Warehouse inventory management method and system

Abstract

The present invention relates to the field of warehouse management technology, and more specifically, the present invention relates to a warehouse inventory management method and system, including: obtaining the historical safety stock and historical daily sales and daily replenishment of inventory goods in the warehouse; calculating the volatility of the day, the volatility includes demand volatility and supply volatility, wherein the demand volatility is used to reflect the changing trend of daily sales over multiple consecutive days, and the demand volatility is used to reflect the changing trend of daily replenishment over multiple consecutive days, and constructing a historical volatility sequence. The present invention constructs the supply volatility sequence and the demand volatility sequence of the day according to the obtained joint cycle, calculates the matching degree with the sequence of the same length in the historical data, and uses the safety stock of the historical sequence with the largest matching degree as the safety stock of the day, which solves the problem that the traditional safety stock model cannot cope with the demand and supply fluctuations of non-normal distribution, thereby causing out-of-stock or backlog.

Description

Technical Field

[0001] The present invention relates to the technical field of warehouse management, and more specifically, to a warehouse inventory management method and system. Background Art

[0002] In modern logistics and supply chain management, warehouse inventory management is a crucial link. In traditional warehouse inventory management, enterprises usually rely on manual records, paper documents, manual verification and other methods to manage inventory, which is prone to data errors and cannot analyze inventory data, resulting in inventory backlogs or out-of-stock. With the development of information technology, enterprises use artificial intelligence and big data technology to analyze inventory data and predict inventory demand, and manage warehouses based on inventory demand and warehouse inventory.

[0003] In the related technology, for example, the Chinese patent application document with publication number CN107563705A discloses a system and method for analyzing the safety inventory and reordering of household appliances using big data, and calculating the safety inventory based on mathematical statistics models to achieve accurate quantity. It guides procurement and production to carry out accurate production planning, factory inventory, commercial inventory, and logistics distribution management, and provides early warning services and determination of reorder points in a timely and efficient manner. This improves the timeliness and accuracy of safety inventory and reorder determination, reduces inventory and improves inventory turnover, and avoids product out-of-stock.

[0004] The current safety stock models usually calculate safety stock based on certain statistical assumptions and static historical data. For example, demand fluctuations and supply cycle time must satisfy the normal distribution. However, in actual warehouse inventory management, the fixed safety stock setting calculated based on the standard deviation of demand may not be able to cope with non-normally distributed demand and supply fluctuations. Finally, the calculated safety stock may show the same situation, resulting in out-of-stock or inventory backlogs, which is inconvenient to manage the goods in the warehouse. Summary of the invention

[0005] The present invention provides a warehouse inventory management method and system, aiming to solve the problem that the fixed safety stock setting calculated based on the standard deviation of demand in the related art may not be able to cope with non-normally distributed demand and supply fluctuations, and the safety stock finally calculated may have the same situation, resulting in out-of-stock or inventory backlog problems.

[0006] In the first aspect, the present invention provides a warehouse inventory management method, which obtains the historical safety inventory and the historical daily sales and daily replenishment of the inventory goods in the warehouse; calculates the volatility of the day, wherein the volatility includes demand volatility and supply volatility, wherein the demand volatility is used to reflect the changing trend of the daily sales in a continuous number of days, and the demand volatility is used to reflect the changing trend of the daily replenishment in a continuous number of days, and constructs a historical volatility sequence; calculates the joint cycle of the historical volatility sequence, and uses the length of the joint cycle as the The historical volatility sequence is divided into a daily volatility subsequence and multiple historical volatility subsequences, and the matching degree between the daily volatility subsequence and each historical volatility subsequence is calculated. , the calculation formula is: ; In the formula, and are the volatility subsequences of the day. Demand volatility and Supply volatility, and are the historical volatility subsequences. Demand volatility and Supply volatility, is an exponential function with the natural constant e as the base; the historical volatility subsequence with the matching degree greater than the matching threshold is screened out, the historical safety stock corresponding to the date with the smallest difference with the daily sales volume is selected as the safety stock of the day, and the order point is calculated based on the safety stock of the day, and the warehouse inventory is managed with the order point.

