CN111798167A

CN111798167A - Warehouse replenishment method and device

Info

Publication number: CN111798167A
Application number: CN201911053458.2A
Authority: CN
Inventors: 禄晓龙
Original assignee: Beijing Wodong Tianjun Information Technology Co Ltd
Current assignee: Beijing Wodong Tianjun Information Technology Co Ltd
Priority date: 2019-10-31
Filing date: 2019-10-31
Publication date: 2020-10-20
Anticipated expiration: 2039-10-31
Also published as: CN111798167B

Abstract

The invention discloses a warehouse replenishment method and device, and relates to the technical field of computers. One embodiment of the method comprises: calculating the recommendation accuracy of each derivative recommendation quantity of the recommendation quantity according to the historical recommendation data and the historical ex-warehouse data; selecting the highest derived recommended quantity with the recommendation accuracy rate larger than the initial threshold value as a pre-recommended quantity corresponding to the recommended quantity; determining the pre-recommendation amount of the recommendation objects based on the recommendation amount of the recommendation objects, and calculating the pre-recommendation inventory of the warehouse; and determining the replenishment quantity of the recommended object according to the pre-recommended inventory and the current inventory threshold, or determining the replenishment quantity of the recommended object after adjusting the initial threshold. The embodiment can efficiently and accurately control the replenishment quantity of the warehouse, reduce the stock backlog, reduce the operation cost, adapt to the changed stock limit and maintain the stable stock quantity.

Description

Warehouse replenishment method and device

Technical Field

The invention relates to the technical field of computers, in particular to a warehouse replenishment method and device.

Background

At present, storage logistics business is constantly strong, in order to relieve the production pressure of regional big storehouses, reduce the delivery timeliness, increase customer experience, reduce the operation cost, and auxiliary storehouses are established for regional big storehouses in some places.

The auxiliary warehouse is a warehouse closer to the user, which can store large goods, such as air conditioners, televisions, washing machines, and the like, the storage capacity and the credit amount of the auxiliary warehouse are limited, and the storage limit of the auxiliary warehouse, the credit amount, and the like is also adjusted in real time, for example, certain special dates are different from the daily maximum storage limit.

For the replenishment of the auxiliary warehouse, if the replenishment is performed according to the recommended items, the phenomenon that the inventory limit is exceeded is often caused, so that a person in charge of the auxiliary warehouse is required to regularly adjust the recommended items according to the inventory limit, specifically, the recommended items are subjected to statistical analysis on the number of pieces, the credit amount and the like, and then compared with the current inventory amount, the credit amount and the like, if the set inventory amount, the credit amount and the like are exceeded, the recommended amount is reduced or a part of the recommended items is selected, and then the statistical analysis and the comparison are performed again until the recommended amount is lower than the set inventory amount, the credit amount and the like.

In the process of implementing the invention, the inventor finds that at least the following problems exist in the prior art:

the replenishment of the auxiliary bin depends on the subjective judgment of a person in charge of the auxiliary bin, and the replenishment quantity of the auxiliary bin cannot be accurately controlled; the method cannot adapt to the changed inventory limit and maintain stable inventory; and the phenomenon of stock overstock is easy to occur, and the operation cost is higher.

Disclosure of Invention

In view of this, embodiments of the present invention provide a method and an apparatus for warehouse replenishment, which can efficiently and accurately control the replenishment quantity of a warehouse, reduce the stock backlog, reduce the operation cost, adapt to the changed stock limit, and maintain a stable stock.

To achieve the above object, according to an aspect of an embodiment of the present invention, there is provided a method of restocking a warehouse.

The warehouse replenishment method comprises the following steps:

calculating the recommendation accuracy of each derivative recommendation quantity of the recommendation quantity according to the historical recommendation data and the historical ex-warehouse data;

selecting the highest value of the derived recommended quantities with the recommendation accuracy rate larger than an initial threshold value as a pre-recommended quantity corresponding to the recommended quantity;

determining a pre-recommendation amount of the recommended objects based on the recommended number of the recommended objects, and calculating a pre-recommendation inventory amount of a warehouse;

and determining the replenishment quantity of the recommended object according to the pre-recommended inventory and the current inventory threshold, or determining the replenishment quantity of the recommended object after adjusting the initial threshold.

Optionally, calculating a recommendation accuracy of each derived recommendation quantity of the recommendation quantity according to the historical recommendation data and the historical ex-warehouse data, including:

acquiring historical recommendation data and historical ex-warehouse data; the historical recommendation data comprises historical objects and historical recommendation quantity thereof, and the historical ex-warehouse data comprises the historical objects and ex-warehouse quantity thereof;

extracting the historical objects with the same historical recommendation amount and the ex-warehouse quantity thereof from the historical recommendation data and the historical ex-warehouse data;

based on the historical objects and the ex-warehouse quantity thereof corresponding to the historical recommendation quantity which is the same as the recommendation quantity, respectively calculating the recommendation accuracy of each derivative recommendation quantity of each recommendation quantity by adopting an accuracy formula; wherein the accuracy formula is

P is the recommendation accuracy, n is the number of the history objects with the same history recommendation amount, Y_jIs the derivative recommended amount, 1 ≦ Y_jLess than or equal to the recommended amount threshold, X_jIs the derivative residual amount corresponding to the derivative recommended amount.

Optionally, determining a pre-recommendation amount of the recommended object based on the recommended number of the recommended objects, and calculating a pre-recommendation inventory amount of a warehouse, includes:

receiving recommended selections of a warehouse; the recommended selection comprises recommended objects and the recommended quantity corresponding to the recommended objects;

determining the pre-recommendation amount of the recommended objects according to the recommendation amount;

and calculating the pre-recommended inventory of the warehouse based on the recommended selection and the pre-recommended amount of the recommended object.

