Article dispatching device control method, apparatus, device, medium, and program product
By determining the category classification information of items in the target warehouse and calculating the forecast standard deviation, a safety stock quantity is generated, which solves the problem of low accuracy of safety stock quantity and achieves efficient use of resources.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- MULTIPOINT LIFE (CHENGDU) TECH CO LTD
- Filing Date
- 2022-07-22
- Publication Date
- 2026-05-15
AI Technical Summary
Existing technologies lack clear and detailed methods for determining safety stock levels, resulting in low accuracy of safety stock levels and waste of transportation and warehouse resources.
By determining the category classification information of the target warehouse's item category set, optimal service level information is generated, the forecast standard deviation is calculated, a safety stock quantity is generated, and the item scheduling equipment is controlled to perform replenishment operations based on this.
It improved the accuracy of safety stock levels and reduced waste of transportation and warehousing resources.
Smart Images
Figure CN115358445B_ABST
Abstract
Description
Technical Field
[0001] The embodiments disclosed herein relate to the field of computer technology, and specifically to methods, apparatus, devices, media, and program products for controlling item scheduling equipment. Background Technology
[0002] Safety stock is a buffer stock prepared to prevent future uncertainties in the demand or supply of goods. Currently, the common method for determining safety stock levels is to estimate the service level of each item, and then use the average daily turnover of goods as a forecast to determine the safety stock level.
[0003] However, when determining safety stock levels using the above method, the following technical problems often arise:
[0004] First, the lack of a clear and detailed plan for determining service levels leads to low accuracy in safety stock levels. When the predicted safety stock level is low, multiple shipments are required, resulting in wasted transportation resources. When the predicted safety stock level is high, the warehouse is overstocked, leading to wasted warehouse resources.
[0005] Second, directly using the average daily actual goods turnover as the forecast value results in a relatively singular forecast basis, leading to poor forecast accuracy and thus wasting transportation and warehouse resources.
[0006] Third, using the same method to determine safety stock levels for all items is problematic because different items have different shelf lives, and items with shorter shelf lives will expire quickly. Therefore, it is necessary to control the upper limit of safety stock levels, which leads to low accuracy in determining safety stock levels for different items using the same method, resulting in waste of transportation and warehouse resources. Summary of the Invention
[0007] The summary portion of this disclosure is intended to provide a brief overview of the concepts, which will be described in detail in the detailed description portion. This summary portion is not intended to identify key or essential features of the claimed technical solutions, nor is it intended to limit the scope of the claimed technical solutions.
[0008] Some embodiments of this disclosure provide methods, apparatuses, electronic devices, computer-readable media, and computer program products for controlling item scheduling equipment to solve one or more of the technical problems mentioned in the background section above.
[0009] In a first aspect, some embodiments of this disclosure provide a method for controlling an item dispatching device. The method includes: determining category classification information for each item category in a set of item categories in a target warehouse, obtaining a set of category classification information; selecting category classification information corresponding to a target item category from the set of category classification information as target category classification information, wherein the target item category is an item category in the set of item categories; generating optimal service level information corresponding to the target item category based on the target category classification information, a preset upper limit for item turnover value rate, the average daily item turnover attribute values reaching the service level upper limit within a first preset time period, unit inventory value, and logistics value; and generating optimal service level information corresponding to the target item category based on the target item category classification information, a preset upper limit for item turnover value rate, the average daily item turnover attribute values reaching the service level upper limit within a first preset time period, unit inventory value, and logistics value. The forecast standard deviation corresponding to the target item category is determined based on the daily actual item turnover and the daily predicted item turnover of the item category. A safety stock quantity for the target item category is generated based on the optimal service level information, the forecast standard deviation, the lead time of the target item category within the first preset time period, the booking interval of the target item category, and the average daily predicted item turnover within the second preset time period. A target safety stock quantity for the target item category is determined based on the safety stock quantity. In response to determining that the existing inventory of the target item category in the target warehouse is less than the safety stock quantity, the associated item scheduling equipment is controlled to perform a replenishment operation for the target item category based on the existing inventory quantity and the target safety stock quantity.
[0010] Secondly, some embodiments of this disclosure provide an item scheduling equipment control device, the device comprising: a first determining unit configured to determine the category classification information of each item category in a set of item categories in a target warehouse, thereby obtaining a set of category classification information; a selecting unit configured to select the category classification information corresponding to a target item category from the set of category classification information as target category classification information, wherein the target item category is an item category in the set of item categories; a first generating unit configured to generate optimal service level information corresponding to the target item category based on the target category classification information, a preset upper limit value of item turnover value rate, the average value of each day's item turnover attribute value reaching the upper limit value of service level within a first preset time period, unit inventory value, and logistics value; and a second determining unit configured to determine the optimal service level information corresponding to the target item category based on the target category classification information, a preset upper limit value of item turnover value rate, the average value of each day's item turnover attribute value reaching the upper limit value of service level within a first preset time period, unit inventory value, and logistics value; and a second determining unit configured to determine the optimal service level information corresponding to the target item category based on the preset upper limit value of item turnover value within the first preset time period. The first unit determines the forecast standard deviation corresponding to the target item category based on the daily actual item turnover and the daily predicted item turnover of the target item category; the second generation unit is configured to generate a safety stock quantity for the target item category based on the optimal service level information, the forecast standard deviation, the lead time of the target item category within the first preset time period, the booking interval of the target item category, and the average of the daily predicted item turnover of each of the second preset time periods; the third determination unit is configured to determine the target safety stock quantity for the target item category based on the safety stock quantity; and the control unit is configured to, in response to determining that the existing inventory quantity of the target item category in the target warehouse is less than the safety stock quantity, control the associated item scheduling equipment to perform a replenishment operation for the target item category based on the existing inventory quantity and the target safety stock quantity.
