Inventory data processing method, device, computer readable medium and electronic device

Abstract

The embodiments of the present application provide a method, device, computer-readable medium and electronic device for processing inventory data. The method includes: obtaining characteristic data of the first inventory index of the inventory object in each sub-period in the historical period as the first characteristic data, and obtaining the preset arrival date for the inventory object as the preset arrival date, the arrival date is the time interval between the shipment request time and the actual arrival time; based on the first characteristic data and the preset arrival date, through a pre-constructed simulation model, fitting the characteristic data of the second inventory index of the inventory object in each sub-period in the historical period as the second characteristic data, the second inventory index is an associated index of the first inventory index; according to the first characteristic data and the second characteristic data, determining the inventory efficiency index data of the inventory object under the preset arrival date. The technical solution of the embodiment of the present application can improve the accuracy of inventory data management.

Description

Technical Field

[0001] The present application relates to the field of computer and data processing technology, and in particular, to an inventory data processing method, device, computer-readable medium and electronic device. Background Art

[0002] At present, for most companies, the uncertainty of product delivery time is an important indicator affecting the company's operational efficiency. If the delivery period is too long compared to expectations, the company will cause untimely supply and affect the customer service level. If the delivery period is too short compared to expectations, the company will have a certain amount of excess inventory, resulting in waste. In this case, it is very important to evaluate the inventory benefits caused by the delivery period in order to improve the accuracy of inventory data management. Based on this, how to improve the accuracy of inventory data management is a technical problem that needs to be solved urgently. Summary of the invention

[0003] The embodiments of the present application provide an inventory data processing method, apparatus, computer program product or computer program, computer-readable medium, and electronic device, which can improve the accuracy of inventory data management at least to a certain extent.

[0004] Other features and advantages of the present application will become apparent from the following detailed description, or may be learned in part by the practice of the present application.

[0005] According to one aspect of an embodiment of the present application, a method for processing inventory data is provided, the method comprising: obtaining characteristic data of a first inventory indicator of an inventory object in each sub-period within a historical period as first characteristic data, and obtaining a preset arrival date for the inventory object as the preset arrival date, the arrival date being the time interval between a shipment request time and an actual arrival time; based on the first characteristic data and the preset arrival date, fitting characteristic data of a second inventory indicator of the inventory object in each sub-period within the historical period through a pre-constructed simulation model as second characteristic data, the second inventory indicator being a related indicator of the first inventory indicator; and determining inventory efficiency indicator data of the inventory object under the preset arrival date based on the first characteristic data and the preset arrival date.

[0006] According to one aspect of an embodiment of the present application, there is provided an inventory data processing device, the device comprising: an acquisition unit, used to acquire characteristic data of a first inventory indicator of an inventory object in each sub-period within a historical period as first characteristic data, and to acquire a preset arrival date for the inventory object as the preset arrival date, the arrival date being the time interval between a shipment request time and an actual arrival time; a fitting unit, used to fit characteristic data of a second inventory indicator of the inventory object in each sub-period within the historical period as second characteristic data through a pre-constructed simulation model based on the first characteristic data and the preset arrival date, the second inventory indicator being a related indicator of the first inventory indicator; and a determination unit, used to determine inventory efficiency indicator data of the inventory object under the preset arrival date based on the first characteristic data and the preset arrival date.

[0007] In some embodiments of the present application, based on the aforementioned scheme, the acquisition unit is configured as at least one of the following: obtaining characteristic data of the cargo demand quantity index of the inventory object in each sub-period within the historical period; obtaining characteristic data of the cargo replenishment quantity index of the inventory object in each sub-period within the historical period; obtaining characteristic data of the cargo inventory quantity index of the first sub-period within the historical period.

[0008] In some embodiments of the present application, based on the aforementioned scheme, the acquisition unit is further configured to: acquire multiple historical arrival dates of the inventory object within a historical period, and calculate an average of the historical arrival dates based on the multiple historical arrival dates; determine a preset arrival period interval for the inventory object based on the average of the historical arrival dates and a preset floating value; and select a preset arrival period for the inventory object within the preset arrival period interval.

[0009] In some embodiments of the present application, based on the aforementioned scheme, the acquisition unit is further configured to: acquire multiple historical arrival dates of the inventory object within a historical period, and fit an arrival date KDE curve based on the multiple historical arrival dates; based on the arrival date KDE curve, determine the arrival date whose arrival date distribution probability exceeds a predetermined threshold or a predetermined number of arrival dates with the highest arrival date distribution probability as the arrival date to be selected; and select a preset arrival date for the inventory object from the arrival dates to be selected.