[0007] The effect is: based on the obtained joint cycle, the supply volatility sequence and demand volatility sequence of the day are constructed, and the degree of matching is calculated with the sequence of the same length in the historical data. The safety stock based on the historical sequence with the largest matching degree is used as the safety stock for the day, which solves the problem that the traditional safety stock model cannot cope with non-normally distributed demand and supply fluctuations, resulting in shortages or backlogs.

[0008] Furthermore, the warehouse inventory management is performed based on the number of order points, including: determining whether it is necessary to replenish the stock based on a comparison result between the order point and the safety stock of the day; if the safety stock of the day is less than or equal to the order point, replenishing the stock; if the safety stock of the day is greater than the order point, no replenishment of the stock is required.

[0009] The effect is that the order point is compared with the safety stock of the day, and whether the goods need to be replenished is determined according to the comparison result, so as to better control the inventory of goods and ensure the normal sales of goods.

[0010] Furthermore, the daily demand volatility is calculated using the following formula: ; In the formula, Indicates the volatility of daily demand, reflecting the changing trend of daily sales volume over several consecutive days. Represents the total number of sample data, For the Daily sales volume, For the The average of daily sales from day to day, For the The standard deviation of sales volume from day to day; The cube of the ratio of the difference between the daily sales volume and the average value and the standard deviation is The trend of daily sales from day to day.

[0011] The effect is: based on the collected historical daily sales data, the daily demand volatility and supply volatility are calculated, and in the calculation process, corresponding weights are assigned according to the data at different times, so that the calculated results are more accurate, and reflect the direction of fluctuations and clarify the direction of change.

[0012] Furthermore, the supply volatility of the day is calculated using the following formula: ; In the formula, Indicates the volatility of the supply on the same day, reflecting the changing trend of daily replenishment over several consecutive days. Represents the total number of sample data, For the Daily replenishment quantity, For the The average of the daily replenishment quantity from day to day, For the The standard deviation of day-to-day replenishment quantities.

[0013] Furthermore, the calculation of the daily demand volatility also includes: The distance between the day and the current day is used as the weight. The trend of daily sales volume changes from day to day is weighted to obtain the daily demand volatility.

[0014] The effect is that the sales or replenishment data of dates further away from the current day are less relevant to the current data. The weighting of the trend of day-to-day sales volume or day-to-day replenishment volume improves the accuracy of the final calculation results.

[0015] Further, the order point is calculated, including: the order point is positively correlated with the average daily sales volume of all dates, the last purchase cycle, and the safety stock of the day.

[0016] Furthermore, the calculation method of the combined cycle includes: constructing a historical volatility sequence, wherein the historical volatility sequence includes a historical demand volatility sequence and a supply volatility sequence; using a multidimensional Fourier transform to calculate the cross spectral density between the historical demand volatility sequence and the supply volatility sequence, and selecting the frequency corresponding to the maximum cross spectral density. Calculate the joint period of two sequences, the joint period .

[0017] The effect is that the calculated joint cycle is a cycle with a strong correlation between the demand volatility series and the supply volatility series, which can reflect the changing trends of commodity sales and replenishment.

[0018] Furthermore, calculating the safety stock for the day includes: calculating the supply-demand balance of each day, wherein the supply-demand balance of each day and the difference between the supply volatility and the demand volatility of the day, and the difference between the daily sales volume and the daily replenishment volume are all negatively correlated; screening out a date with the same supply-demand balance as the day as the target date, and taking the average value of the safety stock corresponding to the target date as the safety stock for the day.

[0019] Furthermore, the supply and demand balance of each day is calculated using the following formula: ; In the formula, For the The daily supply and demand balance, For the Daily demand volatility, For the Daily supply volatility, and is the weight parameter, For the Daily sales volume, For the Daily supply.

[0020] In a second aspect of the present invention, there is also provided a warehouse inventory management system, comprising a processor and a memory, wherein the memory stores a computer program, and the processor executes the computer program to implement any of the above-described warehouse inventory management methods and systems.