[0011] Thirdly, some embodiments of this disclosure provide an electronic device, including: one or more processors; and a storage device having one or more programs stored thereon, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the method described in any implementation of the first aspect above.
[0012] Fourthly, some embodiments of this disclosure provide a computer-readable medium having a computer program stored thereon, wherein the program, when executed by a processor, implements the method described in any of the implementations of the first aspect above.
[0013] Fifthly, some embodiments of this disclosure provide a computer program product, including a computer program that, when executed by a processor, implements the method described in any of the implementations of the first aspect above.
[0014] The above embodiments of this disclosure have the following beneficial effects: the item scheduling equipment control method of some embodiments of this disclosure can improve the accuracy of safety stock and reduce the waste of transportation and warehouse resources. Specifically, the reasons for the low accuracy of safety stock and the large waste of transportation and warehouse resources are as follows: First, there is no clear and detailed plan for determining the service level, resulting in low accuracy of safety stock. When the predicted safety stock is low, multiple transportations are required, leading to waste of transportation resources. When the predicted safety stock is high, too many items are stored in the warehouse, leading to waste of warehouse resources. Second, directly using the average daily actual item turnover as the predicted value results in a relatively singular prediction basis, leading to poor prediction accuracy, thereby causing waste of transportation and warehouse resources. Based on this, the item scheduling equipment control method of some embodiments of this disclosure first determines the category classification information of each item category in the item category set of the target warehouse, obtaining a category classification information set. Second, the category classification information corresponding to the target item category is selected from the above category classification information set as the target category classification information. Wherein, the target item category is the item category in the above item category set. Then, based on the aforementioned target category classification information, the preset upper limit of the item turnover value rate, the average of the daily item turnover attribute values reaching the service level upper limit within the first preset time period, the unit inventory value, and the logistics value, the optimal service level information corresponding to the aforementioned target item category is generated. This allows the determination of the optimal service level for the aforementioned target item category. Next, based on the daily actual item turnover volume and daily predicted item turnover volume of the aforementioned target item category within the first preset time period, the prediction standard deviation corresponding to the aforementioned target item category is determined. Finally, based on the aforementioned optimal service level information, the aforementioned prediction standard deviation, the lead time of the aforementioned target item category within the first preset time period, the aforementioned booking interval of the aforementioned target item category, and the average of the daily predicted item turnover volume within the second preset time period, the safety stock quantity of the aforementioned target item category is generated. Therefore, by using the forecast standard deviation to determine the safety stock level instead of the average daily actual goods turnover, the prediction algorithm, considering multiple dimensions and having stronger predictive basis, achieves better prediction results than directly using the average daily actual goods turnover. This leads to higher accuracy in determining the safety stock level and reduces waste of transportation and warehouse resources. Next, based on the aforementioned safety stock level, a target safety stock level for the target item category is determined. Finally, in response to the determination that the existing inventory level of the target item category in the target warehouse is less than the aforementioned safety stock level, the relevant goods dispatching equipment is controlled to perform replenishment operations for the target item category based on the existing inventory level and the target safety stock level. This improves the accuracy of the safety stock level and reduces waste of transportation and warehouse resources. Attached Figure Description
[0015] The above and other features, advantages, and aspects of the embodiments of this disclosure will become more apparent from the accompanying drawings and the following detailed description. Throughout the drawings, the same or similar reference numerals denote the same or similar elements. It should be understood that the drawings are schematic, and elements are not necessarily drawn to scale.
[0016] Figure 1 This is a flowchart of some embodiments of the item scheduling equipment control method according to the present disclosure;
[0017] Figure 2 These are schematic diagrams illustrating the structure of some embodiments of the item dispatching equipment control device according to this disclosure;
[0018] Figure 3 This is a schematic diagram of the structure of an electronic device suitable for implementing some embodiments of the present disclosure. Detailed Implementation
[0019] Embodiments of this disclosure will now be described in more detail with reference to the accompanying drawings. While some embodiments of this disclosure are shown in the drawings, it should be understood that this disclosure can be implemented in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of this disclosure. It should be understood that the accompanying drawings and embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of protection of this disclosure.