[0010] In some embodiments of the present application, based on the aforementioned scheme, the fitting unit is configured as at least one of the following: fitting the characteristic data of the cargo satisfaction quantity index of the inventory object in each sub-period within the historical period; fitting the characteristic data of the cargo shortage quantity index of the inventory object in each sub-period within the historical period; fitting the characteristic data of the cargo in-transit quantity index of the inventory object in each sub-period within the historical period; fitting the characteristic data of the cargo inventory quantity index of the inventory object in each sub-period within the historical period except the first sub-period.

[0011] In some embodiments of the present application, based on the aforementioned scheme, the determination unit is configured to at least one of the following: determine the goods fulfillment rate of the inventory object under the preset delivery period; determine the goods inventory turnover days of the inventory object under the preset delivery period.

[0012] In some embodiments of the present application, based on the aforementioned scheme, the device also includes: an application unit, which is used to obtain the inventory efficiency index data of the inventory object under multiple preset delivery periods after determining the inventory efficiency index data of the inventory object under the preset delivery period; and determine the preset delivery period corresponding to the inventory efficiency index data that meets the preset conditions as the target delivery period, so as to apply it to the inventory management of the inventory object.

[0013] According to one aspect of an embodiment of the present application, a computer program product or a computer program is provided, the computer program product or the computer program includes computer instructions, and the computer instructions are stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device executes the inventory data processing method described in the above embodiment.

[0014] According to one aspect of an embodiment of the present application, a computer-readable medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the inventory data processing method as described in the above embodiment is implemented.

[0015] According to one aspect of an embodiment of the present application, an electronic device is provided, comprising: one or more processors; a storage device for storing one or more programs, and when the one or more programs are executed by the one or more processors, the one or more processors implement the inventory data processing method as described in the above embodiments.

[0016] In the technical solutions provided in some embodiments of the present application, inventory data management is simulated based on the characteristic data of the first inventory indicator of the inventory object in each sub-period within the historical period and the preset delivery period for the inventory object, and the characteristic data of the second inventory indicator associated with the first inventory indicator can be simulated to obtain the inventory efficiency indicator data of the inventory object under the preset delivery period, thereby improving the accuracy of inventory data management.

[0017] It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The drawings herein are incorporated into the specification and constitute a part of the specification, showing embodiments consistent with the present application, and together with the specification, are used to explain the principles of the present application. Obviously, the drawings described below are only some embodiments of the present application, and for ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work. In the drawings:

[0019] Figure 1 A schematic diagram showing an exemplary system architecture to which the technical solution of the embodiments of the present application can be applied;

[0020] Figure 2 A flowchart of a method for processing inventory data according to an embodiment of the present application is shown;

[0021] Figure 3 A detailed flow chart of obtaining a preset arrival date for the inventory object according to an embodiment of the present application is shown;

[0022] Figure 4 A detailed flow chart of obtaining a preset arrival date for the inventory object according to an embodiment of the present application is shown;

[0023] Figure 5 A KDE curve diagram of the delivery period according to an embodiment of the present application is shown;

[0024] Figure 6 A flowchart of a method after determining the inventory benefit index data of the inventory object under the preset delivery period according to an embodiment of the present application is shown;

[0025] Figure 7 A block diagram of an inventory data processing device according to an embodiment of the present application is shown;

[0026] Figure 8A schematic diagram of the structure of a computer system suitable for implementing an electronic device of an embodiment of the present application is shown. DETAILED DESCRIPTION

[0027] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in a variety of forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this application will be more comprehensive and complete and fully convey the concept of the example embodiments to those skilled in the art.

[0028] In addition, described feature, structure or characteristic can be combined in one or more embodiments in any suitable manner. In the following description, many specific details are provided to provide a full understanding of the embodiments of the present application. However, those skilled in the art will appreciate that the technical scheme of the present application can be put into practice without one or more of the specific details, or other methods, components, devices, steps, etc. can be adopted. In other cases, known methods, devices, realizations or operations are not shown or described in detail to avoid blurring the various aspects of the application.

[0029] The block diagrams shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically independent entities. That is, these functional entities may be implemented in software form, or in one or more hardware modules or integrated circuits, or in different networks and / or processor devices and / or microcontroller devices.