Optionally, determining the replenishment quantity of the recommended object according to the pre-recommended inventory amount and the current inventory threshold, or determining the replenishment quantity of the recommended object after adjusting the initial threshold, includes:

comparing the pre-recommended inventory amount with a current inventory threshold value;

if the pre-recommended inventory amount is equal to the current inventory threshold value, determining that the replenishment quantity of the recommended object is the pre-recommended quantity minus the inventory quantity of the recommended object;

if the pre-recommended inventory amount is larger than or smaller than the current inventory threshold value, the initial threshold value is increased in gradient or decreased in gradient so as to determine the replenishment quantity of the recommended object.

Optionally, if the pre-recommended inventory amount is greater than or less than the current inventory threshold, the step of increasing or decreasing the initial threshold in a gradient manner to determine the replenishment quantity of the recommended object includes:

if the pre-recommended inventory amount is larger than the current inventory threshold value, increasing a first preset value to the initial threshold value, and re-determining the pre-recommended amount of the recommended object to determine the replenishment quantity of the recommended object;

if the pre-recommended inventory amount is smaller than the current inventory threshold value, reducing the initial threshold value by a second preset value, and comparing the reduced initial threshold value with a lowest threshold value;

if the reduced initial threshold is greater than or equal to the minimum threshold, re-determining the pre-recommended amount of the recommended object to determine the replenishment quantity of the recommended object;

and if the reduced initial threshold value is smaller than the minimum threshold value, determining that the replenishment quantity of the recommended object is the pre-recommended quantity of the recommended object minus the stock quantity of the recommended object.

Optionally, determining the replenishment quantity of the recommended object according to the pre-recommended inventory amount and the current inventory threshold, or determining the replenishment quantity of the recommended object after adjusting the initial threshold, further comprising:

if the pre-recommended inventory after the gradient increase is larger than the current inventory threshold value and the pre-recommended inventory after the gradient decrease is smaller than the current inventory threshold value, determining the replenishment quantity of the recommended object based on the pre-recommended inventory after the gradient decrease;

and if the initial threshold value gradient is increased or decreased for a preset number of times, determining the replenishment quantity of the recommended object based on the pre-recommended inventory amount for the first preset number of times.

To achieve the above object, according to another aspect of the embodiments of the present invention, there is provided an apparatus for restocking a warehouse.

The device for replenishing goods in the warehouse of the embodiment of the invention comprises:

the calculation module is used for calculating the recommendation accuracy of each derivative recommendation quantity of the recommendation quantity according to the historical recommendation data and the historical ex-warehouse data;

the selection module is used for selecting the highest value in the derived recommended quantity with the recommendation accuracy rate larger than an initial threshold value as a pre-recommended quantity corresponding to the recommended quantity;

the determining module is used for determining the pre-recommendation amount of the recommended objects based on the recommended quantity of the recommended objects and calculating the pre-recommendation stock quantity of the warehouse;

and the adjusting module is used for determining the replenishment quantity of the recommended object according to the pre-recommended inventory and the current inventory threshold, or determining the replenishment quantity of the recommended object after adjusting the initial threshold.

Optionally, the adjusting module is further configured to:

when the pre-recommended inventory amount after the gradient increase is larger than the current inventory threshold value and the pre-recommended inventory amount after the gradient decrease is smaller than the current inventory threshold value, determining the replenishment quantity of the recommended object based on the pre-recommended inventory amount after the gradient decrease;

and when the initial threshold value gradient is increased or decreased for a preset number of times, determining the replenishment quantity of the recommended object based on the pre-recommended inventory amount for the first preset number of times.

To achieve the above object, according to still another aspect of the embodiments of the present invention, there is provided an electronic device for warehouse restocking.

The electronic equipment for warehouse replenishment in the embodiment of the invention comprises: one or more processors; a storage device for storing one or more programs which, when executed by the one or more processors, cause the one or more processors to implement a method for warehouse restocking in accordance with an embodiment of the present invention.

To achieve the above object, according to still another aspect of embodiments of the present invention, there is provided a computer-readable storage medium.

A computer-readable storage medium of an embodiment of the present invention has stored thereon a computer program that, when executed by a processor, implements a method of warehouse restocking of an embodiment of the present invention.

One embodiment of the above invention has the following advantages or benefits: because the recommendation accuracy of each derivative recommendation quantity of the recommendation quantity is calculated according to the historical recommendation data and the historical ex-warehouse data; selecting the highest derived recommended quantity with the recommendation accuracy rate larger than the initial threshold value as a pre-recommended quantity corresponding to the recommended quantity; determining the pre-recommendation amount of the recommendation objects based on the recommendation amount of the recommendation objects, and calculating the pre-recommendation inventory of the warehouse; the technical means of determining the replenishment quantity of the recommended objects or determining the replenishment quantity of the recommended objects after adjusting the initial threshold value according to the pre-recommended inventory quantity and the current inventory threshold value overcome that the replenishment of the auxiliary warehouse depends on the subjective judgment of a person in charge of the auxiliary warehouse and the replenishment quantity of the auxiliary warehouse cannot be accurately controlled; the method cannot adapt to the changed inventory limit and maintain stable inventory; and the technical problems of easy occurrence of the phenomenon of stock overstock and higher operation cost are solved, so that the technical effects of efficiently and accurately controlling the replenishment quantity of the warehouse, reducing the stock overstock and the operation cost, adapting to the changed stock limitation and maintaining stable stock are achieved.

Further effects of the above-mentioned non-conventional alternatives will be described below in connection with the embodiments.

Drawings

The drawings are included to provide a better understanding of the invention and are not to be construed as unduly limiting the invention. Wherein:

FIG. 1 is a schematic diagram of the main steps of a method of warehouse restocking according to an embodiment of the present invention;

FIG. 2 is a flow chart illustrating an implementation of a method for warehouse restocking according to a referenced embodiment of the present invention;

FIG. 3 is a schematic diagram of adjusting an initial threshold value of a method of warehouse restocking according to a referenced embodiment of the present invention;

FIG. 4 is a schematic diagram of an application of a method of warehouse restocking according to an embodiment of the present invention;

FIG. 5 is a schematic diagram of the main modules of an apparatus for warehouse restocking in accordance with an embodiment of the present invention;

FIG. 6 is an exemplary system architecture diagram in which embodiments of the present invention may be employed;

fig. 7 is a schematic block diagram of a computer system suitable for use in implementing a terminal device or server of an embodiment of the invention.

