preset value.
  • the above preset value may be 10.
  • the specific setting of the preset value is not limited.
  • the cumulative distribution function of the circulation volume can be fitted according to the overall distribution of the historical circulation volume collection and the type of the target distribution function.
  • Step 203 according to the cumulative distribution function of the circulation volume and the target confidence level, generate the risk circulation volume information under the target confidence level as the inventory target information.
  • the execution subject may generate the risk turnover information under the target confidence level as the inventory target information according to the cumulative distribution function of the turnover volume and the target confidence level.
  • the above-mentioned executive body can generate the risk turnover under the above-mentioned target confidence level through the following formula according to the above-mentioned cumulative distribution function of the turnover volume and the target confidence level:
  • VaR ⁇ (Z) inf ⁇ z
  • ⁇ represents the above-mentioned target confidence.
  • VaR ⁇ (Z) represents the amount of risk circulation under the above target confidence level.
  • inf ⁇ means to take the lower limit function.
  • Z represents each historical turnover included in the above historical turnover set.
  • z represents a random historical turnover among the above-mentioned historical turnovers.
  • F Z (z) represents the probability value of the cumulative distribution function of the above-mentioned circulation volume. Then, the generated risk turnover can be determined as risk turnover information.
  • the circulation volume of the target item on a certain day will not exceed the circulation volume represented by the inventory target information, that is, the inventory target information can be used as the maximum item demand.
  • the executive body may generate the conditional risk turnover under the target confidence level as the risk turnover information according to the turnover cumulative distribution function and the target confidence level.
  • the above-mentioned executive body can generate the conditional risk turnover under the above-mentioned target confidence level according to the above-mentioned cumulative distribution function of the turnover volume and the above-mentioned target confidence level:
  • CVaR ⁇ (Z) E ⁇ Z
  • ⁇ represents the above-mentioned target confidence.
  • CVaR ⁇ (Z) represents the conditional risk turnover under the above target confidence level.
  • VaR ⁇ (Z) represents the amount of risk circulation under the above target confidence level.
  • Z represents each historical turnover included in the above historical turnover set. Then, the generated conditional risk turnover can be determined as risk turnover information. Thus, the conditional risk turnover can be used as the inventory target information.
  • the above-mentioned target confidence is determined through the following steps:
  • the inventory target information under the above-mentioned confidence level is generated to obtain the inventory target information set.
  • the execution subject for determining the above-mentioned target confidence may be the above-mentioned execution subject or other execution subjects.
  • step 203 for the above-mentioned step of the execution subject to generate the inventory target information under the above-mentioned confidence level and details are not repeated here.
  • the second step is to generate target total inventory information according to each inventory target information in the above inventory target information set and the quantity per unit period included in the first historical period, and obtain a target total inventory information set.
  • the above-mentioned first historical time period includes multiple days
  • the above-mentioned unit time period may be a time period in units of days.
  • the executive body may determine the product of the inventory target information (ie, risk turnover) and the quantity per unit period included in the first historical period as the target total inventory information.
  • the third step for each confidence degree in the above-mentioned confidence degree set, according to the target total inventory information corresponding to the above-mentioned confidence degree in the above-mentioned target total inventory information set and the inventory corresponding to the above-mentioned confidence degree in the above-mentioned inventory target information set Target information to generate simulation results.
  • the above simulation results may include order fulfillment rate and inventory turnover days.
  • the executive body may determine the difference between the target total inventory information and the sum of the historical circulation quantities included in the historical circulation volume set as the ending total inventory. Then, the ratio of the total inventory at the end of the above-mentioned period to the sum of the above-mentioned various historical circulation volumes can be determined as the inventory turnover days.
  • the quantity of the historical circulation quantity that is less than or equal to the above-mentioned inventory target information among the various historical circulation quantities included in the historical circulation quantity set may be determined as the first quantity.
  • the quantity of the historical turnover volume included in the above historical turnover volume set may be determined as the second quantity.
  • the ratio of the first quantity to the second quantity may be determined as the order fulfillment rate.
