CN114742505A - Inventory control method and device - Google Patents

Inventory control method and device Download PDF

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CN114742505A
CN114742505A CN202210414914.7A CN202210414914A CN114742505A CN 114742505 A CN114742505 A CN 114742505A CN 202210414914 A CN202210414914 A CN 202210414914A CN 114742505 A CN114742505 A CN 114742505A
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蒋开均
罗仕梅
王远松
初伟
李勇昌
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Abstract

The disclosure provides an inventory control method and device, and relates to the technical field of inventory control. Wherein, the method comprises the following steps: acquiring a historical inventory sequence of a target object aiming at a target product before an observation time sequence, and processing the historical inventory sequence to obtain an initial stock of the target product in each unit observation time in the observation time sequence; determining the inventory influence factor of the target product at the current observation time, and determining the inventory of the target product at the current observation time according to the inventory influence factor of the target product at the current observation time and the initial inventory of the target product at the observation time sequence. By the method, the inventory of the target product of the target object can be accurately determined, and the inventory control efficiency is improved.

Description

Inventory control method and device
Technical Field
The present disclosure relates to the field of inventory control technologies, and in particular, to an inventory control method and apparatus.
Background
Product inventory and age management at retail terminal stores is an important task for the traditional off-line retail industry. If the product inventory is too high, the product is likely to be stale in the age, even the risk of the product being in the temporary period and overdue appears, and the loss is caused to stores; if the product inventory is too low, on the one hand, the purchase demand can not be met very well, inconvenience is brought to a purchaser, and on the other hand, the store needs to enter goods for many times, logistics resources are wasted, and logistics efficiency is reduced.
Inventory forecasting is an important link in inventory control. In the related art, the accuracy of inventory prediction is not high, which brings inconvenience to inventory control.
Disclosure of Invention
One technical problem to be solved by the present disclosure is to provide a solution that can accurately determine the inventory of a target product and improve the efficiency of inventory control.
According to a first aspect of the present disclosure, an inventory control method is provided, including: acquiring a historical stocking amount sequence of a target object aiming at a target product before an observation time sequence, wherein the observation time sequence comprises at least one unit of observation time; processing the historical stocking amount sequence to obtain an initial stock of the target product in each unit observation time in the observation time sequence; determining an inventory impact factor of the target product at a current observation time, wherein the current observation time is a unit observation time of the observation time series; and determining the inventory of the target product at the current observation time according to the inventory influence factor of the target product at the current observation time and the initial inventory of the target product at the observation time sequence.
In some embodiments, further comprising: generating inventory control information according to the inventory of the target product at the current observation time; and sending the inventory control information to a terminal corresponding to the target object, wherein the inventory control information is used for prompting the target object to carry out inventory control on the target product.
In some embodiments, generating inventory control information based on the inventory of the target product at the current observation time includes at least one of: generating first inventory control information under the condition that the inventory of the target product at the current observation time is greater than a first inventory threshold value, wherein the first inventory control information is used for indicating the target object to carry out inventory cleaning on the target product; and generating second inventory control information under the condition that the inventory of the target product of the target object at the current observation time is less than a second inventory threshold, wherein the second inventory control information is used for indicating the target object to replenish the target product, and the second inventory threshold is less than the first inventory threshold.
In some embodiments, an inventory threshold storage table is queried to determine the first inventory threshold and the second inventory threshold based on at least one of the identification of the target object and the identification of the target product.
In some embodiments, the inventory impact factor for the target product at the current observation time includes at least one of a stock quantity delta indicator value, a number of stock turnaround days, and an average amount of stock consumed per stock interval for the target product at the current observation time.
In some embodiments, the inventory of the target product at the current observation time is positively correlated with the inventory increment index value; the inventory of the target product at the current observation time is in negative correlation with the number of days of inventory turnover; the inventory of the target product at the current observation time is positively correlated with the inventory consumed at the average time interval of each stock.
In some embodiments, the inventory of the target product at the current observation time is determined according to the following formula:
Figure BDA0003605309360000021
wherein the content of the first and second substances,
Figure BDA0003605309360000022
for the stock of the target product at the current observation time, alpha and beta are adjustment coefficients, K0For initial inventory, Δ S is the inventory increment index value,
Figure BDA0003605309360000023
d is the number of days of stock turnover, which is the average stock consumed per stocking interval.
In some embodiments, the determining the inventory impact factor for the target product at the current observation time comprises: and determining a monthly ring ratio goods intake difference value of the target product according to the goods intake of the target product at the current observation time and the goods intake of the target product on the same day of the last month, and taking the monthly ring ratio goods intake difference value as the goods intake increment index value.
In some embodiments, the determining the inventory impact factor for the target product at the current observation time comprises: and determining the number of inventory turnover days according to the initial inventory of the target product in the observation time sequence, the historical inventory of the target product in a preset time period before the current observation time and the duration of the preset time period.
In some embodiments, the number of inventory turnover days is positively correlated with the initial inventory and the duration of the preset time period, and the number of inventory turnover days is negatively correlated with the historical inventory of the target product over a preset time period prior to the current observation time.
In some embodiments, the determining the inventory impact factor for the target product at the current observation time comprises: and determining the average inventory consumed at each time of the target products at the stocking interval according to the historical stocking amount of the target products in a preset time period before the current observation time and the historical stocking times of the target products in the preset time period.
In some embodiments, said processing said historical sequence of inventory amounts to obtain an initial inventory of said target product per unit of observed time in said sequence of observed times comprises: decomposing the historical cargo volume sequence according to an empirical mode decomposition algorithm to obtain an eigenmode function sequence; and processing the eigenmode function sequence according to the inventory determination model to obtain the initial inventory of the target product in the observation time sequence.