Detailed Description

Exemplary embodiments of the present invention are described below with reference to the accompanying drawings, in which various details of embodiments of the invention are included to assist understanding, and which are to be considered as merely exemplary. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the invention. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.

It should be noted that the embodiments of the present invention and the technical features of the embodiments may be combined with each other without conflict.

The warehouse replenishment method of the embodiment of the invention performs derivation according to historical recommendation data, namely, assuming a plurality of derived recommendations, and the historical ex-warehouse data is used for matching to obtain derivative recommendation results (namely the recommendation accuracy of each derivative recommendation amount), and the derivative recommendation results are mapped into the recommendation accuracy of the derivative recommendation amount of the current recommendation amount, forming a ex-warehouse probability gradient for each recommended object according to the recommended quantity, setting an initial threshold and a step length of gradient increase or gradient decrease based on the ex-warehouse probability gradient, iteratively calculating the pre-recommended quantity of the recommended objects, and further calculates the pre-recommended stock quantity of the warehouse to enable the pre-recommended stock quantity to approach the current stock threshold value of the warehouse, thereby efficiently and accurately controlling the replenishment quantity of the warehouse, further reducing inventory backlog, reducing operating costs, and being able to adapt to changing inventory constraints and maintain a stable inventory.

The ex-warehouse probability gradient refers to different recommendation accuracy rates of different derivative recommendation quantities, wherein the higher the derivative recommendation quantity is, the lower the recommendation accuracy rate is, and the recommendation accuracy rates form a value sequence with a gradient.

Fig. 1 is a schematic diagram of the main steps of a method of warehouse restocking according to an embodiment of the present invention.

As shown in fig. 1, the method for replenishing the warehouse in the embodiment of the present invention mainly includes the following steps:

step S101: and calculating the recommendation accuracy of each derivative recommendation quantity of the recommendation quantity according to the historical recommendation data and the historical ex-warehouse data.

Wherein, the historical recommendation data and the historical ex-warehouse data can be data of a past period of time or a past period and the like.

Because the objects in the warehouse are various in types and the warehouse-out rate has large fluctuation, the recommendation accuracy of a specific object is difficult to determine, objects with the same recommendation quantity have similar commonalities and can be used as a whole to evaluate the recommendation accuracy, and the recommendation accuracy is stable, so that calculation can be performed according to the recommendation quantity, wherein the recommendation quantity is the stock recommended for each recommendation object.

In the embodiment of the present invention, step S101 may be implemented based on the following steps: acquiring historical recommendation data and historical ex-warehouse data; extracting historical objects with the same historical recommendation amount and the ex-warehouse quantity thereof from the historical recommendation data and the historical ex-warehouse data; and respectively calculating the recommendation accuracy of each derivative recommendation quantity of each recommendation quantity by adopting an accuracy formula based on the history objects corresponding to the history recommendation quantities with the same recommendation quantity and the ex-warehouse quantity thereof.

The historical recommendation data comprises historical objects and historical recommendation quantity thereof, and the historical ex-warehouse data comprises the historical objects and ex-warehouse quantity thereof. The method comprises the steps that historical objects with the same historical recommendation amount can be found according to historical recommendation data, the ex-warehouse quantity of each historical object with the same historical recommendation amount can be found from the historical ex-warehouse data, for one historical object, the historical recommendation amount and the ex-warehouse quantity are known, the derivative residual quantity of the historical object can be obtained, the accuracy of each corresponding derivative recommendation amount is calculated, the accuracy of each derivative recommendation amount of all the historical objects with the same historical recommendation amount is obtained by the method, and the average value of the accuracy of the same derivative recommendation amount is used as the recommendation accuracy of the derivative recommendation amount. The recommendation accuracy of each derivative recommendation quantity of a historical recommendation quantity can be obtained in the calculation mode, so that the recommendation accuracy of each derivative recommendation quantity of each historical recommendation quantity is obtained, and when the replenishment quantity is analyzed and calculated, the recommendation accuracy of each derivative recommendation quantity of the historical recommendation quantity can be directly mapped to the recommendation accuracy of each derivative recommendation quantity of the recommendation quantity, namely the recommendation accuracy of each derivative recommendation quantity of the recommendation quantity is directly calculated by using historical recommendation data and historical ex-warehouse data. The recommendation accuracy of the derived recommendation amount is verified through the real ex-warehouse quantity, and good data reference is provided for recommendation according to the derived recommendation result.

The accuracy formula may be

P is the recommendation accuracy, n is the number of history objects with the same history recommendation amount, Y_jIs a derivative recommended amount, 1. ltoreq. Y_jLess than or equal to the recommended amount threshold, X_jThe derived residual amount is the derived residual amount corresponding to the derived recommended amount, and the derived residual amount is the residual amount obtained by subtracting the ex-warehouse amount from the derived recommended amount.

Step S102: and selecting the highest value in the derived recommended quantity with the recommendation accuracy rate larger than the initial threshold value as a pre-recommended quantity corresponding to the recommended quantity.

The recommendation accuracy can reflect the expected ex-warehouse condition of one recommendation object, namely the probability of deriving all the recommendation objects of the recommendation quantity. And screening the recommendation accuracy rate through the initial threshold value, so that the pre-recommendation amount corresponding to each recommendation amount can be determined.

It should be noted that the initial threshold may be set according to situations, historical data, or similar warehouse situations, and generally requires a higher initial threshold to be set, so that the probability of the pre-recommended amount of recommended objects going out of the warehouse in a future period of time cannot be too low (to avoid late sales), and the initial threshold cannot be too high, resulting in no available pre-recommended amount. As a preferred embodiment, the initial threshold may be set to 80%.