  • the above-mentioned order fulfillment rate and the above-mentioned inventory turnover days may be combined to obtain a simulation result.
  • the above combination processing may be character splicing processing.
  • Step 4 From the obtained simulation result set, select the simulation results including the order fulfillment rate greater than the preset order fulfillment rate and the inventory turnover days less than the preset inventory turnover days as the target simulation results.
  • the order fulfillment rate included in the obtained simulation result set is greater than the preset order fulfillment rate, and the number of simulation results including inventory turnover days less than the preset inventory turnover days is multiple, it can be obtained from the included order
  • a simulation result is arbitrarily selected as the target simulation result from the simulation results whose fulfillment rate is greater than the preset order fulfillment rate and which includes inventory turnover days less than the preset inventory turnover days.
  • the simulation result including the largest order fulfillment rate may also be selected as the target simulation result from the simulation results whose order fulfillment rate is greater than the preset order fulfillment rate and whose inventory turnover days are less than the preset inventory turnover days.
  • the confidence degree corresponding to the above target simulation result is determined as the target confidence degree.
  • the size of the target confidence can be automatically configured through the preset order fulfillment rate and order fulfillment rate.
  • Step 204 generating unit replenishment information according to the inventory target information and the existing inventory information of the target item.
  • the execution subject may generate unit replenishment information according to the inventory target information and the existing inventory information of the target item.
  • the above-mentioned existing inventory information may include the current inventory of the above-mentioned target item.
  • the executive body may determine the difference between the above-mentioned risk circulation amount and the above-mentioned inventory amount as the unit replenishment amount in response to the above-mentioned risk circulation amount being greater than the above-mentioned inventory amount. Then, the above-mentioned unit replenishment quantity can be determined as unit replenishment information.
  • the replenishment-related information of the target item for one day can be determined.
  • the execution subject may control an associated item scheduling device to perform an item scheduling operation according to the unit replenishment information.
  • the aforementioned item scheduling device may be a device for transporting items to schedule items.
  • the above item dispatching device may be a transport vehicle.
  • the above-mentioned execution subject may send the information representing the dispatching of the items of the unit replenishment amount represented by the above-mentioned unit replenishment information to the above-mentioned item scheduling device, so that the above-mentioned item scheduling device executes scheduling the items of the unit replenishment amount after receiving the above-mentioned information. item scheduling operations.
  • the target item can be scheduled according to the generated unit replenishment information with the unit period as the time granularity.
  • the above-mentioned embodiments of the present disclosure have the following beneficial effects: through the methods for generating replenishment information in some embodiments of the present disclosure, loss of articles is reduced, and article transportation resources are saved. Specifically, the reason for the loss of items and the waste of item transportation resources is that the determination of replenishment quantity and safety stock quantity is based on the forecast value of historical circulation volume, and the accuracy of the forecast value is low, so the determined replenishment quantity The accuracy of the inventory and safety stock is also low. When the determined replenishment amount or safety stock is large, the items in the warehouse will be backlogged for a long time, resulting in loss of items.
  • a set of historical circulation volumes of the target item within the first historical time period is acquired.
  • the acquired set of historical circulation volumes can represent each actual circulation-related information of the target item in the first historical time period.
  • cumulative distribution fitting is performed on each historical turnover volume included in the above historical turnover volume set to obtain a turnover cumulative distribution function.
  • the cumulative distribution function of the circulation volume can be fitted according to the overall distribution of the historical circulation volume collection and the type of the target distribution function.
  • the risk circulation volume information under the above target confidence level is generated as the inventory target information. Therefore, there is a possibility of target confidence in the future, and the circulation volume of the target item on a certain day will not exceed the circulation volume represented by the inventory target information, that is, the inventory target information can be used as the maximum item demand.
  • unit replenishment information is generated based on the inventory target information and the existing inventory information of the target item. Thus, according to the current inventory information and inventory target information of the target item, the replenishment-related information of the target item for one day can be determined. Also, because the predicted value of the circulation volume is not used when generating the unit replenishment information, the accuracy of the unit replenishment information is improved. In turn, the loss of items is reduced, and the transportation resources of items are saved.