According to a second aspect of the present disclosure, there is provided an inventory control device including: an acquisition module configured to acquire a historical inventory quantity sequence of a target object for a target product prior to an observation time sequence, wherein the observation time sequence includes at least one unit of observation time; a first inventory determination module configured to process the historical inventory sequence to obtain an initial inventory of the target product for each unit of observation time in the observation time sequence; an influence factor determination module configured to determine an inventory influence factor for the target product at a current observation time, wherein the current observation time is a unit observation time in the observation time series; a second inventory determination module configured to determine an inventory of the target product at the current observation time based on the inventory impact factor of the target product at the current observation time and an initial inventory of the target product at the observation time series.
According to a third aspect of the present disclosure, there is also provided an inventory control device, comprising: a memory; and a processor coupled to the memory, the processor configured to perform the inventory control method as described above based on instructions stored in the memory.
According to a fourth aspect of the present disclosure, a computer-readable storage medium is also proposed, on which computer program instructions are stored, which instructions, when executed by a processor, implement the inventory control method described above.
Compared with the related art, in the embodiment of the disclosure, the historical inventory quantity sequence of the target product before the observation time sequence is obtained, the historical inventory quantity sequence is processed to obtain the initial inventory of the target product at each unit observation time in the observation time sequence, and the inventory of the target product at the current observation time is determined according to the inventory influence factor of the target product at the current observation time and the initial inventory, so that the inventory of the target product of the target object can be accurately determined, and the inventory control efficiency of the target product is further improved.
Other features of the present disclosure and advantages thereof will become apparent from the following detailed description of exemplary embodiments thereof, which proceeds with reference to the accompanying drawings.
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The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments of the disclosure and together with the description, serve to explain the principles of the disclosure.
The present disclosure may be more clearly understood from the following detailed description, taken with reference to the accompanying drawings, in which:
FIG. 1 is a flow diagram of an inventory control method according to some embodiments of the present disclosure.
FIG. 2 is a flow diagram of an inventory control method according to further embodiments of the present disclosure.
FIG. 3 is a schematic illustration of effects of inventory control methods according to some embodiments of the disclosure.
FIG. 4 is a schematic diagram of an inventory control device according to some embodiments of the present disclosure.
FIG. 5 is a schematic diagram of an inventory control device according to some embodiments of the present disclosure.
FIG. 6 is a schematic diagram of an inventory control device according to still further embodiments of the present disclosure.
FIG. 7 is a block diagram of a computer system according to some embodiments of the present disclosure.
Detailed Description
Various exemplary embodiments of the present disclosure will now be described in detail with reference to the accompanying drawings. It should be noted that: the relative arrangement of the components and steps, the numerical expressions, and numerical values set forth in these embodiments do not limit the scope of the present disclosure unless specifically stated otherwise.
Meanwhile, it should be understood that the sizes of the respective portions shown in the drawings are not drawn in an actual proportional relationship for the convenience of description.
The following description of at least one exemplary embodiment is merely illustrative in nature and is in no way intended to limit the disclosure, its application, or uses.
Techniques, methods, and apparatus known to those of ordinary skill in the relevant art may not be discussed in detail but are intended to be part of the specification where appropriate.
In all examples shown and discussed herein, any particular value should be construed as merely illustrative, and not limiting. Thus, other examples of the exemplary embodiments may have different values.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be discussed further in subsequent figures.
For the purpose of promoting a better understanding of the objects, aspects and advantages of the present disclosure, reference is made to the following detailed description taken in conjunction with the accompanying drawings.
FIG. 1 is a flow diagram of an inventory control method according to some embodiments of the present disclosure. As shown in fig. 1, the inventory control method of the embodiment of the present disclosure includes:
step S110: and acquiring a historical stocking amount sequence of the target object aiming at the target product before the observation time sequence.
Illustratively, the target object is an end store directly facing the consumer, such as a supermarket, convenience store, grocery store, or hotel, etc. The target object may be one terminal store or a plurality of terminal stores. For example, a plurality of terminal stores are selected from the plurality of terminal stores according to at least one of the type and the geographical location of the terminal stores, and the selected terminal stores are set as target objects, and product inventory control is performed for each target object.
Illustratively, the target product is a collection of products of the same category or of multiple categories. For example, the target product is a product set of water products, wherein the product set comprises water products with specification capacities of 380ml, 550ml, 1.5L, 5L, 12L water and the like. For example, the target product is a product set of water and beverage categories.
Wherein the observation time series includes at least one unit observation time. For example, the observation time series is 7 days, two weeks, or one month, etc., and the unit observation time is one day. For example, the observation time is 180 days, and the unit observation time is two days.
Wherein the historical shipment volume sequence includes a plurality of historical shipment volume data. For example, the historical inventory data includes inventory data for a target subject for six consecutive months of an aquatic product prior to the observation time series.
In some embodiments, the database is queried to obtain a sequence of historical inventories of the target object for the target product prior to observing the time sequence.
In other embodiments, an inventory determination request is received, and a sequence of historical inventories of the target object for the target product prior to the observation time sequence is obtained from the inventory determination request.
Step S120: the historical inventory sequence is processed to obtain an initial inventory of the target product for each unit of observation time in the observation time sequence.
In some embodiments, the historical inventory sequence is decomposed according to an Empirical Mode Decomposition (EMD) algorithm to obtain a sequence of eigenmode functions; and processing the eigenmode function sequence according to the inventory determination model to obtain the initial inventory of the target product in the observation time sequence.
The EMD algorithm decomposes signals according to the time scale characteristics of data, and does not need to set any basis function in advance. The method has the advantages of processing non-stationary and non-linear data. Three assumptions for the EMD algorithm are as follows:
j1: the data has at least two extreme values, a maximum value and a minimum value;
j2: the local time domain characteristics of the data are uniquely determined by the time scale between extreme points;
j3: if the data has no extreme points but has inflection points, the data can be differentiated one or more times to obtain an extreme value, and then integrated to obtain the eigenmode function sequence.