[0021] Beneficial effects: The demand volatility and supply volatility of the day are calculated based on the collected historical daily sales data, and corresponding weights are assigned according to the data at different times during the calculation process, so that the calculated results are more accurate and reflect the direction of the fluctuation. Then, the multi-dimensional Fourier transform is used to calculate the joint cycle of historical supply volatility and demand volatility. According to the obtained joint cycle, the supply volatility sequence and demand volatility sequence of the day are constructed to calculate the matching degree with the sequence of the same length in the historical data. The safety stock based on the historical sequence with the largest matching degree is used as the safety stock of the day, which solves the problem that the traditional safety stock model cannot cope with non-normally distributed demand and supply fluctuations, resulting in out-of-stock or backlogs. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] The following detailed description is read with reference to the accompanying drawings, which illustrate several embodiments of the present invention in an exemplary and non-limiting manner, and in which like or corresponding reference numerals represent like or corresponding parts, wherein:

[0023] Figure 1 is a flowchart schematically illustrating obtaining the safety stock of the day according to an embodiment of the present invention;

[0024] Figure 2 It is a specific flow chart schematically showing the calculation of the safety stock of the day according to an embodiment of the present invention. DETAILED DESCRIPTION

[0025] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0026] The specific embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0027] like Figure 1 As shown, S101: Obtain the historical safety stock and historical sales volume and replenishment volume of the inventory goods in the warehouse.

[0028] In one embodiment, the current day safety stock and historical sales and replenishment of the inventory in the warehouse are obtained, wherein the historical sales and replenishment can be counted on a daily basis to obtain the historical daily sales and replenishment. For example, the safety stock on day Q is , the daily sales volume on the Qth day is , the daily replenishment quantity on the Qth day is .

[0029] S102: Calculate the volatility of the day.

[0030] In one embodiment, since the standard deviation of sales volume in different periods may be the same, the traditional safety stock model calculates the standard deviation of historical sales volume as the demand volatility of the product on the day. Although the standard deviation can evaluate the magnitude of the fluctuation range, it cannot reflect the direction of the fluctuation, resulting in the same calculation result of the safety stock volume in the upward and downward sales trends, resulting in inventory backlog or out-of-stock phenomenon. Therefore, the present invention calculates the volatility of the day based on the sales volume change rate and the sales volume standard deviation at different times. The volatility includes demand volatility and supply volatility, the demand volatility is used to reflect the changing trend of daily sales volume for multiple consecutive days, and the demand volatility is used to reflect the changing trend of daily replenishment volume for multiple consecutive days.

[0031] In one embodiment, the daily demand volatility is calculated using the following formula: ; In the formula, Indicates the volatility of daily demand, reflecting the changing trend of daily sales volume over several consecutive days. Represents the total number of sample data, For the Daily sales volume, For the The average of daily sales from day to day, For the The standard deviation of daily sales from day to day; Expressed as The trend of daily sales from day to day. When the value of is positive, the larger the value, the greater the probability of a significant increase in daily sales within the time interval, and the greater the volatility of daily demand. The bigger; When the value is negative, the smaller the value, the greater the probability that the daily sales volume will decrease significantly during the time interval, and the volatility of the daily demand It should be noted that the calculation method and principle of supply volatility are the same as the above method of calculating the volatility of demand for the day.

[0032] In one embodiment, the supply volatility of the day is calculated using the following formula: ; In the formula, Indicates the volatility of the supply on the same day, reflecting the changing trend of daily replenishment over several consecutive days. Represents the total number of sample data, For the Daily replenishment quantity, For the The average of the daily replenishment quantity from day to day, For the The standard deviation of day-to-day replenishment quantities.

[0033] In one embodiment, since the sales or replenishment data of dates farther from the current day have a lower reference value to the current data, the sales or replenishment data farther from the current day have a smaller impact on the calculation of the demand volatility and supply volatility of the current day. Therefore, when calculating the demand volatility and supply volatility of the current day, the sales or replenishment data of the first day can be used as the reference value. The distance between the day and the current day is used as the weight. The trend of day-to-day sales volume or day-to-day replenishment volume is weighted to obtain the daily demand volatility and supply volatility, which improves the accuracy of the calculation results.