  • FIG. 3 it shows a flow 300 of another embodiment of a method for generating replenishment information.
  • the process 300 of the method for generating replenishment information includes the following steps:
  • Step 301 acquiring a set of historical circulation volumes of target items within a first historical time period.
  • step 201 in those embodiments corresponding to FIG. 2 for the specific implementation of step 301 and the technical effects brought about, and details are not repeated here.
  • Step 302 acquiring the historical circulation volume set of the target item within the second historical time period.
  • the execution subject of the replenishment information generation method may obtain the historical flow of the above-mentioned target items in the second historical time period from the terminal through a wired connection or a wireless connection. volume set.
  • the second historical time period may be the same as the first historical time period, or may be different from the first historical time period.
  • no limitation is set for the specific setting of the first historical time period and the second historical time period.
  • Step 303 determining the historical turnover volume at the preset quantile point in the historical turnover volume set as the historical turnover volume of the quantile point.
  • the execution subject may determine the historical turnover volume at the preset quantile point in the historical turnover volume set as the historical turnover volume of the quantile point.
  • the above-mentioned preset quantile points may be preset such that the corresponding percentages of historical turnover volumes are all less than or equal to the percentage values of the quantile point historical turnover volumes. For example, when the preset quantile point is 95%, 95% of the historical turnover volume in the set of historical turnover volumes is smaller than the historical turnover volume of the aforementioned quantile point.
  • Step 304 Determine the mean value of the historical flow volume included in the historical flow volume set as the average value of the historical flow volume.
  • the execution subject may determine the mean value of the historical turnover volume included in the historical turnover volume set as the average value of the historical turnover volume.
  • Step 305 in response to the ratio of the historical turnover of the quantile point to the average value of the historical turnover greater than or equal to a preset threshold, determine the item type of the target item as the long-tail category.
  • the executive body may determine the item type of the target item as the long-tail category in response to the ratio of the historical turnover volume of the quantile point to the average value of the historical circulation volume being greater than or equal to a preset threshold.
  • the above-mentioned long-tail class can represent the above-mentioned target item as an item that conforms to the long-tail theory.
  • the specific setting of the above-mentioned preset threshold is not limited.
  • Step 306 perform cumulative distribution fitting on each historical turnover volume included in the historical turnover volume set to obtain a cumulative distribution function of the turnover volume.
  • step 202 in those embodiments corresponding to FIG. 2 for the specific implementation of step 306 and the technical effects brought about, and details are not repeated here.
  • Step 307 in response to the item type of the target item being long tail, according to the cumulative distribution function of the turnover volume and the target confidence level, generate the conditional risk turnover volume under the target confidence level as the risk turnover volume information.
  • the execution subject may respond to the item type of the target item as a long-tail category, and generate the conditional risk turnover under the target confidence level as the risk circulation according to the cumulative distribution function of the turnover volume and the target confidence level. amount of information.
  • the above-mentioned executive body can generate the conditional risk turnover under the above-mentioned target confidence level through the following formula according to the above-mentioned cumulative distribution function of the turnover volume and the above-mentioned target confidence level:
  • CVaR ⁇ (Z) E ⁇ Z
  • ⁇ represents the above-mentioned target confidence.
  • CVaR ⁇ (Z) represents the conditional risk turnover under the above target confidence level.
  • VaR ⁇ (Z) represents the amount of risk circulation under the above target confidence level.
  • Z represents each historical turnover included in the above historical turnover set.
  • the conditional risk circulation amount slightly larger than the value of the risk circulation amount can be used as the risk circulation amount information as the inventory target information.
  • the risk of the aforementioned target item being out of stock can be reduced, thereby reducing the number of rescheduling items. Thereby, the resource of item transportation can be saved.
  • Step 308 generating unit replenishment information according to the inventory target information and the existing inventory information of the target item.
  • step 204 in those embodiments corresponding to FIG. 2 for the specific implementation of step 308 and the technical effects brought about, and details are not repeated here.