In some embodiments, decomposing the sequence of historical inventory amounts according to an empirical mode decomposition algorithm to obtain a sequence of eigenmode functions comprises: step 1.1 to step 1.5.
Step 1.1: historical inventory sequence K through cubic spline interpolation method1(t) fitting the extreme points to determine maxima and minima, and determining a first average envelope from the maxima and minima.
Illustratively, the determination is made according to the following formula
Figure BDA0003605309360000071
Wherein U (t) is a maximum value, L (t) is a minimum value, M1(t) is the first-order average envelope.
Step 1.2: will history the sequence of the amount of the goods K1(t) and the first average envelope M1(t) subtracting to obtain a new sequence H1(t)。
In step 1.2, the calculation formula is as follows:
H1(t)＝K1(t)-M1(t)
step 1.3: judgment of H1(t) whether or not to reject the Intrinsic Mode Function (IMF) component criterion assumption, if reject, use H1(t) in place of K1(t) repeating steps 1.1 and 1.2 until an Intrinsic Mode Function (IMF) component criterion assumption is satisfied.
The IMF component standard assumptions, i.e., IMF criteria, include: zero and extreme points in the sequence are equal or at most 1; the mean of the maximum and minimum values are equal and 0.
When the sequence in step 1.3 meets the IMF criterion for the first time, the sequence is marked as IMF1(t) and go to step 1.4.
Step 1.4: IMF sequence1(t) and KtSubtracting to obtain the residual sequence R1(t)。
In step 1.4, the calculation formula is as follows:
R1(t)＝IMF1(t)-Kt
step 1.5: with R1(t) in place of KtRepeating the steps 1.1 to 1.4 until a plurality of IMF components and the last 1 inseparable sequence are obtained and marked as a trend item Rn(t)。
Finally, the historical inventory sequence is decomposed into IMF components and a trend term, as follows:
Figure BDA0003605309360000072
wherein the content of the first and second substances,
Figure BDA0003605309360000073
is the sum of all IMF components.
After decomposing the historical inventory sequence according to steps 1.1 to 1.5, the eigenmode function sequence is processed according to the inventory determination model to obtain an initial inventory of the target product for each unit of observation time in the observation time sequence. Illustratively, the inventory determination model is a time series model, such as a Back Propagation (BP) neural network model, a Support Vector Machine (SVM) model, or the like.
In the embodiment of the disclosure, the historical inventory sequence is decomposed according to the empirical mode decomposition algorithm, and the eigenmode function sequence obtained by decomposition is processed according to the inventory determination model, so that the unstable product inventory can be well predicted, and the accuracy of the determined product inventory is improved.
In some embodiments, before step S120, the method further includes: the data is scrubbed to obtain a historical inventory sequence.
Illustratively, data cleansing is performed according to one or more of the following rules:
1. the historical shipping data of the selected customers and product categories need to satisfy three assumptions of EMD.
2. The selected clients are clients which cooperate normally and have regular visit records of service personnel, and false clients or clients which have no visit records of service personnel for a long time are excluded.
3. In the selected goods input data of the client, order information of non-superior dealers for direct supply, such as cross-superior units, cross-provincial and municipal regional goods mixing and the like, is eliminated from the goods input sources.
4. For customer order information with return records for the corresponding product category, the return amount is subtracted from the input amount.
Through data cleaning, the interference of noise data on an analysis result can be eliminated or unnecessary data defaults are caused, and the accuracy of the determined inventory is improved.
Step S130: and determining the inventory influence factor of the target product at the current observation time.
Wherein the current observation time is a unit observation time in the observation time series.
In some embodiments, the inventory impact factor for the target product at the current observation time includes at least one of a stock quantity delta indicator value, a number of stock turnaround days, and an average amount of stock consumed per stock interval for the target product at the current observation time.
For example, the inventory impact factor of the target product at the current observation time includes an inventory increment index value of the target product at the current observation time, the number of days of stock turnover, and the average inventory consumed per inventory interval.
In some embodiments, the target product's inventory increment index value at the current observation time is determined according to the following manner: and determining a monthly ring ratio goods intake difference value of the target product according to the goods intake of the target product at the current observation time and the goods intake of the target product on the same day of the last month, and taking the monthly ring ratio goods intake difference value as the goods intake increment index value.
The calculation formula of the monthly cycle specific cargo intake difference value of the target product is as follows:
ΔS＝Sj1-Sj0
wherein S isj1Is a target productCurrent time of observation, quantity of items, Sj0The target product is the shipment on the same day of the last month, and j is the number in the observation time series, or the number of days of the rolling date of observation.
In some embodiments, the number of inventory turnaround days is determined according to the following: and determining the number of turnover days of the inventory according to the initial inventory of the target product in the observation time sequence, the historical inventory of the target product in a preset time period before the current observation time and the duration of the preset time period.
In some embodiments, the number of inventory turnaround days is positively correlated with the initial inventory and the duration of the preset time period, and the number of inventory turnaround days is negatively correlated with the historical inventory of the target product over the preset time period prior to the current observation time.
For example, the calculation formula for the number of days of the stock cycle is as follows:
Figure BDA0003605309360000091
wherein, K0For initial inventory, S180The historical goods input amount of the target product in a preset time period before the current observation time is provided, specifically, the number of containers of the target product in the last 6 months of the terminal store is provided, and 180 is the duration of the preset time period.
In the above example, setting the preset time period to 180 days is comprehensively evaluated according to the company category business system. Options to assess inclusion were: length of expiration date for the selected category; and if the product terminal product is not put in the market once in more than 6 months, the terminal store is determined to be sold. It is noted that setting the preset time period to 180 days is merely exemplary. In specific implementation, the preset time period can be determined according to comprehensive evaluation of various factors.