[0030] The flowcharts shown in the accompanying drawings are only exemplary and do not necessarily include all the contents and operations / steps, nor must they be executed in the order described. For example, some operations / steps can be decomposed, and some operations / steps can be combined or partially combined, so the actual execution order may change according to actual conditions.

[0031] It should be noted that the "multiple" mentioned in this article refers to two or more. "And / or" describes the association relationship of the associated objects, indicating that there can be three relationships. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. The character " / " generally indicates that the associated objects before and after are in an "or" relationship.

[0032] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the objects used in this way can be interchanged where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those shown or described.

[0033] Figure 1A schematic diagram of an exemplary system architecture to which the technical solution of the embodiments of the present application can be applied is shown.

[0034] like Figure 1 As shown, the system architecture may include terminal devices (such as Figure 1 The embodiment of the present invention is a network 104 and a server 105. The network 104 is a medium for providing a communication link between the terminal device and the server 105. The network 104 may include various connection types, such as a wired communication link, a wireless communication link, etc.

[0035] In one embodiment of the present application, the server 105 can obtain characteristic data of a first inventory indicator of an inventory object in each sub-period within a historical period from a terminal device as first characteristic data, and obtain a preset delivery date for the inventory object as the preset delivery date, wherein the delivery date is the time interval between a shipment request time and an actual arrival time. Then, based on the first characteristic data and the preset delivery date, the server 105 can fit the characteristic data of a second inventory indicator of the inventory object in each sub-period within the historical period through a pre-built simulation model as second characteristic data, wherein the second inventory indicator is an associated indicator of the first inventory indicator. Finally, the server 105 determines the inventory efficiency indicator data of the inventory object under the preset delivery date based on the first characteristic data and the preset delivery date.

[0036] In this embodiment, inventory data management is simulated based on the characteristic data of the first inventory indicator of the inventory object in each sub-period within the historical period and the preset delivery period for the inventory object, and the characteristic data of the second inventory indicator associated with the first inventory indicator can be simulated to obtain the inventory efficiency indicator data of the inventory object under the preset delivery period, thereby improving the accuracy of inventory data management.

[0037] It should be noted that the inventory data processing method provided in the embodiment of the present application can be executed by the server 105, and accordingly, the inventory data processing device is generally arranged in the server 105. However, in other embodiments of the present application, the terminal device can also have similar functions as the server, so as to execute the inventory data processing solution provided in the embodiment of the present application.

[0038] It should also be noted that Figure 1The number of terminal devices, networks and servers in the description is only for illustration. According to the implementation requirements, the server can be an independent physical server, a server cluster or a distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms.

[0039] It should be explained that cloud computing as described above is a computing model that distributes computing tasks on a resource pool composed of a large number of computers, so that various application systems can obtain computing power, storage space and information services as needed. The network that provides resources is called a "cloud". The resources in the "cloud" are infinitely expandable in the eyes of users, and can be obtained at any time, used on demand, and expanded at any time. By establishing a cloud computing resource pool (referred to as a cloud platform, generally referred to as an IaaS (Infrastructure as a Service) platform, various types of virtual resources are deployed in the resource pool for external customers to choose to use. The cloud computing resource pool mainly includes: computing devices (virtualized machines, including operating systems), storage devices, and network devices.

[0040] The implementation details of the technical solution of the embodiment of the present application are described in detail below:

[0041] Figure 2 A flowchart of an inventory data processing method according to an embodiment of the present application is shown. The inventory data processing method can be executed by a device having a computing and processing function, such as Figure 1 The server 105 or terminal device shown in is executed. Figure 2 As shown, the inventory data processing method at least includes steps 210 to 250, which are described in detail as follows:

[0042] In step 210, characteristic data of the first inventory indicator of the inventory object in each sub-period within the historical period is obtained as the first characteristic data, and a preset arrival date for the inventory object is obtained as the preset arrival date, where the arrival date is the time interval between the shipment request time and the actual arrival time.

[0043] In this application, inventory objects may refer to goods stored in a warehouse.

[0044] In the present application, each sub-period within a historical period may refer to each time interval within a period of time in history, for example, each day within a month in history.

[0045] In this application, the delivery date is the time interval between the shipment request time and the actual arrival time. For example, for a certain inventory object, a shipment is requested on May 1st, and after a period of transportation, it arrives on May 4th. Therefore, the delivery date is 3 days.