[0020] It should also be noted that, for ease of description, only the parts relevant to the invention are shown in the accompanying drawings. Unless otherwise specified, the embodiments and features described in this disclosure can be combined with each other.
[0021] It should be noted that the concepts of "first" and "second" mentioned in this disclosure are used only to distinguish different devices, modules or units, and are not used to limit the order of functions performed by these devices, modules or units or their interdependencies.
[0022] It should be noted that the terms "a" and "a plurality of" used in this disclosure are illustrative rather than restrictive, and those skilled in the art should understand that, unless otherwise expressly indicated in the context, they should be understood as "one or more".
[0023] The names of messages or information exchanged between multiple devices in the embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of such messages or information.
[0024] This disclosure will now be described in detail with reference to the accompanying drawings and embodiments.
[0025] Figure 1A flow 100 of some embodiments of an item scheduling device control method according to the present disclosure is shown. The item scheduling device control method includes the following steps:
[0026] Step 101: Determine the category classification information for each item category in the item category set of the target warehouse to obtain the category classification information set.
[0027] In some embodiments, the executing entity (e.g., a computing device) of the item scheduling device control method can determine the category classification information of each item category in the item category set of the target warehouse, thereby obtaining a category classification information set. The target warehouse can be any warehouse in different regions. The item categories in the item category set can be the categories of items stored in the target warehouse.
[0028] In some optional implementations of certain embodiments, the aforementioned execution entity may determine the category classification information of the item category through the following steps:
[0029] The first step is to perform a primary classification process on the above item categories to obtain the corresponding primary classification results. This primary classification process can be ABC classification (Activity Based Classification, Pareto analysis). The primary classification results can be category A, category B, or category C.
[0030] The second step involves performing a second classification process on the aforementioned item categories to obtain the corresponding second classification results. This second classification process can be the XYZ classification method. The resulting second classification can be of category X, category Y, or category Z.
[0031] The third step involves generating category classification information corresponding to the aforementioned item categories based on the first and second classification results. This category classification information represents the classification category of the aforementioned item categories. In practice, the category classification information can be the classification category of the aforementioned item categories. For example, the category classification information can be AX, AY, AZ, BX, BY, BZ, CX, CY, or CZ.
[0032] Step 102: Select the category classification information corresponding to the target item category from the category classification information set as the target category classification information.
[0033] In some embodiments, the executing entity may select the category classification information corresponding to the target item category from the category classification information set as the target category classification information. The target item category can be any item category in the item category set.
[0034] Step 103: Based on the target category classification information, the preset upper limit of the item circulation value rate, the average value of the item circulation attribute values of each day that reaches the upper limit of the service level within the first preset time period, the unit inventory value and the logistics value, generate the optimal service level information corresponding to the target item category.
[0035] In some embodiments, the executing entity can generate optimal service level information corresponding to the target item category based on the target category classification information, the preset upper limit of the item turnover value rate of the target item category, the average value of the daily item turnover attribute values that reach the upper limit of the service level within a first preset time period of the target item category, the unit inventory value of the target item category, and the logistics value of the target item category. The optimal service level information can be the optimal service level corresponding to the target item category. The service level can be a percentage that meets user needs. For example, the service level can be the quantity supplied over the entire period divided by the demand over the entire period. The preset upper limit of the item turnover value rate can be the maximum value that needs to be paid for each item's net value (e.g., the maximum cost of profit per item, i.e., the upper limit of the sales cost rate). The average value of the daily item turnover attribute values that reach the upper limit of the service level within the first preset time period can represent the average value of the daily item turnover attribute values (e.g., daily sales revenue) under the condition of no stockouts within the first preset time period. The first preset time period can be the past month or three months. The unit inventory value described above can represent the value required to store an item (e.g., unit inventory cost). The logistics value described above can represent the value required to transport an item (e.g., logistics cost).
[0036] In some optional implementations of certain embodiments, the execution entity can generate optimal service level information corresponding to the target item category by following these steps: based on the target category classification information, the preset upper limit of the item turnover value rate, the average of the daily item turnover attribute values that reach the service level upper limit within a first preset time period, the unit inventory value, and the logistics value.
[0037] The first step is to determine the upper and lower limits of the service level corresponding to the target item category based on the aforementioned target category classification information. In practice, firstly, the implementing entity can determine the service level range corresponding to the target item category based on the pre-defined service level ranges for each item category. Then, the upper and lower limits of the aforementioned range are determined as the upper and lower limits of the service level corresponding to the target item category. For example, if the service level range for category AZ is [95%, 99%], then the corresponding upper limit of the service level is 99%, and the lower limit is 95%. If the service level range for category CY is [50%, 80%], then the corresponding upper limit of the service level is 80%, and the lower limit is 50%.