In some embodiments, the average inventory consumed per shipment interval for the target product is determined according to the following: and determining the average inventory consumed at each time of the target product at the stock-in interval according to the historical stock-in amount of the target product in a preset time period before the current observation time and the historical stock-in times of the target product in the preset time period.
For example, the calculation formula of the average inventory consumed per stock interval of the target product is as follows:
Figure BDA0003605309360000101
wherein the content of the first and second substances,
Figure BDA0003605309360000102
inventory consumed for the target product average per shipment interval, NtAnd the total goods feeding times of the terminal customer stores in the current observation time.
Step S140: and determining the inventory of the target product at the current observation time according to the inventory influence factor of the target product at the current observation time and the initial inventory of the target product at the observation time sequence.
In some embodiments, the inventory of the target product at the current observation time is positively correlated with the inventory increment index value; the inventory of the target product at the current observation time is in negative correlation with the number of days of turnover of the inventory; the inventory of the target product at the current observation time is positively correlated with the inventory consumed in the average each-time stock-in interval.
Illustratively, the inventory of the target product at the current observation time is determined according to the following formula:
Figure BDA0003605309360000103
wherein the content of the first and second substances,
Figure BDA0003605309360000104
for the stock of the target product at the current observation time, alpha and beta are adjustment coefficients, K0For initial inventory, Δ S is the value of the incremental index of the quantity of goods delivered,
Figure BDA0003605309360000105
d is the number of days of stock turnover, which is the average stock consumed per stocking interval.
The value range of alpha is 0-1, the value range of the terminal customer random error coefficient beta is seasonal time period deviation coefficient, and the terminal customer random error coefficient alpha is caused by legal holidays, weekends and terminal store open-door business hours.
In some embodiments, the values of α, β are determined by the above manner: the method comprises the steps of setting a plurality of alpha and beta combinations through computer programming and an exhaustion method, forecasting inventory under each alpha and beta combination, calculating root mean square error according to inventory forecasting results and real inventory, and selecting the alpha and beta combination corresponding to the minimum value of the root mean square error as the optimal alpha and beta.
In other embodiments, a genetic-neural network (GABP) model is trained based on the order data of the end store in recent years, and optimal α, β are obtained by continuously adjusting the parameter weights of the neural network model. It should be noted that other parameter optimization selection algorithms known to those skilled in the art may also be used to determine the optimal α and β, and the method of parameter solution is not limited by the present invention.
In the embodiment of the disclosure, the inventory of the target product of the target object can be accurately determined through the steps, and the effectiveness of inventory control for the target product is further improved. Moreover, compared with the related art, the embodiment of the disclosure reduces the requirement on the scale of the training sample through the above method, and improves the applicability of the method.
FIG. 2 is a flow diagram of an inventory control method according to further embodiments of the present disclosure. As shown in fig. 2, the inventory control method of the embodiment of the present disclosure includes:
step S110: and acquiring a historical stocking amount sequence of the target object aiming at the target product before the observation time sequence.
Wherein the observation time series includes a plurality of unit observation times. For example, the observation time series includes 30 days, and the unit observation time is 1 day.
Wherein the historical shipment volume sequence includes a plurality of historical shipment volume data. For example, the historical inventory data includes inventory data for a target subject for six consecutive months of an aquatic product prior to the observation time series.
In some embodiments, the database is queried to obtain a sequence of historical inventories of the target object for the target product prior to observing the time sequence.
In other embodiments, an inventory determination request is received, and a sequence of historical inventories of the target object for the target product prior to the observation time sequence is obtained from the inventory determination request.
Step S120: the historical inventory sequence is processed to obtain an initial inventory of the target product for each unit of observation time in the observation time sequence.
In some embodiments, the historical inventory sequence is decomposed according to an Empirical Mode Decomposition (EMD) algorithm to obtain a sequence of eigenmode functions; and processing the eigenmode function sequence according to the inventory determination model to obtain the initial inventory of the target product in each unit observation time in the observation time sequence.
In the embodiment of the disclosure, the historical inventory sequence is decomposed according to the empirical mode decomposition algorithm, and the eigenmode function sequence obtained by decomposition is processed according to the inventory determination model, so that the unstable product inventory can be well predicted, and the accuracy of the determined product inventory is improved.
In some embodiments, before step S120, the method further includes: the data is scrubbed to obtain a historical inventory sequence.
Through data cleaning, the interference of noise data on an analysis result can be eliminated or unnecessary data defaults are caused, and the accuracy of the determined inventory is improved.
Step S130: determining the inventory impact factor of the target product at the current observation time.
Wherein the current observation time is a unit observation time in the observation time series.
In some embodiments, the inventory impact factor for the target product at the current observation time includes at least one of a stock quantity delta indicator value, a number of stock turnaround days, and an average amount of stock consumed per stock interval for the target product at the current observation time.
For example, the inventory impact factor of the target product at the current observation time includes an inventory increment index value of the target product at the current observation time, the number of days of stock turnover, and the average inventory consumed per inventory interval.
Step S140: and determining the inventory of the target product at the current observation time according to the inventory influence factor of the target product at the current observation time and the initial inventory of the target product in the observation time sequence.
In some embodiments, the inventory of the target product at the current observation time is positively correlated with the inventory increment index value; the inventory of the target product at the current observation time is in negative correlation with the number of days of turnover of the inventory; the inventory of the target product at the current observation time is positively correlated with the inventory consumed in the average each-time stock-in interval.
Illustratively, the inventory of the target product at the current observation time is determined according to the following formula:
Figure BDA0003605309360000121
wherein, the first and the second end of the pipe are connected with each other,
Figure BDA0003605309360000122
for the stock of the target product at the current observation time, alpha and beta are adjustment coefficients, K0For initial inventory, Δ S is the inventory increment index value,
Figure BDA0003605309360000123
d is the number of days of stock turnover, which is the average stock consumed at each stocking interval.