Step S103: and determining the pre-recommendation amount of the recommendation object based on the recommendation amount of the recommendation object, and calculating the pre-recommendation inventory amount of the warehouse.

And determining the pre-recommendation amount of each recommendation object according to the recommendation amount corresponding to each recommendation object, so as to calculate the pre-recommendation inventory of the warehouse.

In the embodiment of the present invention, step S103 may be implemented based on the following steps: receiving recommended selections of a warehouse; determining the pre-recommendation amount of the recommended objects according to the recommendation amount of the recommended objects; and calculating the pre-recommended inventory of the warehouse based on the recommended selections and the pre-recommended amount of the recommended objects.

The recommended optional items are replenishment schemes provided for the warehouse by a logistics management party or a warehouse management party and the like, wherein the recommended optional items comprise recommended objects and recommended quantity corresponding to the recommended objects. For example, creating a secondary bin for a regional warehouse, the regional warehouse may provide recommended selections to the secondary bin.

Step S104: and determining the replenishment quantity of the recommended object according to the pre-recommended inventory and the current inventory threshold, or determining the replenishment quantity of the recommended object after adjusting the initial threshold.

The pre-recommended stock quantity obtained in step S103 is the stock quantity determined only from the historical data, and when determining the replenishment quantity of each recommended object, the replenishment quantity of each recommended object is directly determined in consideration of the current stock threshold of the warehouse, or the stock quantity is re-pre-recommended by adjusting the initial threshold, and the replenishment quantity of the recommended object is determined.

It should be noted that the current inventory threshold is an amount of inventory currently allowed by the warehouse, and the current inventory threshold may be set according to actual situations such as the inventory capacity of the warehouse or the credit amount, or some requirements.

In the embodiment of the present invention, step S104 may be implemented based on the following steps: comparing the pre-recommended inventory amount with a current inventory threshold value; if the pre-recommended inventory amount is equal to the current inventory threshold value, determining that the replenishment quantity of the recommended object is the pre-recommended quantity minus the inventory quantity of the recommended object; if the pre-recommended inventory amount is larger than or smaller than the current inventory threshold value, the initial threshold value is increased or decreased in a gradient mode so as to determine the replenishment quantity of the recommended object.

As for the pre-recommended inventory amount of the warehouse, whether the pre-recommended inventory amount is the same as the inventory amount allowed by the warehouse (i.e. the current inventory threshold value) needs to be analyzed, if the same indicates that the replenishment quantity of the recommendation object can be determined by the pre-recommended quantity of the recommendation object determined in step S103, specifically, since the pre-recommended quantity contains the existing inventory, the replenishment quantity of the recommendation object is determined by subtracting the inventory quantity of the recommendation object from the pre-recommended quantity of the recommendation object; if the difference indicates that the pre-recommended quantity of the recommended object determined in step S103 needs to be adjusted, that is, the gradient increases or decreases by the initial threshold, and then the replenishment quantity of the recommended object is determined.

In the embodiment of the present invention, if the pre-recommended inventory amount is greater than or less than the current inventory threshold, the step of increasing or decreasing the initial threshold in a gradient manner to determine the replenishment quantity of the recommended object may be implemented based on the following steps: if the pre-recommended inventory amount is larger than the current inventory threshold value, increasing the initial threshold value by a first preset value, and re-determining the pre-recommended amount of the recommended object to determine the replenishment quantity of the recommended object; if the pre-recommended inventory amount is smaller than the current inventory threshold value, reducing the initial threshold value by a second preset value, and comparing the reduced initial threshold value with the lowest threshold value; if the reduced initial threshold value is larger than or equal to the minimum threshold value, re-determining the pre-recommended amount of the recommended object to determine the replenishment quantity of the recommended object; if the reduced initial threshold is less than the minimum threshold, determining that the replenishment quantity of the recommended object is the pre-recommended quantity of the recommended object minus the stock quantity of the recommended object.

It should be noted that the first preset value is a step length of a gradient increase, the second preset value is a step length of a gradient decrease, the first preset value and the second preset value may be set according to a situation or historical data, and the first preset value and the second preset value may be the same or different, and the amplitude of each change of the pre-recommended inventory quantity of the warehouse is controlled by the first preset value and the second preset value. As a preferred embodiment, the first preset value and the second preset value may be set to 2%.

If the pre-recommended inventory amount of the warehouse is larger than the current inventory threshold value of the warehouse, the pre-recommended inventory amount is larger than the inventory amount allowed by the warehouse, the pre-recommended amount of part or all of the recommended objects needs to be reduced, namely, after the initial threshold value is increased by a first preset value, the steps S102-S104 are executed again. If the pre-recommended inventory amount of the warehouse is less than the current inventory threshold value of the warehouse, the pre-recommended inventory amount does not exceed the allowed inventory amount of the warehouse, the pre-recommended amount of part or all of the recommended objects can be increased, namely the initial threshold value is reduced by a second preset value, but the probability that the pre-recommended amount of the recommended objects are delivered from the warehouse in the future period of time cannot be too low in consideration of the risk of inventory backlog, a minimum threshold value can be set, the minimum threshold value can embody the allowed inventory backlog limit of the warehouse, and as a preferred implementation mode, the minimum threshold value can be set to 70%. If the reduced initial threshold is greater than or equal to the minimum threshold, it indicates that the pre-recommendation amount of the recommended object can be increased, and then steps S102-S104 are re-executed; if the reduced initial threshold is smaller than the minimum threshold, it means that the initial threshold does not need to be adjusted, and the pre-recommended amount of the recommended object determined in step S103 may be directly used to determine the replenishment quantity of the recommended object, specifically, the pre-recommended amount of the recommended object is subtracted by the stock quantity of the recommended object.