[0038] The second step is to determine the upper and lower limits of the significance level based on the upper and lower limits of the service level corresponding to the target item category. In practice, the implementing entity can determine the lower limit of the significance level as the difference between 1 and the upper limit of the service level, and the upper limit of the significance level as the difference between 1 and the lower limit of the service level. For example, the upper limit of the significance level for the AZ category is 0.05, and the lower limit is 0.01. The upper limit of the significance level for the CY category is 0.5, and the lower limit is 0.2.
[0039] The third step involves generating the optimal significance level based on the upper and lower limits of the significance level, the preset upper limit of the value rate of goods circulation, the average value of the daily goods circulation attributes when the service level reaches the upper limit within the first preset time period, the unit inventory value, and the logistics value.
[0040] In practice, the aforementioned implementing entity can generate the optimal significance level corresponding to the target item category using the following formula:
[0041]
[0042] Where α represents the significance level. Cost represents the total cost. min Cost represents the minimum total cost. stock Cost represents the value per unit of inventory. delivery This represents the value of logistics. SaleAmt represents the average value of the daily item circulation attributes when the service level reaches its upper limit within the first preset time period mentioned above. α min This represents the lower limit of the significance level corresponding to the aforementioned target species. α max This represents the upper limit of the significance level corresponding to the above target species. threshold This indicates the preset upper limit of the turnover value rate of the above-mentioned items. SS indicates the safety stock level of the above-mentioned target species.
[0043] The above formula can be used to characterize the significance level at which the total cost is minimized under constraints as the optimal significance level.
[0044] SS can be expressed by the following formula:
[0045]
[0046] Where SS represents the safety stock level for the aforementioned target item category. Z α μ represents the safety factor corresponding to a service level of 1-α. VLT This represents the average lead time for the aforementioned target item category within the first preset time period. R represents the booking interval. σ d This represents the standard deviation of the prediction. μ d This represents the average daily predicted goods turnover within the second preset time period. σ VLT This represents the standard deviation of the lead time for the aforementioned target item category within the first preset time period. The lead time can be the time interval between issuing a replenishment request and the arrival of the replenished goods. The number of replenishments for the aforementioned target item category within the first preset time period can be multiple, therefore there can be multiple lead times. The booking interval can represent the number of days between orders. For example, if goods are ordered every Friday, the booking interval is 3 days on Tuesday and 2 days on Wednesday. The second preset time period can be a future period. For example, the second preset time period can be the next 7 days.
[0047] σ d This can be expressed by the following formula:
[0048]
[0049] Where, σ d This represents the prediction standard deviation corresponding to the above target item category. i This represents the predicted daily turnover of goods on day i. i This represents the actual daily turnover of goods on day i. n represents the number of days included in the first preset time period (usually taken as 28).
[0050] Fourth, based on the aforementioned optimal salience level, generate the optimal service level information corresponding to the aforementioned target item category. In practice, the executing entity can determine the difference between 1 and the aforementioned optimal salience level as the optimal service level information corresponding to the aforementioned target item category.
[0051] Step 104: Determine the prediction standard deviation corresponding to the target item category based on the daily actual item turnover and daily predicted item turnover within the first preset time period.
[0052] In some embodiments, the executing entity can determine the prediction standard deviation corresponding to the target item category based on the daily actual item turnover and the daily predicted item turnover within the first preset time period. The daily actual item turnover can represent the actual item turnover (e.g., daily sales volume) of the target item category on a certain day within the first preset time period. The daily predicted item turnover can represent the predicted item turnover (e.g., predicted daily sales volume) of the target item category on a certain day within the first preset time period. The prediction algorithm for determining the daily predicted item turnover can include, but is not limited to, one of the following: linear regression, random forest, XGBoost (eXtremeGradient Boosting), and LightGBM (Light Gradient Boosting Machine).
[0053] In practice, the implementing entity can determine the prediction standard deviation corresponding to the above target item category using the following formula:
[0054]
[0055] Where, σ d This represents the prediction standard deviation corresponding to the above target item category. i This represents the predicted daily turnover of goods on day i. i This represents the actual daily turnover of goods on day i. n represents the number of days included in the first preset time period (usually taken as 28).
[0056] Step 105: Generate the safety stock of the target item category based on the optimal service level information, the forecast standard deviation, the lead time of the target item category within the first preset time period, the booking interval of the target item category, and the average daily forecast item turnover within the second preset time period.
[0057] In some embodiments, the executing entity may generate a safety stock of the target item category based on the optimal service level information, the forecast standard deviation, the lead time of the target item category within the first preset time period, the booking interval of the target item category, and the average daily forecast item turnover of the target item category within the second preset time period.
[0058] In practice, the aforementioned implementing entities can generate the safety stock level for the aforementioned target item categories using the following formula:
[0059]
[0060] Where SS represents the safety stock level for the aforementioned target item category. Z αμ represents the safety factor corresponding to a service level of 1-α. VLT σ represents the average lead time for the aforementioned target item category within the first preset time period. R represents the aforementioned booking interval. d This represents the standard deviation of the above predictions. μ d This represents the average daily predicted goods turnover within the second preset time period mentioned above. σ VLT This represents the standard deviation of the lead time for the aforementioned target item category within the first preset time period.