Step S150: and generating inventory control information according to the inventory of the target product at the current observation time.
In some embodiments, the target object is a plurality of stores, and after determining the inventory for each store, inventory control is performed for the inventory of each store, so as to generate inventory control information.
In other embodiments, the target object is a plurality of stores, and after determining the inventory of each store, the inventory of each store is collected, and unified inventory control is performed according to the collected total inventory to generate inventory control information.
The inventory control information is used for prompting the target object to perform inventory control on the target product.
In some embodiments, the first inventory control information is generated where the inventory of the target product at the current observation time is greater than a first inventory threshold. The first inventory control information is used for indicating the target object to carry out inventory cleaning on the target product.
For example, when the target product is a water product in a supermarket, the stock of the water product at the current observation time is determined to be 120 boxes through steps S110 to S140, the first stock threshold of the water product in the supermarket is 100 boxes, and the comparison shows that the real-time stock of the water product is greater than the first stock threshold, so as to generate first stock control information. Illustratively, the first inventory control information is generated as "the inventory of water products is 120 boxes, the inventory is too high, and please clean the inventory in time".
In some embodiments, the second inventory control information is generated in the event that the inventory of the target product of the target object at the current observation time is less than a second inventory threshold. The second inventory control information is used for indicating the target object to replenish the target product, wherein the second inventory threshold is smaller than the first inventory threshold.
For example, when the target product is a water product in a supermarket, the stock of the water product at the current observation time is determined to be 10 boxes through steps S110 to S140, the first stock threshold of the water product in the supermarket is 20 boxes, and the comparison shows that the real-time stock of the water product is smaller than the second stock threshold, so as to generate the second stock control information. Illustratively, the second inventory control information is generated as "the inventory of the water products is 10 boxes, the inventory is too low, and please replenish the goods in time".
In some embodiments, the inventory threshold storage table is queried to determine a first inventory threshold and a second inventory threshold based on at least one of an identification of a target object and an identification of the target product.
For example, an inventory threshold value storage table is set in advance for a plurality of objects and a plurality of products, wherein the inventory threshold value storage table stores a first inventory threshold value and a second inventory threshold value set for the plurality of products of the plurality of objects. When step S150 is executed, the inventory threshold storage table is queried according to the identifier of the target object and the identifier of the target product, so as to obtain a first inventory threshold and a second inventory threshold corresponding to the target product of the target object.
In the embodiment of the disclosure, by setting the corresponding first inventory threshold and second inventory threshold for different target objects and different target products, the flexibility of product inventory control and the effectiveness of inventory control can be improved.
Step S160: and sending the inventory control information to a terminal corresponding to the target object.
In the embodiment of the disclosure, the inventory of the target product of the target object can be accurately determined through the steps, and efficient and accurate inventory control can be performed for different target objects. Moreover, compared with the related art, the method and the device have the advantages that the initial inventory is roughly determined, and then the inventory predicted value is determined based on the inventory influence factor of the current observation time, so that the requirement on the scale of the training sample is reduced, and the applicability of the method is improved.
FIG. 3 is a schematic diagram illustrating the effects of inventory control methods according to some embodiments of the present disclosure. Fig. 3 shows the error results of the predicted inventory value and the actual inventory value. In fig. 3, the actual inventory value of the product category for the selected 10 terminal stores is shown, and it is found that the accuracy of the inventory determined by the inventory control method is very high and the Root Mean Square Error (RMSE) value is about 80% by comparing with the inventory determined by the inventory control method in some embodiments of the present disclosure.
FIG. 4 is a schematic diagram of an inventory control device according to some embodiments of the present disclosure. As shown in fig. 4, the inventory control device of the embodiment of the present disclosure includes: an acquisition module 410, a first inventory determination module 420, an impact factor determination module 430, and a second inventory determination module 440.
An obtaining module 410 configured to obtain a historical inventory sequence of the target object for the target product prior to the observation time sequence.
Illustratively, the target object is an end store directly facing the consumer, such as a supermarket, convenience store, grocery store, or hotel, etc. The target object may be one terminal store or a plurality of terminal stores. For example, a plurality of terminal stores are selected from the plurality of terminal stores according to at least one of the type and the geographical location of the terminal stores, and the selected terminal stores are set as target objects, and product inventory control is performed for each target object.
Illustratively, the target product is a collection of products of the same category or of multiple categories. For example, the target product is a product set of water categories, wherein the product set includes water products with specification capacities of 380ml, 550ml, 1.5L, 5L, and 12L of water. For example, the target product is a product set of water and beverage categories.
Wherein the observation time series includes at least one unit observation time. For example, the observation time series is 7 days, two weeks, or one month, etc., and the unit observation time is one day.
Wherein the historical shipment volume sequence includes a plurality of historical shipment volume data. For example, the historical inventory data includes inventory data for a target subject for six consecutive months of an aquatic product prior to the observation time series.
In some embodiments, the acquisition module 410 queries a database to acquire a sequence of historical inventories of the target object for the target product prior to the observation time sequence.
In other embodiments, the obtaining module 410 receives the inventory determination request, obtains from the inventory determination request a sequence of historical inventories of the target object for the target product prior to the observation time sequence.
A first inventory determination module 420 configured to process the sequence of historical inventory amounts to obtain an initial inventory of the target product for each unit of observed time in the sequence of observed times.
In some embodiments, the first inventory determination module 420 decomposes the historical inventory sequence according to an Empirical Mode Decomposition (EMD) algorithm to obtain an eigenmode function sequence; and processing the eigenmode function sequence according to the inventory determination model to obtain the initial inventory of the target product in the observation time sequence.