In this embodiment of the present invention, step S104 may further include the following steps: if the pre-recommended inventory after the gradient increase is larger than the current inventory threshold value and the pre-recommended inventory after the gradient decrease is smaller than the current inventory threshold value, determining the replenishment quantity of the recommended object based on the pre-recommended inventory after the gradient decrease; and if the initial threshold value gradient is increased or the gradient is reduced for a preset number of times, determining the replenishment quantity of the recommended object based on the pre-recommended inventory quantity of the first preset number of times.

If the initial threshold value is increased successively and decreased successively (not successively), but the pre-recommended stock quantity is still not equal to the current stock threshold value and fluctuates above and below the current stock threshold value, it indicates that the pre-recommended stock quantity is close to the current stock threshold value (the difference quantity is within an acceptable range), and the replenishment quantity of the recommended object can be determined by the pre-recommended stock quantity which is closest to the current stock threshold value (the difference quantity is minimum) and is smaller than the current stock threshold value. Meanwhile, if the pre-recommended inventory is not equal to the current inventory threshold after the initial threshold is increased or decreased in gradient for multiple times, the replenishment quantity of the recommended objects can be determined directly by the pre-recommended inventory for the first preset time in order to determine the replenishment quantity of the recommended objects in time and reduce the calculation amount.

According to the warehouse replenishment method, the recommendation accuracy of each derivative recommendation quantity of the recommendation quantity is calculated according to the historical recommendation data and the historical ex-warehouse data; selecting the highest derived recommended quantity with the recommendation accuracy rate larger than the initial threshold value as a pre-recommended quantity corresponding to the recommended quantity; determining the pre-recommendation amount of the recommendation objects based on the recommendation amount of the recommendation objects, and calculating the pre-recommendation inventory of the warehouse; the technical means of determining the replenishment quantity of the recommended objects or determining the replenishment quantity of the recommended objects after adjusting the initial threshold value according to the pre-recommended inventory quantity and the current inventory threshold value overcome that the replenishment of the auxiliary warehouse depends on the subjective judgment of a person in charge of the auxiliary warehouse and the replenishment quantity of the auxiliary warehouse cannot be accurately controlled; the method cannot adapt to the changed inventory limit and maintain stable inventory; and the technical problems of easy occurrence of the phenomenon of stock overstock and higher operation cost are solved, so that the technical effects of efficiently and accurately controlling the replenishment quantity of the warehouse, reducing the stock overstock and the operation cost, adapting to the changed stock limitation and maintaining stable stock are achieved.

Fig. 2 is a schematic flow chart of an implementation of a method for warehouse restocking according to a reference embodiment of the present invention.

As shown in fig. 2, the method for warehouse replenishment according to the embodiment of the present invention may be divided into three parts, namely, calculating recommendation accuracy, setting related variables, and performing iterative computation, specifically:

1. calculating recommendation accuracy

Firstly, matching historical recommendation data with historical ex-warehouse data, namely extracting historical objects with the same historical recommendation quantity and ex-warehouse quantity thereof from the historical recommendation data and the historical ex-warehouse data; then, calculating a recommendation result of the historical recommendation amount, namely calculating the recommendation accuracy of each derivative recommendation amount of each historical recommendation amount; finally, mapping the recommendation result of the historical recommendation amount into the recommendation accuracy of each derivative recommendation amount of the recommendation amount;

2. dependent variable setting

The variables to be set comprise a current inventory threshold, a recommended quantity threshold, an initial threshold, a lowest threshold, a first preset value and a second preset value;

3. iterative computation

Calculating the pre-recommended inventory of the warehouse; matching the pre-recommended inventory quantity with a current inventory threshold value; the replenishment quantity of each recommended object is generated in the form of a stock list, or the initial threshold value is increased or decreased in a gradient manner, the pre-recommended stock quantity of the warehouse is recalculated, and the current stock threshold value is matched, and the specific process can refer to step S104.

Fig. 3 is a schematic diagram of adjusting an initial threshold value of a method of warehouse restocking according to a referential embodiment of the present invention.

As shown in fig. 3, when adjusting the initial threshold, the method for replenishing the warehouse according to the embodiment of the present invention may be implemented by referring to the following processes:

step S301: determining the pre-recommendation amount of the recommendation object according to the initial threshold, and calculating the pre-recommendation inventory of the warehouse:

selecting the highest derived recommendation amount with the recommendation accuracy rate larger than the initial threshold value as a pre-recommendation amount corresponding to the recommendation amount, determining the pre-recommendation amount of the recommendation object based on the recommendation amount of the recommendation object, and calculating the pre-recommendation stock of the warehouse;

step S302: comparing the pre-recommended inventory amount with a current inventory threshold:

if the pre-recommended inventory amount is larger than the current inventory threshold value, increasing the initial threshold value by a first preset value and restarting to execute the step S301; if the pre-recommended inventory amount is smaller than the current inventory threshold value, reducing the initial threshold value by a second preset value and executing the step S303; if the pre-recommended inventory amount is equal to the current inventory threshold value, executing the step S304;

step S303: comparing the reduced initial threshold value with the lowest threshold value

If the reduced initial threshold is greater than or equal to the lowest threshold, then step S301 is resumed; if the reduced initial threshold is smaller than the lowest threshold, executing step S304;

step S304: calculating the replenishment quantity of each recommended object

For each recommended object, the replenishment quantity is equal to the pre-recommended quantity minus the stock quantity.

Fig. 4 is a schematic application diagram of a method of warehouse restocking according to an embodiment of the present invention.