  • the process 300 of the method for generating replenishment information in some embodiments corresponding to FIG. 3 embodies determining whether the item type of the target item is a long tail
  • the steps the class extends. Therefore, the solutions described in these embodiments can use the conditional risk turnover slightly larger than the value of the risk turnover as the risk turnover information when the target item is a long-tail item as the inventory target information.
  • the risk of the aforementioned target item being out of stock can be reduced, thereby reducing the number of rescheduling items. Thereby, the resource of item transportation can be saved.
  • FIG. 4 it shows a flow 400 of some other embodiments of methods for generating replenishment information.
  • the flow 400 of the method for generating replenishment information includes the following steps:
  • Step 401 acquiring a set of historical circulation volumes of target items within a first historical time period.
  • Step 402 perform cumulative distribution fitting on each historical turnover volume included in the historical turnover volume set to obtain a cumulative distribution function of the turnover volume.
  • Step 403 According to the cumulative distribution function of the circulation volume and the target confidence level, the risk circulation volume information under the target confidence level is generated as the inventory target information.
  • Step 404 generating unit replenishment information according to the inventory target information and the existing inventory information of the target item.
  • steps 401-404 for the specific implementation of steps 401-404 and the technical effects brought about by them, reference may be made to steps 201-204 in those embodiments corresponding to FIG. 2 , and details are not repeated here.
  • Step 405 according to the target replenishment days and inventory target information, generate the target total inventory of the target item within the target replenishment days.
  • the execution subject of the method for generating replenishment information can generate the target item within the above-mentioned target replenishment days according to the target replenishment days and the above-mentioned inventory target information.
  • Target total inventory may be a preset number of days for replenishing the above-mentioned target items in the future.
  • the executive body may determine the product of the target replenishment days and the inventory target information as the target total inventory of the target item within the target replenishment days. Thus, the determined total target inventory can be used as the maximum total demand for the above-mentioned target items within the target replenishment days.
  • the execution subject may generate the target replenishment days based on the preset replenishment days, the preset replenishment period, and the preset delivery time.
  • the above-mentioned number of pre-stocking days may be a preset number of days used by the supplier for stocking.
  • the aforementioned preset replenishment cycle may be the duration of the next replenishment cycle.
  • the above-mentioned preset delivery time may be a preset time for the supplier to deliver the item. It can be understood that the unit of the number of days for pre-arriving goods, the pre-set replenishment cycle and the pre-set delivery time can all be days.
  • the above executive body can use the following formula to generate the target replenishment days:
  • T represents the target replenishment days.
  • BP means the number of pre-arrival days mentioned above.
  • NRT stands for the preset replenishment cycle mentioned above.
  • VLT stands for the preset replenishment cycle mentioned above.
  • Step 406 generating replenishment information according to the target total inventory and existing inventory information.
  • the execution subject may generate replenishment information according to the target total inventory and the existing inventory information.
  • the executive body may determine the difference between the target total inventory and the inventory as the replenishment amount in response to the target total inventory being greater than the inventory included in the existing inventory information. Then, the above replenishment quantity may be determined as replenishment information.
  • the replenishment-related information of the target item within the target replenishment days can be determined.
  • Step 407 controlling the associated item scheduling device to perform an item scheduling operation according to the replenishment information.
  • the execution subject may control an associated item scheduling device to perform an item scheduling operation according to the replenishment information.
  • the execution subject may send the information representing the scheduling of items of the replenishment quantity indicated by the replenishment information to the item scheduling device, so that the item scheduling device executes scheduling the items of the items of the replenishment amount after receiving the above information Scheduling operations.
  • the target item can be scheduled according to the generated replenishment information with the target replenishment days as the time granularity.
  • the process 400 of the method for generating replenishment information in some embodiments corresponding to FIG. 4 reflects the time granularity of the target replenishment days, The extended step of scheduling the target item based on the generated replenishment information. Therefore, the solutions described in these embodiments can take the target replenishment days as the time granularity, and schedule the target items according to the generated replenishment information.