[0034] In one embodiment, taking the daily demand volatility as an example, the weighted calculation formula is: , where represents the volatility of demand on the day, Represents the total number of sample data, For the Daily sales volume, For the The average of daily sales from day to day, For the The standard deviation of daily sales from day to day.

[0035] in, For the The weight of the trend of daily sales volume from day to day, when the The farther away from the current day, the The smaller the impact of the trend from day to day on the volatility of demand on that day, the smaller the weight. The closer the day is to the current day, the The greater the influence of the trend from day to day on the demand volatility of the day, the greater the weight. So far, the demand volatility and supply volatility of each day can be obtained, and the historical volatility sequence can be constructed, where the historical volatility sequence includes the historical demand volatility sequence and the historical supply volatility sequence. Exemplary, construct the historical demand volatility sequence: , construct the historical supply volatility series: , is the number of sample data and can be adjusted according to the specific implementation scenario.

[0036] S103: Calculate the current day's safety stock based on the difference between historical data and current day's volatility.

[0037] In one embodiment, due to the different life cycles and volatility distributions of different products, traditional safety stock models are usually calculated based on fixed parameters such as Z value, sales volume standard deviation and procurement cycle, which cannot adapt to the dynamic changes in demand and supply fluctuations, further resulting in the same situation in calculating safety stocks in the growth and decline periods of commodity sales, causing warehouse inventory backlogs or out-of-stock phenomena. Therefore, by matching the current day's demand volatility and supply volatility with historical data, a multi-dimensional Fourier transform is used to calculate the joint cycle of the historical demand volatility series and the historical supply volatility series to obtain a cycle length with a strong correlation. And the length of the joint cycle is used as The historical volatility sequence is divided into a current day volatility subsequence and multiple historical volatility subsequences, the matching degree between the current day volatility subsequence and each historical volatility subsequence is calculated, and the safety stock corresponding to the historical volatility subsequence with the largest matching degree is used as the safety stock for the current day.

[0038] like Figure 2 As shown, S1031: Calculate the joint period of the historical demand volatility series and the historical supply volatility series.

[0039] In one embodiment, the calculation method of the joint period includes: using a multi-dimensional Fourier transform to calculate the cross-spectral density between the historical demand volatility series and the historical supply volatility series, and selecting the frequency corresponding to the maximum cross-spectral density. Calculate the joint period of two sequences, the joint period . And the length of the joint cycle The historical volatility sequence is divided into a daily volatility subsequence and multiple historical volatility subsequences.

[0040] For example, the daily demand volatility subsequence: , is the length of the joint cycle, where is the intraday demand volatility, is the demand volatility of the previous day, It is before Daily demand volatility, daily supply volatility subsequence: , is the length of the joint cycle, is the intraday supply volatility, is the supply volatility of the previous day, It is before The historical volatility subsequences refer to the subsequences obtained by dividing the historical data according to the length of the joint cycle.

[0041] S1032: Calculate the matching degree between the current day's volatility subsequence and each historical volatility subsequence.

[0042] In one embodiment, the matching degree is calculated using the formula: ; In the formula, is the matching degree between the current day volatility subsequence and the historical volatility subsequence, and are the volatility subsequences of the day. Demand volatility and Supply volatility, and are the historical volatility subsequences. Demand volatility and Supply volatility, It is an exponential function with the natural constant e as its base.

[0043] S1033: Determine the safety stock for the day.

[0044] In one embodiment, the historical sequences whose matching degree is greater than the matching threshold are screened out, and the safety stock corresponding to the date with the smallest difference in daily sales volume is selected as the safety stock for the day. In this embodiment, the matching threshold is 0.9, and in other embodiments, the matching threshold can be 0.84 or 0.8, etc., which can be adjusted according to the specific implementation situation.