[0061] Step 106: Determine the target safety stock level for the target item category based on the safety stock level.
[0062] In some embodiments, the aforementioned implementing entity may determine the target safety stock quantity for the aforementioned target item category based on the aforementioned safety stock quantity.
[0063] In some optional implementations of certain embodiments, the executing entity may determine the safety stock quantity as the target safety stock quantity for the target item category in response to determining that the target item category is a non-short-shelf-life item category. The non-short-shelf-life item category may be a category of items with a long shelf life (e.g., a shelf life exceeding 7 days). For example, the non-short-shelf-life item category may be bowls, toilet paper, clothing, etc.
[0064] In some optional implementations of certain embodiments, the aforementioned executing entity may further determine the target safety stock level for the aforementioned target item category through the following steps:
[0065] The first step, in response to determining that the target item category is a short-shelf-life item category, is to generate a short-shelf-life safety stock quantity for the target item category based on its shelf life and the average daily predicted item turnover within the second preset time period. The short-shelf-life item category can be a category of items with a short shelf life (e.g., a shelf life of no more than 7 days). For example, the short-shelf-life item category could be items like cakes.
[0066] In practice, the aforementioned implementing entities can determine the short-shelf safety stock level for the aforementioned target item categories using the following formula:
[0067]
[0068] Where C represents the short-shelf-life safety stock level of the aforementioned target item category. lifedays represents the shelf life. predavg represents the average daily predicted item turnover within the aforementioned second preset time period. Indicates to Round down.
[0069] The second step is to determine the target safety stock level for the target item category based on the aforementioned safety stock level and the aforementioned short-shelf-life safety stock level.
[0070] The first and second steps and related content described above, as an inventive point of this disclosure, solve the third technical problem mentioned in the background art: "Using the same method to determine the safety stock level for all items, but because different items have different shelf lives, items with shorter shelf lives will expire quickly, so it is necessary to control the upper limit of the safety stock level, which leads to low accuracy in determining the safety stock level of different items using the same method, resulting in waste of transportation and warehouse resources." The factors leading to low accuracy in safety stock levels and significant waste of transportation and warehouse resources are often as follows: using the same method to determine the safety stock level for all items, but because different items have different shelf lives, items with shorter shelf lives will expire quickly, so it is necessary to control the upper limit of the safety stock level, which leads to low accuracy in determining the safety stock level of different items using the same method, resulting in waste of transportation and warehouse resources. Therefore, this disclosure, targeting the short shelf life of short-shelf-life items, not only determines the safety stock level for short-shelf-life items but also determines the short-shelf-life safety stock level. Then, an appropriate safety stock level is selected from the existing safety stock level and the short-shelf-life safety stock level to control the upper limit of the safety stock level for short-shelf-life items, thereby reducing losses caused by the shelf life of these items. This improves the accuracy of the safety stock level for short-shelf-life items and reduces waste of transportation and warehouse resources.
[0071] Optionally, the aforementioned implementing entity may determine the target safety stock level for the aforementioned target item category based on the aforementioned safety stock level and the aforementioned short-shelf-life safety stock level through the following steps:
[0072] The first step is to determine, in response to the determination that the above safety stock quantity is less than the above short-shelf-life safety stock quantity, the above safety stock quantity is determined as the target safety stock quantity for the above target item category.
[0073] The second step is to determine, in response to the determination that the above-mentioned safety stock quantity is greater than the above-mentioned short-shelf-life safety stock quantity, to determine the above-mentioned short-shelf-life safety stock quantity as the target safety stock quantity for the above-mentioned target item category.
[0074] Step 107: In response to determining that the existing inventory of the target item category in the target warehouse is less than the safety stock, control the associated item dispatching equipment to perform a replenishment operation for the target item category based on the existing inventory and the target safety stock.
[0075] In some embodiments, the executing entity may, in response to determining that the existing inventory of the target item category in the target warehouse is less than the safety stock, control an associated item dispatching device to perform a replenishment operation for the target item category based on the existing inventory and the target safety stock.
[0076] In some optional implementations of certain embodiments, the execution entity may control an associated item dispatching device to perform a replenishment operation for the target item category based on the existing inventory level and the target safety stock level through the following steps:
[0077] The first step is to determine the replenishment quantity based on the difference between the target safety stock level and the existing stock level.
[0078] The second step involves controlling the associated goods dispatching equipment to transport goods from the main warehouse to the target warehouse according to the aforementioned replenishment quantity and the target item category. The main warehouse can be a warehouse used to transport goods to branch warehouses in various regions. For example, if the replenishment quantity is 100 items, the executing entity controls the associated goods dispatching equipment to transport 100 items of the target item category from the main warehouse to the target warehouse.