  • the present disclosure provides some embodiments of a replenishment information generating device, and these device embodiments correspond to those method embodiments shown in FIG. 2 , the device Specifically, it can be applied to various electronic devices.
  • an apparatus 500 for generating replenishment information in some embodiments includes: an acquiring unit 501 , a fitting unit 502 , a first generating unit 503 and a second generating unit 504 .
  • the obtaining unit 501 is configured to obtain the historical circulation volume set of the target item in the first historical time period;
  • the fitting unit 502 is configured to carry out a process for each historical circulation volume included in the above-mentioned historical circulation volume set according to the type of the target distribution function.
  • the cumulative distribution is fitted to obtain the cumulative distribution function of the circulation volume;
  • the first generation unit 503 is configured to generate the risk circulation volume information under the above target confidence level as the inventory target information according to the above circulation volume cumulative distribution function and the target confidence level;
  • the second generation unit 504 is configured to generate unit replenishment information according to the above inventory target information and the existing inventory information of the above target item.
  • the acquisition unit 501 may further include: a historical turnover set acquisition unit, a quantile historical turnover determination unit, a historical turnover average determination unit, and an item type determination unit (not shown in the figure).
  • the above-mentioned historical turnover set acquisition unit is configured to acquire the historical turnover set of the above-mentioned target item within the second historical time period.
  • the quantile point historical flow amount determining unit is configured to determine the historical flow amount at a preset quantile point in the historical flow amount set as the quantile point historical flow amount.
  • the above-mentioned historical flow average value determination unit is configured to determine the average value of the historical flow amounts included in the above-mentioned historical flow amount set as the historical flow average value.
  • the item type determination unit is configured to determine the item type of the target item as the long-tail category in response to the ratio of the historical turnover volume of the quantile point to the average value of the historical circulation volume being greater than or equal to a preset threshold.
  • the first generation unit 503 may be configured to: in response to the item type of the target item being a long-tail item, according to the cumulative distribution function of the turnover volume and the target confidence level, generate the conditional risk circulation under the target confidence level The amount is used as the risk flow information.
  • the first generation unit 503 may be configured to generate, as the risk turnover information, the conditional risk turnover under the above target confidence level according to the above turnover cumulative distribution function and the above target confidence level.
  • the above-mentioned target confidence degree is determined through the following steps: according to the above-mentioned circulation volume cumulative distribution function and each confidence degree in the preset confidence degree set, the inventory target information under the above-mentioned confidence degree is generated, and the inventory amount is obtained Target information set; according to each inventory target information in the above-mentioned inventory target information set and the quantity of the unit time period included in the above-mentioned first historical time period, generate target total inventory information, and obtain the target total inventory information set; for the above-mentioned confidence For each confidence level in the set, a simulation result is generated according to the target total inventory information corresponding to the above-mentioned confidence level in the above-mentioned target total inventory information set and the inventory target information corresponding to the above-mentioned confidence level in the above-mentioned inventory target information set, wherein , the above simulation results include the order fulfillment rate and inventory turnover days; from the obtained simulation result set, select the simulation results that include the order fulfillment rate greater than the preset order fulfillment
  • the replenishment information generation device 500 may also include: a target total inventory generation unit (not shown in the figure), configured to generate the target item in the above target according to the target replenishment days and the above inventory target information.
  • the target total inventory quantity in days to replenish may also include: a target total inventory generation unit (not shown in the figure), configured to generate the target item in the above target according to the target replenishment days and the above inventory target information.
  • the replenishment information generating device 500 may further include: a target replenishment days generating unit (not shown in the figure), configured to be based on the preset stocking days, preset replenishment Cycle and preset delivery time to generate target replenishment days.
  • a target replenishment days generating unit (not shown in the figure), configured to be based on the preset stocking days, preset replenishment Cycle and preset delivery time to generate target replenishment days.
  • the replenishment information generation apparatus 500 may further include: a replenishment information generation unit and a first item scheduling device control unit (not shown in the figure).