As shown in fig. 4, assuming that a large area warehouse in a certain area is provided with a plurality of front warehouses, when the warehouse replenishment method according to the embodiment of the present invention is applied to a certain front warehouse, the replenishment process of the front warehouse is as follows:

1. the large warehouse of the stock preparation stage recommends corresponding recommendation objects and corresponding recommendation quantity for the front warehouse through some product selection devices;

2. the front warehouse calculates according to the recommendation of the regional large warehouse and by combining the current inventory and the current inventory threshold value and adopting the warehouse replenishment method of the embodiment of the invention to generate a finished stock list, wherein the finished stock list comprises the recommended objects and the replenishment quantity corresponding to the recommended objects;

3. submitting the stock list to a distribution center, and distributing corresponding recommended objects to the front-end warehouse by the distribution center according to the stock list;

4. and (3) when the stock quantity or the credit amount of the front warehouse is lower than a set value or the replenishment is needed when the replenishment is needed, repeating the step (1) to the step (3).

In order to further illustrate the technical idea of the present invention, the technical solution of the present invention will now be described with reference to specific application scenarios. Taking a warehouse of a certain online shopping platform as an example, a front warehouse with the number of 120193 recommends commodities and the number of commodities that may be sold in the future 20 days, and it is assumed that the recommended quantity threshold is 5, the initial threshold is 80%, the minimum threshold is 70%, the first preset value is 2% and the second preset value is 8%.

Firstly, selecting a recommended commodity result (namely a historical object and historical recommended quantity thereof) of the last 20 days, and matching the recommended commodity result with the real sale condition (namely the historical object and the ex-warehouse quantity thereof) of the last 20 days, wherein the matching result is shown in a table 1;

TABLE 1

Front bin numbering	Commodity numbering device	Historical recommendation volume	Number of delivery
				120193	1060661	1	10
120193	1094736	1	5
				120193	1106432	5	2
120193	1404743	4	4
				120193	2368534	1	0
120193	2469956	4	5
				120193	274576	3	2
120193	7372400	1	2
				120193	7477658	5	2
120193	7641991	2	13
				120193	7680253	1	1
120193	7931582	1	2
				120195	1094736	2	0
120195	1099660	1	3
				120195	1106432	5	7
120195	1132921	1	1
				120195	1387890	1	10
120195	1404743	4	27
				120195	1451400	4	4
120195	1532590	1	3
				120195	1580963	1	8
120195	1581064	2	1

Secondly, 1-5 pieces of original recommended quantity (namely historical recommended quantity) are derived, namely the historical recommended quantity of each commodity is possible to be recommended to be 1-5 pieces, and the derived recommendations are shown in a table 2;

TABLE 2

The number of pieces remaining after 20 days of sale (i.e., the derivative remaining amount) if recommended according to the derivative recommended amount is calculated again, as shown in table 3;

TABLE 3

Then calculating the recommendation accuracy rate of 1-10 derived recommended quantities under 1-10 recommended quantities, wherein the accuracy rate formula is as follows:

p is the recommendation accuracy, n is the number of history objects with the same history recommendation amount, Y_jIs a derivative recommended amount, 1. ltoreq. Y_jLess than or equal to the recommended amount threshold, X_jIs the derivative residual amount corresponding to the derivative recommended amount;

the recommendation accuracy of each derived recommendation quantity is calculated as follows:

selecting 1 piece of data with the historical recommendation quantity from the table 3, and displaying the data in the table 4;

TABLE 4

And calculating the recommendation accuracy when the derivative recommended quantity is 1 according to an accuracy formula:

P₁＝1—0+0+1+0+0+0+0+0+0+0+0/1+1+1+1+1+1+1+1+1+1+1＝90.91％

similarly, the recommendation accuracy for derivative recommendations of 2, 3, 4, and 5 pieces can be obtained, as shown in table 5;

TABLE 5

From the above data, if the commodities in table 4 are all prepared according to the derivative recommended amount of 1 part, only 1 part is not sold, the recommendation accuracy reaches 90.91%, and if the commodities in table 4 are all prepared according to the derivative recommended amount of 5 parts, as many as 22 parts are not sold, the recommendation accuracy is as low as 58.18%;

by analogy, the recommendation accuracy of each derivative recommendation amount under the historical recommendation amounts of 2, 3, 4 and 5 pieces is calculated respectively, and the derivative recommendation results are shown in table 6;

TABLE 6

The recommendation accuracy of the last derived recommendation is verified through the real sales condition, and good data reference is provided for future recommendations;

then mapping the derived recommendation result into the derived recommendation result of 20 days in the future, matching the same historical recommendation quantity with the recommendation quantity, wherein the recommendation options are shown in table 7, and the mapping result is shown in table 8;

TABLE 7

Front bin numbering	Commodity numbering device	Recommended quantity
			120193	194736	1
120193	145340	1
			120193	274576	2
120193	372774	2
			120193	110643	3
120193	404743	3
			120193	145140	3
120193	634822	3
			120193	863498	4

TABLE 8

The mapped derivative recommendation results greatly enrich the original recommendation conditions, different probability gradients are formed for the derivative recommendation results, more reference contents are provided, and a foundation is provided for pre-warehouse replenishment.

And finally, calculating the pre-recommended inventory of the front warehouse according to the mapped derivative recommendation result and 80% of the initial threshold, specifically, selecting the highest value of the derivative recommendation quantity with the recommendation accuracy rate larger than the initial threshold as the pre-recommended quantity corresponding to the recommendation quantity, thereby determining the pre-recommended quantity (the part marked in the table) of the commodity, and then calculating the pre-recommended inventory of the front warehouse. For example, the commodities in the first row of table 9 are traversed from the lowest recommendation accuracy (the higher the derived recommendation amount is), the lower the recommendation accuracy is, when the recommendation accuracy is greater than or equal to 80%, the traversal is stopped, the derived recommendation amount (2 items) corresponding to the column is the pre-recommendation amount of the commodities, and the commodities in the third row of table 9 are not recommended, that is, the pre-recommendation amount is 0;

TABLE 9

Table 9 is the pre-recommended amount of the commodity determined for the first time according to the initial threshold, and as can be seen from table 9, the actual recommended result and the original recommended amount are different, if the pre-recommended stock quantity is equal to the stock limit, the actual recommended result may be used to replace the original recommended amount, and if the pre-recommended stock quantity is greater than or less than the stock limit, the actual recommended amount is iteratively calculated, specifically:

1) if the pre-recommended inventory amount calculated according to the initial threshold value is larger than the set inventory limit, adding 2% to the initial threshold value, namely the initial threshold value after the gradient increase is 82%, and then performing one round of judgment, wherein the result is shown in table 10;

watch 10

Comparing the table 9 with the table 10, the sum of the actual recommended quantity is reduced by 2, so that the operation can optimize the recommended commodities, and each recommended commodity has good sales probability;

2) if the pre-recommended inventory calculated according to the initial threshold is less than the set inventory limit, the pre-warehouse stock is possibly insufficient, the resource waste of the pre-warehouse is caused, the pre-recommended inventory needs to be increased, namely the initial threshold is subtracted by 8%, namely the initial threshold is changed into 72%, and then one round of judgment is carried out, and the result is shown in table 11;

TABLE 11

Comparing the table 8 with the table 11, the sum of the actual recommended quantity is increased by 2 pieces, so that the operation can lead the recommended commodities to be selected better from the inferior commodities, and each recommended commodity can be ensured to have good sale probability;

in addition, in order to avoid the condition that the recommendation accuracy is too low to cause the lost sales, a minimum threshold of 70% is further set, and once the minimum threshold is triggered, the recommendation is not increased even if the pre-recommended inventory amount is still lower than the inventory limit.

Through the continuous iterative calculation of the gradient increase or the gradient decrease, the accuracy of recommendation is ensured while the pre-recommended inventory amount is close to the total inventory limit. And finally, generating a stock list according to the pre-recommended inventory amount, and carrying out stock according to the stock list, wherein the stock amount of each commodity needs to be subtracted from the pre-recommended amount of each commodity during stock.

Fig. 5 is a schematic diagram of the main modules of an apparatus for warehouse restocking according to an embodiment of the present invention.

As shown in fig. 5, the apparatus 500 for replenishing warehouse goods according to the embodiment of the present invention includes: a calculation module 501, a selection module 502, a determination module 503 and an adjustment module 504.

Wherein the content of the first and second substances,

the calculation module 501 is configured to calculate recommendation accuracy rates of the derivative recommendation amounts of the recommendation amounts according to the historical recommendation data and the historical ex-warehouse data;

a selecting module 502, configured to select a highest value of the derived recommended quantities with the recommendation accuracy greater than an initial threshold as a pre-recommended quantity corresponding to the recommended quantity;

a determining module 503, configured to determine a pre-recommendation amount of a recommended object based on the recommended number of the recommended object, and calculate a pre-recommendation inventory amount of a warehouse;

an adjusting module 504, configured to determine the replenishment quantity of the recommended object according to the pre-recommended inventory amount and the current inventory threshold, or determine the replenishment quantity of the recommended object after adjusting the initial threshold.

In this embodiment of the present invention, the calculating module 501 is further configured to:

In this embodiment of the present invention, the determining module 503 is further configured to:

In this embodiment of the present invention, the adjusting module 504 is further configured to:

In an embodiment of the present invention, the adjusting module 504 is further configured to:

According to the warehouse replenishment device, the recommendation accuracy of each derivative recommendation quantity of the recommendation quantity is calculated according to the historical recommendation data and the historical ex-warehouse data; selecting the highest derived recommended quantity with the recommendation accuracy rate larger than the initial threshold value as a pre-recommended quantity corresponding to the recommended quantity; determining the pre-recommendation amount of the recommendation objects based on the recommendation amount of the recommendation objects, and calculating the pre-recommendation inventory of the warehouse; the technical means of determining the replenishment quantity of the recommended objects or determining the replenishment quantity of the recommended objects after adjusting the initial threshold value according to the pre-recommended inventory quantity and the current inventory threshold value overcome that the replenishment of the auxiliary warehouse depends on the subjective judgment of a person in charge of the auxiliary warehouse and the replenishment quantity of the auxiliary warehouse cannot be accurately controlled; the method cannot adapt to the changed inventory limit and maintain stable inventory; and the technical problems of easy occurrence of the phenomenon of stock overstock and higher operation cost are solved, so that the technical effects of efficiently and accurately controlling the replenishment quantity of the warehouse, reducing the stock overstock and the operation cost, adapting to the changed stock limitation and maintaining stable stock are achieved.

Fig. 6 illustrates an exemplary system architecture 600 of a method of warehouse restocking or an apparatus of warehouse restocking to which embodiments of the present invention may be applied.

As shown in fig. 6, the system architecture 600 may include

terminal devices

601, 602, 603, a network 604, and a server 605. The network 604 serves to provide a medium for communication links between the

terminal devices

601, 602, 603 and the server 605. Network 604 may include various types of connections, such as wire, wireless communication links, or fiber optic cables, to name a few.

A user may use the

terminal devices

601, 602, 603 to interact with the server 605 via the network 604 to receive or send messages or the like. Various communication client applications, such as shopping applications, web browser applications, search applications, instant messaging tools, mailbox clients, social platform software, and the like, may be installed on the

terminal devices

601, 602, and 603.

The

terminal devices

601, 602, 603 may be various electronic devices having a display screen and supporting web browsing, including but not limited to smart phones, tablet computers, laptop portable computers, desktop computers, and the like.

The server 605 may be a server that provides various services, such as a background management server that supports shopping websites browsed by users using the

terminal devices

601, 602, and 603. The background management server may analyze and perform other processing on the received data such as the product information query request, and feed back a processing result (e.g., target push information and product information) to the terminal device.

It should be noted that the method for warehouse replenishment provided by the embodiment of the present invention is generally executed by the server 605, and accordingly, the device for warehouse replenishment is generally disposed in the server 605.

It should be understood that the number of terminal devices, networks, and servers in fig. 6 is merely illustrative. There may be any number of terminal devices, networks, and servers, as desired for implementation.