[0079] The above embodiments of this disclosure have the following beneficial effects: the item scheduling equipment control method of some embodiments of this disclosure can improve the accuracy of safety stock and reduce the waste of transportation and warehouse resources. Specifically, the reasons for the low accuracy of safety stock and the large waste of transportation and warehouse resources are as follows: First, there is no clear and detailed plan for determining the service level, resulting in low accuracy of safety stock. When the predicted safety stock is low, multiple transportations are required, leading to waste of transportation resources. When the predicted safety stock is high, too many items are stored in the warehouse, leading to waste of warehouse resources. Second, directly using the average daily actual item turnover as the predicted value results in a relatively singular prediction basis, leading to poor prediction accuracy, thereby causing waste of transportation and warehouse resources. Based on this, the item scheduling equipment control method of some embodiments of this disclosure first determines the category classification information of each item category in the item category set of the target warehouse, obtaining a category classification information set. Second, the category classification information corresponding to the target item category is selected from the above category classification information set as the target category classification information. Wherein, the target item category is the item category in the above item category set. Then, based on the aforementioned target category classification information, the preset upper limit of the item turnover value rate, the average of the daily item turnover attribute values reaching the service level upper limit within the first preset time period, the unit inventory value, and the logistics value, the optimal service level information corresponding to the aforementioned target item category is generated. This allows the determination of the optimal service level for the aforementioned target item category. Next, based on the daily actual item turnover volume and daily predicted item turnover volume of the aforementioned target item category within the first preset time period, the prediction standard deviation corresponding to the aforementioned target item category is determined. Finally, based on the aforementioned optimal service level information, the aforementioned prediction standard deviation, the lead time of the aforementioned target item category within the first preset time period, the aforementioned booking interval of the aforementioned target item category, and the average of the daily predicted item turnover volume within the second preset time period, the safety stock quantity of the aforementioned target item category is generated. Therefore, by using the forecast standard deviation to determine the safety stock level instead of the average daily actual goods turnover, the prediction algorithm, considering multiple dimensions and having stronger predictive basis, achieves better prediction results than directly using the average daily actual goods turnover. This leads to higher accuracy in determining the safety stock level and reduces waste of transportation and warehouse resources. Next, based on the aforementioned safety stock level, a target safety stock level for the target item category is determined. Finally, in response to the determination that the existing inventory level of the target item category in the target warehouse is less than the aforementioned safety stock level, the relevant goods dispatching equipment is controlled to perform replenishment operations for the target item category based on the existing inventory level and the target safety stock level. This improves the accuracy of the safety stock level and reduces waste of transportation and warehouse resources.
[0080] Further reference Figure 2 As an implementation of the methods shown in the above figures, this disclosure provides some embodiments of an item scheduling equipment control device, which are similar to... Figure 1 Corresponding to the method embodiments shown, the device can be specifically applied to various electronic devices.
[0081] like Figure 2 As shown, the item scheduling equipment control device 200 in some embodiments includes: a first determining unit 201, a selecting unit 202, a first generating unit 203, a second determining unit 204, a second generating unit 205, a third determining unit 206, and a control unit 207. The first determining unit 201 is configured to determine the category classification information of each item category in the item category set of the target warehouse, obtaining a category classification information set; the selecting unit 202 is configured to select the category classification information corresponding to the target item category from the category classification information set as the target category classification information, wherein the target item category is an item category in the item category set; the first generating unit 203 is configured to generate the optimal service level information corresponding to the target item category based on the target category classification information, a preset upper limit value for item turnover value rate, the average value of item turnover attribute values of each day reaching the service level upper limit value within a first preset time period, unit inventory value, and logistics value; the second determining unit 204 is configured to determine the daily actual item turnover of the target item category within the first preset time period. The first generation unit 205 is configured to determine the forecast standard deviation corresponding to the target item category based on the above-mentioned optimal service level information, the above-mentioned forecast standard deviation, the lead time of the target item category within the first preset time period, the booking interval of the target item category, and the average of the daily forecast item turnover within the second preset time period; the second generation unit 206 is configured to determine the target safety stock quantity of the target item category based on the above-mentioned safety stock quantity; and the third determination unit 207 is configured to control the associated item scheduling equipment to perform a replenishment operation for the target item category in response to determining that the existing inventory quantity of the target item category in the target warehouse is less than the above-mentioned safety stock quantity, based on the existing inventory quantity and the above-mentioned target safety stock quantity.
[0082] It is understandable that the units described in the device 200 are related to the reference. Figure 1 The steps in the described method correspond to each other. Therefore, the operations, features, and beneficial effects described above for the method also apply to the device 200 and the units contained therein, and will not be repeated here.
[0083] The following is for reference. Figure 3It shows a schematic diagram of the structure of an electronic device (e.g., a computing device) 300 suitable for implementing some embodiments of the present disclosure. Figure 3 The electronic device shown is merely an example and should not be construed as limiting the functionality and scope of the embodiments of this disclosure.