  • the replenishment information generation unit is configured to generate replenishment information according to the above-mentioned target total inventory and the above-mentioned existing inventory information.
  • the first item scheduling device control unit is configured to control the associated item scheduling device to perform an item scheduling operation according to the above replenishment information.
  • the replenishment information generating apparatus 500 may further include: a second item scheduling device control unit (not shown in the figure), configured to control an associated item scheduling device to perform item scheduling operations according to the above-mentioned unit replenishment information.
  • a second item scheduling device control unit (not shown in the figure), configured to control an associated item scheduling device to perform item scheduling operations according to the above-mentioned unit replenishment information.
  • the units recorded in the device 500 correspond to the steps in the method described with reference to FIG. 2 . Therefore, the operations, features and beneficial effects described above for the method are also applicable to the device 500 and the units contained therein, and will not be repeated here.
  • FIG. 6 it shows a schematic structural diagram of an electronic device (such as the computing device 101 in FIG. 1 ) 600 suitable for implementing some embodiments of the present disclosure.
  • the electronic device shown in FIG. 6 is only an example, and should not limit the functions and scope of use of the embodiments of the present disclosure.
  • an electronic device 600 may include a processing device (such as a central processing unit, a graphics processing unit, etc.) 601, which may be randomly accessed according to a program stored in a read-only memory (ROM) 602 or loaded from a storage device 608.
  • a processing device such as a central processing unit, a graphics processing unit, etc.
  • RAM memory
  • various programs and data necessary for the operation of the electronic device 600 are also stored.
  • the processing device 601, ROM 602, and RAM 603 are connected to each other through a bus 604.
  • An input/output (I/O) interface 605 is also connected to the bus 604 .
  • the following devices can be connected to the I/O interface 605: input devices 606 including, for example, a touch screen, touchpad, keyboard, mouse, camera, microphone, accelerometer, gyroscope, etc.; including, for example, a liquid crystal display (LCD), speaker, vibration an output device 607 such as a computer; a storage device 608 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 609.
  • the communication means 609 may allow the electronic device 600 to communicate with other devices wirelessly or by wire to exchange data. While FIG. 6 shows electronic device 600 having various means, it should be understood that implementing or having all of the means shown is not a requirement. More or fewer means may alternatively be implemented or provided. Each block shown in FIG. 6 may represent one device, or may represent multiple devices as required.
  • the processes described above with reference to the flowcharts may be implemented as computer software programs.
  • some embodiments of the present disclosure include a computer program product, which includes a computer program carried on a computer-readable medium, where the computer program includes program codes for executing the methods shown in the flowcharts.
  • the computer program may be downloaded and installed from a network via communication means 609, or from storage means 608, or from ROM 602.
  • the processing device 601 When the computer program is executed by the processing device 601, the above functions defined in the methods of some embodiments of the present disclosure are performed.
  • the computer-readable medium described in some embodiments of the present disclosure may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two.
  • a computer readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of computer readable storage media may include, but are not limited to: electrical connections having at least one lead, portable computer diskettes, hard disks, random access memory (RAM), read only memory (ROM), erasable programmable Read memory (EPROM or flash memory), fiber optics, portable compact disk read only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the above.
  • a computer-readable storage medium may be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.
  • a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code thereon. Such propagated data signals may take many forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the foregoing.
  • a computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium, which can transmit, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device .
  • Program code embodied on a computer readable medium may be transmitted by any appropriate medium, including but not limited to wires, optical cables, RF (radio frequency), etc., or any suitable combination of the above.
  • the client and the server can communicate using any currently known or future network protocols such as HTTP (HyperText Transfer Protocol, Hypertext Transfer Protocol), and can communicate with digital data in any form or medium
  • HTTP HyperText Transfer Protocol
  • the communication eg, communication network
  • Examples of communication networks include local area networks (“LANs”), wide area networks (“WANs”), internetworks (e.g., the Internet), and peer-to-peer networks (e.g., ad hoc peer-to-peer networks), as well as any currently known or future developed network of.