[0045] In one embodiment, the safety stock corresponding to the date with the smallest difference in daily sales volume is selected, and the following relationship must be satisfied: , where is the safety stock for the day, It represents the difference between the average daily sales volume of the historical series and the average daily sales volume of the current day. It satisfies the conditions The average value of the safety stock in the historical series, It is the matching degree between the current day volatility subsequence and the historical volatility subsequence.

[0046] In another embodiment, the following method is provided for calculating the safety stock of the day: the supply and demand balance of each day is calculated based on the historical supply volatility, demand volatility, warehouse inventory and safety stock, and the date with the same supply and demand balance as the day is selected as the target date, and the average value of the safety stock corresponding to the target date is used as the safety stock of the day. The calculation formula of the supply and demand balance is: ; In the formula, For the The daily supply and demand balance, For the Daily demand volatility, For the Daily supply volatility, and is the weight parameter, For the Daily sales volume, For the Daily supply.

[0047] In one embodiment, the average value of the safety stock corresponding to the target date is used as the safety stock of the day, which needs to satisfy the following relationship: ;in, is the safety stock for the day, It is the quantity where the supply and demand balance of the historical date is the same as the supply and demand balance of the current day. It is day's safety stock.

[0048] S1034: Calculate the order point based on the safety stock of the day, and manage the warehouse inventory according to the number of the order points.

[0049] In one embodiment, the order point is calculated, wherein the order point is positively correlated with the average daily sales volume of all dates, the last purchase cycle, and the safety stock of the day. The formula is: ,in, is the order point, is the historical daily sales average. is the purchasing cycle at the last moment, It is the safety stock of the day. It should be noted that the calculation of order point belongs to the existing method and will not be described in detail here.

[0050] Specifically, based on the comparison result between the order point and the safety stock of the day, determine whether it is necessary to replenish the stock; if the safety stock of the day is less than or equal to the order point, replenish the stock; if the safety stock of the day is greater than the order point, there is no need to replenish the stock.

[0051] Through the above steps, the demand volatility and supply volatility of the day are calculated based on the collected historical daily sales data, and the corresponding weights are assigned according to the data at different times during the calculation process, so that the calculated results are more accurate and reflect the direction of the fluctuation. Then, the multi-dimensional Fourier transform is used to calculate the joint cycle of historical supply volatility and demand volatility. According to the obtained joint cycle, the supply volatility sequence and demand volatility sequence of the day are constructed to calculate the matching degree with the sequence of the same length in the historical data. The safety stock based on the historical sequence with the largest matching degree is used as the safety stock of the day, which solves the problem that the traditional safety stock model cannot cope with non-normally distributed demand and supply fluctuations, resulting in out-of-stock or backlogs.

[0052] The present invention also provides a warehouse inventory management system, the system comprising a processor and a memory, the memory storing computer program instructions, and when the computer program instructions are executed by the processor, a warehouse inventory management method according to the first aspect of the present invention is implemented.

[0053] The system also includes other components familiar to those skilled in the art, such as a communication bus and a communication interface, whose configuration and functions are known in the art and thus will not be described in detail here.

[0054] In the present invention, the aforementioned memory may be any tangible medium containing or storing a program, which may be used by or in combination with an instruction execution system, apparatus or device. For example, a computer-readable storage medium may be any appropriate magnetic storage medium or magneto-optical storage medium, such as a resistive random access memory RRAM (Resistive Random Access Memory), a dynamic random access memory DRAM (Dynamic Random Access Memory), a static random access memory SRAM (Static Random-Access Memory), an enhanced dynamic random access memory EDRAM (Enhanced Dynamic Random Access Memory), a high-bandwidth memory HBM (High-Bandwidth Memory), a hybrid memory cube HMC (Hybrid Memory Cube), etc., or any other medium that can be used to store the required information and can be accessed by an application, a module, or both. Any such computer storage medium may be part of a device or accessible or connectable to a device. Any application or module described in the present invention may be implemented by computer-readable / executable instructions stored or otherwise maintained by such a computer-readable medium.

[0055] In the description of this specification, "plurality" or "several" means at least two, such as two, three or more, etc., unless otherwise clearly and specifically defined.