[0046] In one embodiment of the present application, obtaining characteristic data of the first inventory index of the inventory object in each sub-period within the historical period may include at least one of the following situations:

[0047] The first one is to obtain the characteristic data of the goods demand indicators of the inventory object in each sub-period within the historical period.

[0048] It should be noted that the goods demand indicator may refer to the demand for goods in a corresponding sub-period.

[0049] The second method is to obtain the characteristic data of the goods replenishment quantity indicators of the inventory object in each sub-period within the historical period.

[0050] It should be noted that the goods replenishment quantity indicator may refer to the quantity of goods that triggers replenishment in the corresponding sub-period.

[0051] The third method is to obtain the characteristic data of the goods inventory quantity indicator of the inventory object in the first sub-period within the historical period.

[0052] It should be noted that the cargo inventory indicator may refer to the storage volume of cargo in the first sub-period in the historical period.

[0053] In one embodiment of the present application, the preset delivery date for the inventory object can be obtained as follows: Figure 3 Follow the steps shown.

[0054] See also Figure 3 , shows a detailed flow chart of obtaining the preset delivery date for the inventory object according to an embodiment of the present application. Specifically including steps 211 to 213:

[0055] Step 211, obtaining multiple historical arrival dates of the inventory object within a historical period, and calculating an average of the historical arrival dates based on the multiple historical arrival dates.

[0056] Step 212, taking the historical delivery period average as a reference value and according to a preset floating value, determining a preset delivery period interval for the inventory object.

[0057] Step 213, selecting a preset arrival date for the inventory object within the preset arrival date interval.

[0058] Specifically, for example, the six historical arrival periods of the inventory object within the historical period are 3 days, 2 days, 4 days, 3 days, 1 day, and 5 days respectively. It can be seen that the average of the historical arrival period is 3 days. If the preset floating value is set to 2 days, 3 days can be used as the search center, the search upper bound parameter is 5, and the lower bound parameter is 1. The preset interval of the arrival period for the inventory object is 1 to 5 days. Furthermore, the preset arrival period for the inventory object can be selected within the preset arrival period interval of 1 to 5 days.

[0059] In another embodiment of the present application, the preset delivery date for the inventory object can be obtained according to the following method: Figure 4 Follow the steps shown.

[0060] See also Figure 4 , shows a detailed flow chart of obtaining the preset delivery date for the inventory object according to an embodiment of the present application. Specifically including steps 214 to 216:

[0061] Step 214, obtaining multiple historical arrival dates of the inventory object within the historical period, and fitting the arrival date KDE curve based on the multiple historical arrival dates.

[0062] Step 215 : Based on the arrival date KDE curve, the arrival dates whose arrival date distribution probabilities exceed a predetermined threshold or a predetermined number of arrival dates whose arrival date distribution probabilities are the highest are determined as arrival dates to be selected.

[0063] Step 216, selecting a preset arrival date for the inventory object from the arrival dates to be selected.

[0064] For details, see Figure 5 , shows a KDE curve chart of the delivery period according to an embodiment of the present application.

[0065] like Figure 5 It can be seen from the delivery date KDE curve 500 that if the delivery date with a probability of delivery date distribution exceeding 0.125 is determined as the delivery date to be selected, the delivery date to be selected is 4 to 7 days. If the five delivery dates with the highest probability of delivery date distribution are determined as the delivery date to be selected, the delivery date to be selected is 4 to 8 days.

[0066] Continue to refer to Figure 2 In step 230, based on the first characteristic data and the preset delivery date, the characteristic data of the second inventory indicator of the inventory object in each sub-period within the historical period is fitted through a pre-constructed simulation model as the second characteristic data, and the second inventory indicator is an associated indicator of the first inventory indicator.

[0067] In one embodiment of the present application, fitting the characteristic data of the second inventory index of each sub-period of the inventory object in the historical period may include at least one of the following situations:

[0068] The first one is to fit the characteristic data of the goods satisfaction quantity index of the inventory object in each sub-period within the historical period.

[0069] It should be noted that the cargo satisfaction index may refer to the cargo quantity that can be satisfied in the current warehouse.

[0070] The second method is to fit the characteristic data of the goods shortage quantity index of the inventory object in each sub-period within the historical period.