The EMD algorithm decomposes signals according to the time scale characteristics of data, and does not need to set any basis function in advance. The method has the advantages of processing non-stationary and non-linear data. Three assumptions for the EMD algorithm are as follows:
j1: the data has at least two extreme values, a maximum value and a minimum value;
j2: the local time domain characteristic of the data is uniquely determined by the time scale between extreme points;
j3: if the data has no extreme points but has inflection points, the data can be differentiated one or more times to obtain an extreme value, and then integrated to obtain the eigenmode function sequence.
An impact factor determination module 430 configured to determine an inventory impact factor for the target product at the current observation time.
Wherein the current observation time is a unit observation time in the observation time series.
In some embodiments, the inventory impact factor of the target product at the current observation time includes at least one of a stock quantity increment indicator value of the target product at the current observation time, a number of stock turnaround days, and an average amount of stock consumed per stock interval.
For example, the inventory impact factor of the target product at the current observation time includes an inventory increment index value of the target product at the current observation time, the number of days of stock turnover, and the average inventory consumed per inventory interval.
In some embodiments, the impact factor determination module 430 determines the inventory increment index value for the target product at the current observation time according to the following: and determining a monthly ring ratio goods intake difference value of the target product according to the goods intake of the target product at the current observation time and the goods intake of the target product on the same day of the last month, and taking the monthly ring ratio goods intake difference value as the goods intake increment index value.
In some embodiments, the impact factor determination module 430 determines the number of inventory turnaround days according to: and determining the number of days of stock turnover according to the initial stock of the target product in the observation time sequence, the historical stock quantity of the target product in a preset time period before the current observation time and the duration of the preset time period.
In some embodiments, the impact factor determination module 430 determines the average amount of inventory consumed per inter-stock interval for the target product according to the following: and determining the average inventory consumed at each time of the target product at the stock-in interval according to the historical stock-in amount of the target product in a preset time period before the current observation time and the historical stock-in times of the target product in the preset time period.
The second inventory determination module 440 is configured to determine an inventory of the target product at the current observation time according to the inventory impact factor of the target product at the current observation time and the initial inventory of the target product at the observation time series.
In some embodiments, the inventory of the target product at the current observation time is positively correlated with the inventory increment index value; the inventory of the target product at the current observation time is in negative correlation with the number of days of turnover of the inventory; the inventory of the target product at the current observation time is positively correlated with the inventory consumed in the average each-time stock-in interval.
Illustratively, the second inventory determination module 440 determines the inventory of the target product at the current observation time according to the following formula:
Figure BDA0003605309360000161
wherein the content of the first and second substances,
Figure BDA0003605309360000162
for the stock of the target product at the current observation time, alpha and beta are adjustment coefficients, K0For initial inventory, Δ S is the value of the incremental index of the quantity of goods delivered,
Figure BDA0003605309360000163
d is the number of days of stock turnover, which is the average stock consumed at each stocking interval.
In the embodiment of the disclosure, the inventory of the target product of the target object can be accurately determined by the above device, and thus the effectiveness of inventory control and the efficiency of inventory control for the target product are improved.
FIG. 5 is a schematic diagram of an inventory control device according to some embodiments of the present disclosure. As shown in fig. 5, the inventory control device of the embodiment of the present disclosure includes: an acquisition module 410, a first inventory determination module 420, an impact factor determination module 430, a second inventory determination module 440, a generation module 450, and a transmission module 460.
An obtaining module 410 configured to obtain a historical inventory sequence of the target object for the target product prior to the observation time sequence.
Wherein the historical shipment volume sequence includes a plurality of historical shipment volume data. For example, the historical inventory data includes inventory data for a target subject for six consecutive months of an aquatic product prior to the observation time series.
In some embodiments, the database is queried to obtain a sequence of historical inventories of the target object for the target product prior to observing the time sequence.
In other embodiments, an inventory determination request is received, and a sequence of historical inventories of the target object for the target product prior to the observation time sequence is obtained from the inventory determination request.
A first inventory determination module 420 configured to process the sequence of historical inventory amounts to obtain an initial inventory of the target product for each unit of observed time in the sequence of observed times.
In some embodiments, the first inventory determination module 420 decomposes the historical inventory sequence according to an Empirical Mode Decomposition (EMD) algorithm to obtain an eigenmode function sequence; and processing the eigenmode function sequence according to the inventory determination model to obtain the initial inventory of the target product in the observation time sequence.
An impact factor determination module 430 configured to determine an inventory impact factor for the target product at the current observation time.
Wherein the current observation time is a unit observation time in the observation time series.
In some embodiments, the inventory impact factor for the target product at the current observation time includes at least one of a stock quantity delta indicator value, a number of stock turnaround days, and an average amount of stock consumed per stock interval for the target product at the current observation time.
For example, the inventory impact factor of the target product at the current observation time includes an inventory increment index value of the target product at the current observation time, the number of days of stock turnover, and the average inventory consumed per inventory interval.
The second inventory determination module 440 is configured to determine an inventory of the target product at the current observation time according to the inventory impact factor of the target product at the current observation time and the initial inventory of the target product at the observation time series.
In some embodiments, the inventory of the target product at the current observation time is positively correlated with the inventory increment index value; the inventory of the target product at the current observation time is in negative correlation with the number of days of turnover of the inventory; the inventory of the target product at the current observation time is positively correlated with the inventory consumed in the average each-time stock-in interval.
Illustratively, the second inventory determination module 440 determines the inventory of the target product at the current observation time according to the following formula:
Figure BDA0003605309360000181
wherein, the first and the second end of the pipe are connected with each other,
Figure BDA0003605309360000182
for the stock of the target product at the current observation time, alpha and beta are adjustment coefficients, K0For initial inventory,. DELTA.SThe increment index value of the cargo intake quantity,
Figure BDA0003605309360000183
d is the number of days of stock turnover, which is the average stock consumed per stocking interval.
The generating module 450 is configured to generate the inventory control information according to the inventory of the target product at the current observation time.