[0056] The technical features of the above-described embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above-described embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0057] The above-mentioned embodiments only express several implementation methods of the present invention, and the description is relatively specific and detailed, but it cannot be understood as limiting the scope of the patent application. It should be pointed out that for ordinary technicians in this field, several modifications and improvements can be made without departing from the concept of the present invention, which all belong to the protection scope of the present invention.

Claims

1. A warehouse inventory management method, characterized in that: include: Obtain the historical safety stock, daily sales volume, and daily replenishment volume of the inventory in the warehouse; Calculate the volatility of the day, which includes demand volatility and supply volatility, where: Calculate the daily demand volatility using the formula: ； In the formula, Indicates the volatility of daily demand, reflecting the changing trend of daily sales volume over several consecutive days. Represents the total number of sample data, For the Daily sales volume, For the The average of daily sales from day to day, For the The standard deviation of daily sales from day to day; Calculate the supply volatility for the day using the formula: ； In the formula, Indicates the volatility of the supply on the same day, reflecting the changing trend of daily replenishment over several consecutive days. Represents the total number of sample data, For the Daily replenishment quantity, For the The average of the daily replenishment quantity from day to day, For the The standard deviation of day-to-day replenishment quantities; Constructing a historical volatility series, wherein the historical volatility series includes a historical demand volatility series and a historical supply volatility series; Calculating the joint period of the historical volatility series, including: calculating the cross spectral density between the historical demand volatility series and the historical supply volatility series using a multidimensional Fourier transform, and selecting the frequency corresponding to the maximum cross spectral density Calculate the joint period of two sequences, the joint period ; The length of the joint cycle Dividing the historical volatility sequence into a daily volatility subsequence and a plurality of historical volatility subsequences; Calculate the matching degree between the current day volatility subsequence and each historical volatility subsequence , the calculation formula is: ； In the formula, and are the volatility subsequences of the day. Demand volatility and Supply volatility, and are the historical volatility subsequences. Demand volatility and Supply volatility, The natural constant An exponential function with base ; The historical volatility subsequences whose matching degree is greater than the matching threshold are screened out, the historical safety stock corresponding to the date with the smallest difference with the daily sales volume is selected as the safety stock for the day, and the order point is calculated based on the safety stock for the day, and the warehouse inventory is managed with the order point.

2. The warehouse inventory management method according to claim 1, characterized in that: Warehouse inventory management based on the order point, including: Determine whether to replenish the stock based on the comparison between the order point and the safety stock of the day; If the safety stock for the day is less than or equal to the order point, restock the goods; If the safety stock for the day in question is greater than the order point, there is no need to replenish the stock.

3. The warehouse inventory management method according to claim 1, characterized in that: Calculate the volatility of demand for the day, including: The first The distance between the day and the current day is used as the weight. The trend of daily sales volume changes from day to day is weighted to obtain the daily demand volatility.

4. The warehouse inventory management method according to claim 1, characterized in that: Calculate order points, including: The order point is positively correlated with the average daily sales volume of all dates, the last procurement cycle, and the safety stock of the day.

5. The warehouse inventory management method according to claim 1, characterized in that: Calculate the safety stock for the day, including: Calculate the supply-demand balance of each day, wherein the supply-demand balance of each day is negatively correlated with the difference between the supply volatility and the demand volatility of the day, and the difference between the daily sales volume and the daily replenishment volume of the day; A date with the same supply-demand balance as that of the current day is selected as the target date, and the average value of the safety stock corresponding to the target date is used as the safety stock of the current day.

6. The warehouse inventory management method according to claim 5, characterized in that: Calculate the supply and demand balance of each day, the calculation formula is: ； In the formula, For the The daily supply and demand balance, For the Daily demand volatility, For the Daily supply volatility, and is the weight parameter, For the Daily sales volume, For the The daily replenishment quantity for the day.

7. A warehouse inventory management system, comprising a processor and a memory, characterized in that: The memory stores a computer program, and the processor executes the computer program to implement the warehouse inventory management method according to any one of claims 1 to 6.

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