[0071] It should be noted that the goods shortage indicator may refer to the quantity of goods still missing in the warehouse.

[0072] The third method is to fit the characteristic data of the goods in transit quantity index of the inventory object in each sub-period within the historical period.

[0073] It should be noted that the cargo-in-transit indicator may refer to the volume of cargo that is in transit.

[0074] A fourth method is to fit the characteristic data of the goods inventory quantity index of the inventory object in each sub-period except the first sub-period within the historical period.

[0075] It should be noted that the goods inventory indicator may refer to the storage volume of goods in other sub-periods except the first sub-period in the historical period.

[0076] In order to enable those skilled in the art to better understand the present application, an explanation will be given below in conjunction with Table 1.

[0077] As shown in Table 1, the first characteristic data and the second characteristic data of 8 historical sub-periods are shown when the preset delivery period is 2 days. It should be noted that the second characteristic data is obtained by simulation based on the first characteristic data and the preset delivery period.

[0078]

[0079] Table 1

[0080] Continue to refer to Figure 2 In step 250, the inventory efficiency index data of the inventory object under the preset delivery period is determined according to the first characteristic data and the second characteristic data.

[0081] In one implementation of the present application, determining the inventory efficiency index data of the inventory object under the preset delivery period may include at least one of the following:

[0082] The first method is to determine the goods fulfillment rate of the inventory object under the preset delivery period.

[0083] The second method is to determine the inventory turnover days of the inventory object under the preset delivery date.

[0084] According to the first characteristic data and the second characteristic data, the inventory efficiency index data of the inventory object under the preset delivery period is determined. Referring to Table 1, it can be seen that between the 1st sub-period to the 8th sub-period, the goods satisfaction rate = total satisfaction / total demand = 330 / 360 = 91.6%, and the goods inventory turnover days = average daily inventory / average daily outbound volume = (400 / 8) / (330 / 8) = 1.21 days.

[0085] It should be noted that the goods satisfaction rate represents the service level of the enterprise. The higher the service level, the more stable the supply of the enterprise's supply side. Conversely, it means that the enterprise is seriously out of stock, which leads to reduced benefits. The goods inventory turnover days represent the speed of inventory turnover. The smaller the number of days, the faster the turnover and the smaller the corresponding inventory cost. The larger the number of days, the slower the turnover and the larger the corresponding inventory cost. These two indicators are contradictory and there are certain marginal benefits.

[0086] Based on this, inventory data can be accurately managed through the goods fulfillment rate and goods inventory turnover days of the inventory object under the preset delivery period.

[0087] In one embodiment of the present application, after determining the inventory efficiency index data of the inventory object under the preset delivery period, the following may be performed: Figure 6 Steps shown.

[0088] See also Figure 6 , shows a flowchart of a method after determining the inventory efficiency index data of the inventory object under the preset delivery period according to an embodiment of the present application. Specifically comprising steps 260 to 270:

[0089] Step 260, obtaining inventory efficiency index data of the inventory object under multiple preset delivery dates.

[0090] Step 270, determining the preset delivery date corresponding to the inventory efficiency index data that meets the preset conditions as the target delivery date, so as to be applied to the inventory management of the inventory object.

[0091] In the present application, simulation can be performed based on multiple preset delivery dates according to the first characteristic data to obtain inventory efficiency index data of the inventory object under multiple preset delivery dates, and then a most appropriate preset delivery date is selected according to the inventory efficiency index data and applied to the inventory management of the inventory object.

[0092] In order to enable those skilled in the art to better understand the present application, an explanation will be given below in conjunction with Table 2.

[0093] As shown in Table 2, the cargo fulfillment rate and cargo inventory turnover days of the inventory object under different preset delivery dates are shown. The parameter with the highest cargo fulfillment rate within a specific turnover days can be selected. If the cargo inventory turnover days need to be <1.8 days, the corresponding maximum cargo fulfillment rate is 94.4%. Therefore, the delivery date of 3 days can be selected as the final target delivery date.

[0094] In other cases, you can also select different parameters based on your own goals. For example, if the goal is a certain goods fulfillment rate, you can select a preset delivery date with the minimum goods inventory turnover days.