  • the above-mentioned computer-readable medium may be included in the above-mentioned electronic device, or may exist independently without being incorporated into the electronic device.
  • the above-mentioned computer-readable medium carries one or more programs, and when the above-mentioned one or more programs are executed by the electronic device, the electronic device: acquires a set of historical circulation volumes of the target item within the first historical time period; The type of distribution function, which performs cumulative distribution fitting on each of the historical turnover volumes included in the above-mentioned set of historical turnover volumes to obtain the cumulative distribution function of the turnover volume; according to the above-mentioned cumulative distribution function of the turnover volume and the target confidence level, the risk circulation under the above-mentioned target confidence level is generated
  • the amount information is used as the inventory target information; and the unit replenishment information is generated according to the above-mentioned inventory target information and the existing inventory information of the above-mentioned target item.
  • Computer program code for carrying out operations of some embodiments of the present disclosure may be written in one or more programming languages, or combinations thereof, including object-oriented programming languages—such as Java, Smalltalk, C++, Also included are conventional procedural programming languages - such as the "C" language or similar programming languages.
  • the program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server.
  • the remote computer may be connected to the user computer through any kind of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (for example, using an Internet service provider to connected via the Internet).
  • LAN local area network
  • WAN wide area network
  • Internet service provider for example, using an Internet service provider to connected via the Internet.
  • each block in the flowchart or block diagram may represent a module, program segment, or part of code that contains at least one programmable logic function for implementing the specified logical function.
  • Execute instructions may also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or they may sometimes be executed in the reverse order, depending upon the functionality involved.
  • each block of the block diagrams and/or flowchart illustrations, and combinations of blocks in the block diagrams and/or flowchart illustrations can be implemented by a dedicated hardware-based system that performs the specified functions or operations , or may be implemented by a combination of dedicated hardware and computer instructions.
  • the units described in some embodiments of the present disclosure may be realized by software or by hardware.
  • the described units may also be set in a processor, for example, it may be described as: a processor includes an acquiring unit, a fitting unit, a first generating unit, and a second generating unit.
  • a processor includes an acquiring unit, a fitting unit, a first generating unit, and a second generating unit.
  • the names of these units do not constitute a limitation to the unit itself under certain circumstances, for example, the acquisition unit may also be described as "a unit that acquires the historical turnover collection of the target item in the first historical time period".
  • exemplary types of hardware logic components include: Field Programmable Gate Arrays (FPGAs), Application Specific Integrated Circuits (ASICs), Application Specific Standard Products (ASSPs), System on Chips (SOCs), Complex Programmable Logical device (CPLD) and so on.
  • FPGAs Field Programmable Gate Arrays
  • ASICs Application Specific Integrated Circuits
  • ASSPs Application Specific Standard Products
  • SOCs System on Chips
  • CPLD Complex Programmable Logical device

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Abstract

Des modes de réalisation de la présente invention divulguent un procédé et un appareil de génération d'informations de réapprovisionnement, un dispositif électronique et un support lisible par ordinateur. Un mode de réalisation spécifique du procédé consiste : à acquérir un ensemble de quantités de circulation historiques d'un élément cible dans une première période de temps historique ; à effectuer, selon un type de fonction de distribution cible, un ajustement de distribution cumulative sur chaque quantité de circulation historique comprise dans l'ensemble de quantités de circulation historiques pour obtenir une fonction de distribution cumulative de quantité de circulation ; à générer, en fonction de la fonction de distribution cumulative de quantité de circulation et d'un coefficient de confiance cible, des informations de quantité de circulation de risque sous le coefficient de confiance cible en tant qu'informations cibles d'inventaire ; et à générer des informations de réapprovisionnement d'unité en fonction des informations cibles d'inventaire et des informations d'inventaire à portée de main de l'élément cible.
PCT/CN2022/118579 2022-01-13 2022-09-14 Procédé et appareil de génération d'informations de réapprovisionnement, dispositif électronique et support lisible par ordinateur WO2023134189A1 (fr)

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