[0084] like Figure 3 As shown, the electronic device 300 may include a processing unit (e.g., a central processing unit, a graphics processing unit, etc.) 301, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 302 or a program loaded from a storage device 308 into a random access memory (RAM) 303. The RAM 303 also stores various programs and data required for the operation of the electronic device 300. The processing unit 301, ROM 302, and RAM 303 are interconnected via a bus 304. An input / output (I / O) interface 305 is also connected to the bus 304.
[0085] Typically, the following devices can be connected to I / O interface 305: input devices 306 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; output devices 307 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; storage devices 308 including, for example, magnetic tapes, hard disks, etc.; and communication devices 309. Communication device 309 allows electronic device 300 to communicate wirelessly or wiredly with other devices to exchange data. Although Figure 3 An electronic device 300 with various devices is shown; however, it should be understood that it is not required to implement or possess all of the devices shown. More or fewer devices may be implemented or possessed alternatively. Figure 3 Each box shown can represent a device or multiple devices as needed.
[0086] In particular, according to some embodiments of this disclosure, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, some embodiments of this disclosure include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication device 309, or installed from storage device 308, or installed from ROM 302. When the computer program is executed by processing device 301, it performs the functions defined in the methods of some embodiments of this disclosure.
[0087] It should be noted that, in some embodiments of this disclosure, the computer-readable medium may be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. 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 a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In some embodiments of this disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In some embodiments of this disclosure, 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. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium can be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to: wires, optical fibers, RF (radio frequency), etc., or any suitable combination thereof.
[0088] In some implementations, clients and servers can communicate using any currently known or future-developed network protocol such as HTTP (Hypertext Transfer Protocol) and can interconnect with digital data communication (e.g., communication networks) of any form or medium. Examples of communication networks include local area networks (“LANs”), wide area networks (“WANs”), the Internet (e.g., the Internet of Things), and peer-to-peer networks (e.g., ad hoc peer-to-peer networks), as well as any currently known or future-developed networks.
[0089] The aforementioned computer-readable medium may be included in the aforementioned electronic device; or it may exist independently and not assembled into the electronic device. The aforementioned computer-readable medium carries one or more programs, which, when executed by the electronic device, cause the electronic device to: determine the category classification information of each item category in the set of item categories in the target warehouse, obtaining a set of category classification information; select the category classification information corresponding to the target item category from the set of category classification information as the target category classification information, wherein the target item category is an item category in the set of item categories; generate optimal service level information corresponding to the target item category based on the target category classification information, a preset upper limit for item turnover value rate, the average daily item turnover attribute values reaching the service level upper limit within a first preset time period, unit inventory value, and logistics value; and generate optimal service level information corresponding to the target item category based on the first preset time period. Within the specified time period, the daily actual and predicted daily turnover of the target item category are used to determine the forecast standard deviation corresponding to the target item category. Based on the optimal service level information, the forecast standard deviation, the lead time of the target item category within the first preset time period, the booking interval of the target item category, and the average daily predicted turnover of each of the second preset time periods, a safety stock quantity for the target item category is generated. Based on the safety stock quantity, a target safety stock quantity for the target item category is determined. In response to determining that the existing inventory of the target item category in the target warehouse is less than the safety stock quantity, the associated item scheduling equipment is controlled to perform a replenishment operation for the target item category based on the existing inventory quantity and the target safety stock quantity.
[0090] Computer program code for performing operations of some embodiments of this disclosure can be written in one or more programming languages or a combination thereof, including object-oriented programming languages such as Java, Smalltalk, and C++, and conventional procedural programming languages such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).
[0091] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.
[0092] The units described in some embodiments of this disclosure can be implemented in software or hardware. The described units can also be housed in a processor; for example, a processor may be described as including a first determining unit, a selecting unit, a first generating unit, a second determining unit, a second generating unit, a third determining unit, and a control unit. The names of these units do not necessarily limit the specific unit itself; for example, the first determining unit may also be described as "a unit that determines the category classification information of each item category in the set of item categories in a target warehouse, and obtains a set of category classification information."
[0093] The functions described above in this document can be performed, at least in part, by one or more hardware logic components. For example, exemplary types of hardware logic components that can be used, without limitation, include: Field Programmable Gate Arrays (FPGAs), Application-Specific Integrated Circuits (ASICs), Application Standard Products (ASSPs), System-on-Chip (SoCs), Complex Programmable Logic Devices (CPLDs), and so on.
[0094] Some embodiments of this disclosure also provide a computer program product, including a computer program that, when executed by a processor, implements any of the above-described item scheduling device control methods.
[0095] The above description is merely a selection of preferred embodiments of this disclosure and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of the invention involved in the embodiments of this disclosure is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the above-described inventive concept. For example, technical solutions formed by substituting the above-described features with (but not limited to) technical features with similar functions disclosed in the embodiments of this disclosure.