[0095] Delivery time (days) Cargo fulfillment rate Cargo inventory turnover days 2 94.5％ 1.84 3 94.4％ 1.76 4 92.3％ 1.65 5 89.3％ 1.41

[0096] Table 2

[0097] In the present application, by simulating and obtaining the cargo fulfillment rate and cargo inventory turnover days under multiple preset delivery dates, and comparing the cargo fulfillment rate and cargo inventory turnover days under multiple preset delivery dates, an optimal delivery date can be determined, thereby assisting the warehouse to prepare goods more effectively and improving the level of inventory management.

[0098] In the technical solutions provided in some embodiments of the present application, inventory data management is simulated based on the characteristic data of the first inventory indicator of the inventory object in each sub-period within the historical period and the preset delivery date for the inventory object, and the characteristic data of the second inventory indicator associated with the first inventory indicator can be simulated, so that the inventory efficiency indicator data of the inventory object under the preset delivery date can be determined based on the characteristic data of the first inventory indicator and the characteristic data of the second inventory indicator, thereby improving the accuracy of inventory data management. The following introduces the device embodiment of the present application, which can be used to execute the inventory data processing method in the above-mentioned embodiment of the present application. For details not disclosed in the device embodiment of the present application, please refer to the above-mentioned embodiment of the inventory data processing method of the present application.

[0099] Figure 7 A block diagram of an inventory data processing device according to an embodiment of the present application is shown.

[0100] Reference Figure 7 As shown, the inventory data processing device 700 according to an embodiment of the present application includes: an acquisition unit 701, a fitting unit 702 and a determination unit 703.

[0101] Among them, the acquisition unit 701 is used to obtain the characteristic data of the first inventory index of the inventory object in each sub-period within the historical period as the first characteristic data, and obtain the preset arrival date for the inventory object as the preset arrival date, and the arrival date is the time interval between the shipment request time and the actual arrival time; the fitting unit 702 is used to fit the characteristic data of the second inventory index of the inventory object in each sub-period within the historical period based on the first characteristic data and the preset arrival date through a pre-constructed simulation model as the second characteristic data, and the second inventory index is a related index of the first inventory index; the determination unit 703 is used to determine the inventory efficiency index data of the inventory object under the preset arrival date according to the first characteristic data and the second characteristic data.

[0102] In some embodiments of the present application, based on the aforementioned scheme, the acquisition unit 701 is configured as at least one of the following: acquiring characteristic data of the cargo demand quantity index of the inventory object in each sub-period within the historical period; acquiring characteristic data of the cargo replenishment quantity index of the inventory object in each sub-period within the historical period; acquiring characteristic data of the cargo inventory quantity index of the first sub-period within the historical period.

[0103] In some embodiments of the present application, based on the aforementioned scheme, the acquisition unit 701 is further configured to: acquire multiple historical arrival dates of the inventory object within a historical period, and calculate an average of the historical arrival dates based on the multiple historical arrival dates; determine a preset arrival period interval for the inventory object based on the average of the historical arrival dates and a preset floating value; and select a preset arrival period for the inventory object within the preset arrival period interval.

[0104] In some embodiments of the present application, based on the aforementioned scheme, the acquisition unit 701 is further configured to: acquire multiple historical arrival dates of the inventory object within a historical period, and fit an arrival date KDE curve based on the multiple historical arrival dates; based on the arrival date KDE curve, determine the arrival date whose arrival date distribution probability exceeds a predetermined threshold or a predetermined number of arrival dates with the highest arrival date distribution probability as the arrival date to be selected; and select a preset arrival date for the inventory object from the arrival dates to be selected.

[0105] In some embodiments of the present application, based on the aforementioned scheme, the fitting unit 702 is configured as at least one of the following: fitting the characteristic data of the cargo satisfaction quantity index of the inventory object in each sub-period within the historical period; fitting the characteristic data of the cargo shortage quantity index of the inventory object in each sub-period within the historical period; fitting the characteristic data of the cargo in-transit quantity index of the inventory object in each sub-period within the historical period; fitting the characteristic data of the cargo inventory quantity index of the inventory object in each sub-period within the historical period except the first sub-period.

[0106] In some embodiments of the present application, based on the aforementioned scheme, the determination unit 703 is configured as at least one of the following: determining the goods fulfillment rate of the inventory object under the preset delivery period; determining the goods inventory turnover days of the inventory object under the preset delivery period.

[0107] In some embodiments of the present application, based on the aforementioned scheme, the device also includes: an application unit, which is used to obtain the inventory efficiency index data of the inventory object under multiple preset delivery periods after determining the inventory efficiency index data of the inventory object under the preset delivery period; and determine the preset delivery period corresponding to the inventory efficiency index data that meets the preset conditions as the target delivery period, so as to apply it to the inventory management of the inventory object.