In some embodiments, the target object is a plurality of stores, and after determining the inventory for each store, inventory control is performed for the inventory of each store, so as to generate inventory control information.
In other embodiments, the target object is a plurality of stores, and after determining the inventory of each store, the inventory of each store is collected, and unified inventory control is performed according to the collected total inventory to generate inventory control information.
The inventory control information is used for prompting the target object to perform inventory control on the target product.
In some embodiments, the generation module 450 generates the first inventory control information if the inventory of the target product at the current observation time is greater than a first inventory threshold. The first inventory control information is used for indicating the target object to carry out inventory cleaning on the target product.
For example, when the target product is a water product in a supermarket, the stock of the water product at the current observation time is determined to be 120 boxes through steps S110 to S140, the first stock threshold of the water product in the supermarket is 100 boxes, and the comparison shows that the real-time stock of the water product is greater than the first stock threshold, so as to generate first stock control information. Illustratively, the first inventory control information is generated as "the inventory of water products is 120 boxes, the inventory is too high, and please clean the inventory in time".
In some embodiments, the generation module 450 generates the second inventory control information if the inventory of the target product of the target object at the current observation time is less than the second inventory threshold. The second inventory control information is used for indicating the target object to replenish the target product, wherein the second inventory threshold is smaller than the first inventory threshold.
For example, when the target product is a water product in a supermarket, the inventory of the water product at the current observation time is determined to be 10 boxes through steps S110 to S140, the first inventory threshold of the water product in the supermarket is 20 boxes, and the comparison shows that the real-time inventory of the water product is smaller than the second inventory threshold, so as to generate second inventory control information. Illustratively, the second inventory control information is generated as "the inventory of the water products is 10 boxes, the inventory is too low, and the user needs to replenish the goods in time".
In some embodiments, the generation module 450 queries the inventory threshold storage table to determine the first inventory threshold and the second inventory threshold based on at least one of an identification of the target object and an identification of the target product.
For example, an inventory threshold value storage table is set in advance for a plurality of objects and a plurality of products, wherein the inventory threshold value storage table stores a first inventory threshold value and a second inventory threshold value set for the plurality of products of the plurality of objects. The generating module 450 queries the inventory threshold storage table according to the identifier of the target object and the identifier of the target product to obtain a first inventory threshold and a second inventory threshold corresponding to the target product of the target object.
In the embodiment of the disclosure, by setting the corresponding first inventory threshold and second inventory threshold for different target objects and different target products, the flexibility of product inventory control and the effectiveness of inventory control can be improved.
A sending module 460 configured to send the inventory control information to a terminal corresponding to the target object.
In the embodiment of the disclosure, the device can accurately determine the inventory of the target product of the target object, and perform efficient and accurate inventory control for different target objects. Moreover, compared with the related art, the device disclosed by the embodiment of the disclosure roughly determines the initial inventory, and then determines the inventory predicted value based on the inventory influence factor of the current observation time, so that the requirement on the scale of the training sample is reduced, and the applicability of inventory control is improved.
FIG. 6 is a block diagram illustrating an inventory control device according to further embodiments of the present disclosure.
As shown in fig. 6, the inventory control device 600 includes a memory 610; and a processor 620 coupled to the memory 610. The memory 610 is used for storing instructions for performing the corresponding embodiments of the inventory control method. The processor 620 is configured to perform the inventory control method in any of the embodiments of the present disclosure based on instructions stored in the memory 610.
FIG. 7 is a block diagram illustrating a computer system for implementing some embodiments of the present disclosure.
As shown in FIG. 7, computer system 700 may be embodied in the form of a general purpose computing device. Computer system 700 includes a memory 710, a processor 720, and a bus 730 that connects the various system components.
The memory 710 may include, for example, system memory, non-volatile storage media, and the like. The system memory stores, for example, an operating system, an application program, a Boot Loader (Boot Loader), and other programs. The system memory may include volatile storage media such as Random Access Memory (RAM) and/or cache memory. The non-volatile storage medium, for example, stores instructions to perform corresponding embodiments of at least one of the inventory control methods. Non-volatile storage media include, but are not limited to, magnetic disk storage, optical storage, flash memory, and the like.
Processor 720 may be implemented as discrete hardware components, such as a general purpose processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other programmable logic device, discrete gates or transistors, or the like. Accordingly, each of the modules, such as the acquisition module and the first inventory determination module, may be implemented by a Central Processing Unit (CPU) executing instructions in a memory to perform the corresponding steps, or may be implemented by dedicated circuitry to perform the corresponding steps.
Bus 730 may use any of a variety of bus architectures. For example, bus structures include, but are not limited to, Industry Standard Architecture (ISA) bus, Micro Channel Architecture (MCA) bus, and Peripheral Component Interconnect (PCI) bus.
The computer system 700 may also include input-output interfaces 740, network interfaces 750, storage interfaces 760, and the like. These interfaces 740, 750, 760 and the memory 710 and the processor 720 may be connected by a bus 730. The input/output interface 740 may provide a connection interface for an input/output device such as a display, a mouse, a keyboard, and the like. The network interface 750 provides a connection interface for various networking devices. The storage interface 760 provides a connection interface for external storage devices such as a floppy disk, a usb disk, and an SD card.
Various aspects of the present disclosure are described herein with reference to flowchart illustrations and/or block diagrams of methods, apparatus and computer program products according to embodiments of the disclosure. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer readable program instructions.
These computer-readable program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable apparatus to produce a machine, such that the execution of the instructions by the processor results in an apparatus that implements the functions specified in the flowchart and/or block diagram block or blocks.
These computer-readable program instructions may also be stored in a computer-readable memory that can direct a computer to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instructions which implement the function specified in the flowchart and/or block diagram block or blocks.
The present disclosure may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects.