Claims
1. A method for controlling an item scheduling device, comprising: Determine the category classification information for each item category in the target warehouse's item category set to obtain a category classification information set; Select the category classification information corresponding to the target item category from the category classification information set as the target category classification information, wherein the target item category is the item category in the item category set; Based on the target category classification information, the preset upper limit of the item turnover value rate, the average value of each day's item turnover attribute value reaching the service level upper limit within the first preset time period, the unit inventory value, and the logistics value, the optimal service level information corresponding to the target item category is generated, including: generating the optimal salience level corresponding to the target item category using the following formula: ,in, Indicates the significance level. Represents the total cost. This represents the minimum total cost. Indicates the value per unit of inventory. Indicates the value of logistics. This represents the average value of the daily item circulation attributes when the service level reaches its upper limit within the first preset time period. This represents the lower limit of the significance level corresponding to the target species. This represents the upper limit of the significance level corresponding to the target species. This indicates the preset upper limit of the turnover value rate of the goods. The above formula represents the safety stock level of the target species, and the significance level at which the total cost is minimized under constraints is taken as the optimal significance level. Based on the optimal significance level, the optimal service level information corresponding to the target item category is generated. Based on the daily actual turnover and daily predicted turnover of the target item category within the first preset time period, determine the prediction standard deviation corresponding to the target item category; Based on the optimal service level information, the forecast standard deviation, the lead time of the target item category within the first preset time period, the booking interval of the target item category, and the average daily forecast item turnover within the second preset time period, a safety stock of the target item category is generated. Based on the safety stock level, determine the target safety stock level for the target item category; In response to determining that the existing inventory of the target item category in the target warehouse is less than the safety stock, the associated item dispatching equipment is controlled to perform a replenishment operation for the target item category based on the existing inventory and the target safety stock.
2. The method according to claim 1, wherein, The classification information of each item category in the set of item categories in the target warehouse is determined to obtain a set of classification information, including: For each item category in the set of item categories, perform the following steps: The item category is subjected to a first classification process to obtain the first classification result corresponding to the item category; The item category is subjected to a second classification process to obtain a second classification result corresponding to the item category; Based on the first classification result and the second classification result, generate category classification information corresponding to the item category; The generated category classification information is combined into a category classification information set.
3. The method according to claim 2, wherein, The upper and lower limits of the significance level are determined using the following steps: Based on the target category classification information, determine the upper and lower limits of the service level corresponding to the target item category; Based on the upper and lower limits of the service level corresponding to the target item category, the upper and lower limits of the salience level are determined.
4. The method according to claim 1, wherein, The step of controlling associated item dispatching equipment to perform replenishment operations for the target item category based on the existing inventory level and the target safety stock level includes: The difference between the target safety stock level and the existing stock level is determined as the replenishment quantity; The control system uses associated item dispatching equipment to transport goods from the main warehouse to the target warehouse according to the replenishment quantity and the target item category.
5. A control device for an item dispatching system, comprising: The first determining unit is configured to determine the category classification information of each item category in the set of item categories in the target warehouse, and obtain a set of category classification information; The selection unit is configured to select the category classification information corresponding to the target item category from the category classification information set as the target category classification information, wherein the target item category is the item category in the item category set; The first generation unit is configured to generate optimal service level information corresponding to the target item category based on the target category classification information, a preset upper limit for the item turnover value rate, the average of the daily item turnover attribute values that reach the service level upper limit within a first preset time period, the unit inventory value, and the logistics value. This includes generating the optimal salience level corresponding to the target item category using the following formula: ,in, Indicates the significance level. Represents the total cost. This represents the minimum total cost. Indicates the value per unit of inventory. Indicates the value of logistics. This represents the average value of the daily item circulation attributes when the service level reaches its upper limit within the first preset time period. This represents the lower limit of the significance level corresponding to the target species. This represents the upper limit of the significance level corresponding to the target species. This indicates the preset upper limit of the turnover value rate of the goods. The above formula represents the safety stock level of the target species, and the significance level at which the total cost is minimized under constraints is taken as the optimal significance level. Based on the optimal significance level, the optimal service level information corresponding to the target item category is generated. The second determining unit is configured to determine the prediction standard deviation corresponding to the target item category based on the daily actual item turnover and daily predicted item turnover of the target item category within the first preset time period. The second generation unit is configured to generate a safety stock of the target item category based on the optimal service level information, the prediction standard deviation, the lead time of the target item category within the first preset time period, the booking interval of the target item category, and the average of the predicted item turnover of each day within the second preset time period. The third determining unit is configured to determine the target safety stock quantity for the target item category based on the safety stock quantity. The control unit is configured to, in response to determining that the existing inventory of the target item category in the target warehouse is less than the safety stock, control an associated item dispatching device to perform a replenishment operation for the target item category based on the existing inventory and the target safety stock.
6. An electronic device, comprising: One or more processors; A storage device on which one or more programs are stored; When the one or more programs are executed by the one or more processors, the one or more processors implement the method as described in any one of claims 1-4.
7. A computer-readable medium having a computer program stored thereon, wherein, When the program is executed by the processor, it implements the method as described in any one of claims 1-4.
8. A computer program product comprising a computer program that, when executed by a processor, implements the method according to any one of claims 1-4.