[0108] Figure 8 A schematic diagram of the structure of a computer system suitable for implementing an electronic device of an embodiment of the present application is shown.

[0109] It should be noted that Figure 8 The computer system 800 of the electronic device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0110] like Figure 8 As shown, the computer system 800 includes a central processing unit (CPU) 801, which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM) 802 or the program loaded from the storage part 808 to the random access memory (RAM) 803, such as executing the method described in the above embodiment. In the RAM 803, various programs and data required for system operation are also stored. The CPU 801, ROM 802 and RAM 803 are connected to each other through a bus 804. An input / output (I / O) interface 805 is also connected to the bus 804.

[0111] The following components are connected to the I / O interface 805: an input section 806 including a keyboard, a mouse, etc.; an output section 807 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker; a storage section 808 including a hard disk, etc.; and a communication section 809 including a network interface card such as a LAN (Local Area Network) card, a modem, etc. The communication section 809 performs communication processing via a network such as the Internet. A drive 810 is also connected to the I / O interface 805 as needed. A removable medium 811, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 810 as needed so that a computer program read therefrom is installed into the storage section 808 as needed.

[0112] In particular, according to an embodiment of the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present application includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication section 809, and / or installed from a removable medium 811. When the computer program is executed by a central processing unit (CPU) 801, various functions defined in the system of the present application are executed.

[0113] It should be noted that the computer-readable medium shown in the embodiment of the present application may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium may be, for example, - but not limited to - an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a flash memory, an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present application, a computer-readable storage medium may be any tangible medium containing or storing a program, which may be used by an instruction execution system, device or device or used in combination with it. In the present application, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, wherein a computer-readable program code is carried. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than computer-readable storage media, which may send, propagate, or transmit programs for use by or in conjunction with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wired, etc., or any suitable combination of the above.

[0114] The flowchart and block diagram in the accompanying drawings illustrate the possible architecture, functions and operations of the system, method and computer program product according to various embodiments of the present application. Wherein, each box in the flowchart or block diagram can represent a module, a program segment, or a part of the code, and the above-mentioned module, program segment, or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flowchart, and the combination of boxes in the block diagram or flowchart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0115] The units involved in the embodiments described in this application may be implemented by software or hardware, and the units described may also be set in a processor. The names of these units do not, in some cases, constitute limitations on the units themselves.

[0116] As another aspect, the present application also provides a computer program product or a computer program, which includes computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device executes the inventory data processing method described in the above embodiment.

[0117] As another aspect, the present application also provides a computer-readable medium, which may be included in the electronic device described in the above embodiment; or may exist independently without being assembled into the electronic device. The above computer-readable medium carries one or more programs, and when the above one or more programs are executed by an electronic device, the electronic device implements the inventory data processing method described in the above embodiment.

[0118] It should be noted that, although several modules or units of the equipment for action execution are mentioned in the above detailed description, this division is not mandatory. In fact, according to the embodiments of the present application, the features and functions of two or more modules or units described above can be embodied in one module or unit. On the contrary, the features and functions of one module or unit described above can be further divided into being embodied by multiple modules or units.

[0119] Through the description of the above implementation methods, it is easy for those skilled in the art to understand that the example implementation methods described here can be implemented by software or by combining software with necessary hardware. Therefore, the technical solution according to the implementation methods of the present application can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, and includes several instructions to enable a computing device (which can be a personal computer, a server, a touch terminal, or a network device, etc.) to execute the method according to the implementation methods of the present application.

[0120] Those skilled in the art will readily appreciate other embodiments of the present application after considering the specification and practicing the embodiments disclosed herein. The present application is intended to cover any variations, uses or adaptations of the present application, which follow the general principles of the present application and include common knowledge or customary technical means in the art that are not disclosed in the present application.

[0121] It should be understood that the present application is not limited to the precise structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present application is limited only by the appended claims.