By the inventory control method and the inventory control device in the embodiment, the inventory of the target product of the target object can be accurately determined, and the inventory control efficiency and effectiveness are improved.
Thus far, inventory control methods and apparatus according to the present disclosure have been described in detail. Some details that are well known in the art have not been described in order to avoid obscuring the concepts of the present disclosure. It will be fully apparent to those skilled in the art from the foregoing description how to practice the presently disclosed embodiments.

Claims (15)

1. An inventory control method, comprising:
acquiring a historical shipment quantity sequence of a target object for a target product before an observation time sequence, wherein the observation time sequence comprises at least one unit of observation time;
processing the historical stocking amount sequence to obtain an initial stock of the target product in each unit observation time in the observation time sequence;
determining an inventory impact factor of the target product at a current observation time, wherein the current observation time is a unit observation time in the observation time series;
and determining the inventory of the target product at the current observation time according to the inventory influence factor of the target product at the current observation time and the initial inventory of the target product at the observation time sequence.
2. The inventory control method of claim 1, further comprising:
generating inventory control information according to the inventory of the target product at the current observation time;
and sending the inventory control information to a terminal corresponding to the target object, wherein the inventory control information is used for prompting the target object to carry out inventory control on the target product.
3. The inventory control method of claim 2, wherein generating inventory control information based on the inventory of the target product at the current observation time includes at least one of:
generating first inventory control information under the condition that the inventory of the target product at the current observation time is greater than a first inventory threshold value, wherein the first inventory control information is used for indicating the target object to carry out inventory cleaning on the target product;
and generating second inventory control information under the condition that the inventory of the target product of the target object at the current observation time is less than a second inventory threshold, wherein the second inventory control information is used for indicating the target object to replenish the target product, and the second inventory threshold is less than the first inventory threshold.
4. The inventory control method according to claim 3,
querying an inventory threshold storage table based on at least one of the identification of the target object and the identification of the target product to determine the first inventory threshold and the second inventory threshold.
5. The inventory control method of claim 1, wherein the inventory impact factor of the target product at the current observation time includes at least one of a stock quantity increment index value, a number of stock turnaround days, and an average amount of stock consumed per stock interval of the target product at the current observation time.
6. The inventory control method according to claim 5, wherein:
the inventory of the target product at the current observation time is positively correlated with the inventory increment index value;
the inventory of the target product at the current observation time is in negative correlation with the number of days of inventory turnover;
the inventory of the target product at the current observation time is positively correlated with the inventory consumed at the average time interval of each stock.
7. The inventory control method of claim 6, wherein the inventory of the target product at the current observed time is determined according to the formula:
Figure FDA0003605309350000021
wherein the content of the first and second substances,
Figure FDA0003605309350000022
is composed ofThe stock of the target product at the current observation time, alpha and beta are adjustment coefficients, K0For initial inventory, Δ S is the value of the incremental index of the quantity of goods delivered,
Figure FDA0003605309350000023
d is the number of days of stock turnover, which is the average stock consumed per stocking interval.
8. The inventory forecasting method of claim 5, wherein the determining an inventory impact factor for a target product at a current observed time comprises:
and determining a monthly ring ratio goods intake difference value of the target product according to the goods intake of the target product at the current observation time and the goods intake of the target product on the same day of the last month, and taking the monthly ring ratio goods intake difference value as the goods intake increment index value.
9. The inventory forecasting method of claim 5, wherein the determining an inventory impact factor for a target product at a current observed time comprises:
and determining the number of inventory turnover days according to the initial inventory of the target product in the observation time sequence, the historical inventory of the target product in a preset time period before the current observation time and the duration of the preset time period.
10. The inventory prediction method of claim 8, wherein the number of inventory turnaround days is positively correlated to the initial inventory and the duration of the preset time period, and negatively correlated to a historical inventory of the target product over a preset time period prior to the current observation time.
11. The inventory forecasting method of claim 5, wherein the determining an inventory impact factor for a target product at a current observed time comprises:
and determining the average inventory consumed at each time of the target products at the stocking interval according to the historical stocking amount of the target products in a preset time period before the current observation time and the historical stocking times of the target products in the preset time period.
12. The inventory forecasting method of claim 1, wherein the processing the sequence of historical inventory amounts to obtain an initial inventory of the target product per unit of observed time in the sequence of observed times comprises:
decomposing the historical cargo volume sequence according to an empirical mode decomposition algorithm to obtain an eigenmode function sequence;
and processing the eigenmode function sequence according to an inventory determination model to obtain the initial inventory of the target product in the observation time sequence.
13. An inventory control device comprising:
an acquisition module configured to acquire a historical inventory quantity sequence of a target object for a target product prior to an observation time sequence, wherein the observation time sequence includes at least one unit of observation time;
a first inventory determination module configured to process the historical inventory sequence to obtain an initial inventory of the target product for each unit of observation time in the observation time sequence;
an influence factor determination module configured to determine an inventory influence factor for the target product at a current observation time, wherein the current observation time is a unit observation time in the observation time series;
a second inventory determination module configured to determine an inventory of the target product at the current observation time based on the inventory impact factor of the target product at the current observation time and an initial inventory of the target product at the observation time series.
14. An inventory control device comprising:
a memory; and
a processor coupled to the memory, the processor configured to perform the inventory control method of any of claims 1-12 based on instructions stored in the memory.
15. A computer readable storage medium having stored thereon computer program instructions which, when executed by a processor, implement the inventory control method of any of claims 1 to 12.
CN202210414914.7A 2022-04-20 2022-04-20 Inventory control method and device Pending CN114742505A (en)

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113657667A (en) * 2021-08-17 2021-11-16 北京沃东天骏信息技术有限公司 Data processing method, device, equipment and storage medium

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113657667A (en) * 2021-08-17 2021-11-16 北京沃东天骏信息技术有限公司 Data processing method, device, equipment and storage medium

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