Claims

1. A method for processing inventory data, characterized in that: The method comprises: Acquire characteristic data of the first inventory index of the inventory object in each sub-period in the historical period as the first characteristic data, wherein the first characteristic data includes the demand for goods, the replenishment of goods, and the inventory of goods in the first sub-period; Obtaining a preset arrival date for the inventory object as the preset arrival date, where the arrival date is the time interval between the shipment request time and the actual arrival time; Based on the first characteristic data and the preset delivery date, the characteristic data of the second inventory index of the inventory object in each sub-period within the historical period is fitted through a pre-built simulation model as the second characteristic data, the second inventory index is an associated index of the first inventory index, and the second characteristic data includes the quantity of goods in stock, the quantity of goods in short supply, the quantity of goods in transit, and the inventory quantity of goods in each sub-period except the first sub-period; Determine, based on the first characteristic data and the second characteristic data, inventory efficiency index data of the inventory object at the preset delivery date, the inventory efficiency index data including a goods fulfillment rate and a goods inventory turnover days of the inventory object at the preset delivery date; After determining the inventory efficiency index data of the inventory object under the preset delivery date, obtaining the inventory efficiency index data of the inventory object under multiple preset delivery dates respectively; determining the preset delivery date corresponding to the inventory efficiency index data that meets the preset conditions as the target delivery date, so as to apply it to the inventory management of the inventory object; The obtaining of the preset arrival date for the inventory object includes: Acquire multiple historical arrival dates of the inventory object within a historical period, and calculate an average of the historical arrival dates based on the multiple historical arrival dates; determine a preset arrival date interval for the inventory object based on the average of the historical arrival dates and a preset floating value; and select a preset arrival date for the inventory object within the preset arrival date interval; or Acquire multiple historical arrival dates of the inventory object within a historical period, and fit an arrival date KDE curve based on the multiple historical arrival dates; based on the arrival date KDE curve, determine the arrival date whose arrival date distribution probability exceeds a predetermined threshold or a predetermined number of arrival dates with the highest arrival date distribution probability as the arrival dates to be selected; and select a preset arrival date for the inventory object from the arrival dates to be selected.

2. An inventory data processing device, characterized in that: The device comprises: an acquisition unit, configured to acquire characteristic data of a first inventory indicator of an inventory object in each sub-period in a historical period as first characteristic data, and acquire a preset arrival date for the inventory object as preset arrival date, wherein the arrival date is a time interval between a shipment request time and an actual arrival time, wherein the first characteristic data includes a demand for goods, a replenishment of goods, and an inventory of goods in the first sub-period; A fitting unit is used to fit the characteristic data of the second inventory index of each sub-period of the inventory object in the historical period based on the first characteristic data and the preset delivery date through a pre-built simulation model, as the second characteristic data, wherein the second inventory index is an associated index of the first inventory index, and the second characteristic data includes the quantity of goods in stock, the quantity of goods in short supply, the quantity of goods in transit, and the inventory quantity of goods in each sub-period except the first sub-period; a determining unit, configured to determine inventory efficiency index data of the inventory object at the preset delivery date according to the first characteristic data and the second characteristic data, wherein the inventory efficiency index data includes a goods fulfillment rate and goods inventory turnover days of the inventory object at the preset delivery date; An application unit is used to obtain the inventory efficiency index data of the inventory object under the preset delivery period after determining the inventory efficiency index data of the inventory object under the preset delivery period; determine the preset delivery period corresponding to the inventory efficiency index data that meets the preset conditions as the target delivery period, so as to apply it to the inventory management of the inventory object; The obtaining of the preset arrival date for the inventory object includes: Acquire multiple historical arrival dates of the inventory object within a historical period, and calculate an average of the historical arrival dates based on the multiple historical arrival dates; determine a preset arrival date interval for the inventory object based on the average of the historical arrival dates and a preset floating value; and select a preset arrival date for the inventory object within the preset arrival date interval; or Acquire multiple historical arrival dates of the inventory object within a historical period, and fit an arrival date KDE curve based on the multiple historical arrival dates; based on the arrival date KDE curve, determine the arrival date whose arrival date distribution probability exceeds a predetermined threshold or a predetermined number of arrival dates with the highest arrival date distribution probability as the arrival dates to be selected; and select a preset arrival date for the inventory object from the arrival dates to be selected.

3. An electronic device, characterized in that: The electronic device includes one or more processors and one or more memories, wherein at least one program code is stored in the one or more memories, and the at least one program code is loaded and executed by the one or more processors to implement the operations performed by the inventory data processing method according to claim 1.

4. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores at least one program code, and the at least one program code is loaded and executed by the processor to implement the operations performed by the inventory data processing method according to claim 1.

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