Referring now to FIG. 7, shown is a block diagram of a computer system 700 suitable for use with a terminal device implementing an embodiment of the present invention. The terminal device shown in fig. 7 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present invention.

As shown in fig. 7, the computer system 700 includes a Central Processing Unit (CPU)701, which can perform various appropriate actions and processes in accordance with a program stored in a Read Only Memory (ROM)702 or a program loaded from a storage section 708 into a Random Access Memory (RAM) 703. In the RAM 703, various programs and data necessary for the operation of the system 700 are also stored. The CPU 701, the ROM 702, and the RAM 703 are connected to each other via a bus 704. An input/output (I/O) interface 705 is also connected to bus 704.

The following components are connected to the I/O interface 705: an input portion 706 including a keyboard, a mouse, and the like; an output section 707 including a display such as a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, and a speaker; a storage section 708 including a hard disk and the like; and a communication section 709 including a network interface card such as a LAN card, a modem, or the like. The communication section 709 performs communication processing via a network such as the internet. A drive 710 is also connected to the I/O interface 705 as needed. A removable medium 711 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 710 as necessary, so that a computer program read out therefrom is mounted into the storage section 708 as necessary.

In particular, according to the embodiments of the present disclosure, the processes described above with reference to the flowcharts may be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method illustrated in the flow chart. In such an embodiment, the computer program can be downloaded and installed from a network through the communication section 709, and/or installed from the removable medium 711. The computer program performs the above-described functions defined in the system of the present invention when executed by the Central Processing Unit (CPU) 701.

It should be noted that the computer readable medium shown in the present invention can be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present invention, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In the present invention, however, a computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, fiber optic cable, RF, etc., or any suitable combination of the foregoing.

The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams or flowchart illustration, and combinations of blocks in the block diagrams or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.

The modules described in the embodiments of the present invention may be implemented by software or hardware. The described modules may also be provided in a processor, which may be described as: a processor includes a calculation module, a selection module, a determination module, and an adjustment module. Where the names of these modules do not in some cases constitute a limitation on the module itself, for example, a calculation module may also be described as a "module that calculates the recommendation accuracy for each derived recommendation quantity for a recommendation quantity from historical recommendation data and historical export data".

As another aspect, the present invention also provides a computer-readable medium that may be contained in the apparatus described in the above embodiments; or may be separate and not incorporated into the device. The computer readable medium carries one or more programs which, when executed by a device, cause the device to comprise: step S101: calculating the recommendation accuracy of each derivative recommendation quantity of the recommendation quantity according to the historical recommendation data and the historical ex-warehouse data; step S102: selecting the highest derived recommended quantity with the recommendation accuracy rate larger than the initial threshold value as a pre-recommended quantity corresponding to the recommended quantity; step S103: determining the pre-recommendation amount of the recommendation objects based on the recommendation amount of the recommendation objects, and calculating the pre-recommendation inventory of the warehouse; step S104: and determining the replenishment quantity of the recommended object according to the pre-recommended inventory and the current inventory threshold, or determining the replenishment quantity of the recommended object after adjusting the initial threshold.

According to the technical scheme of the embodiment of the invention, the recommendation accuracy of each derivative recommendation quantity of the recommendation quantity is calculated according to the historical recommendation data and the historical ex-warehouse data; selecting the highest derived recommended quantity with the recommendation accuracy rate larger than the initial threshold value as a pre-recommended quantity corresponding to the recommended quantity; determining the pre-recommendation amount of the recommendation objects based on the recommendation amount of the recommendation objects, and calculating the pre-recommendation inventory of the warehouse; the technical means of determining the replenishment quantity of the recommended objects or determining the replenishment quantity of the recommended objects after adjusting the initial threshold value according to the pre-recommended inventory quantity and the current inventory threshold value overcome that the replenishment of the auxiliary warehouse depends on the subjective judgment of a person in charge of the auxiliary warehouse and the replenishment quantity of the auxiliary warehouse cannot be accurately controlled; the method cannot adapt to the changed inventory limit and maintain stable inventory; and the technical problems of easy occurrence of the phenomenon of stock overstock and higher operation cost are solved, so that the technical effects of efficiently and accurately controlling the replenishment quantity of the warehouse, reducing the stock overstock and the operation cost, adapting to the changed stock limitation and maintaining stable stock are achieved.

The above-described embodiments should not be construed as limiting the scope of the invention. Those skilled in the art will appreciate that various modifications, combinations, sub-combinations, and substitutions can occur, depending on design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method of restocking a warehouse, comprising:

2. The method of claim 1, wherein calculating a recommendation accuracy rate for each derived recommendation quantity for the recommendation quantity based on the historical recommendation data and the historical ex-warehouse data comprises:

3. The method of claim 2, wherein determining a pre-recommended amount of recommended objects based on the recommended number of recommended objects and calculating a pre-recommended inventory amount of a warehouse comprises:

4. The method of claim 1, wherein determining the replenishment quantity of the recommended object according to the pre-recommended inventory quantity and a current inventory threshold value, or determining the replenishment quantity of the recommended object after adjusting the initial threshold value comprises:

5. The method of claim 4, wherein if the pre-recommended inventory amount is greater than or less than the current inventory threshold, then gradiently increasing or gradiently decreasing the initial threshold to determine the replenishment quantity of the recommended object comprises:

6. The method of claim 4, wherein determining the replenishment quantity of the recommended object according to the pre-recommended inventory quantity and a current inventory threshold value, or determining the replenishment quantity of the recommended object after adjusting the initial threshold value, further comprises:

7. A device for restocking a warehouse, comprising:

8. The apparatus of claim 7, wherein the adjustment module is further configured to:

9. An electronic device for warehouse restocking, comprising:

one or more processors;

a storage device for storing one or more programs,

when executed by the one or more processors, cause the one or more processors to implement the method of any one of claims 1-6.

10. A computer-readable medium, on which a computer program is stored, which, when being executed by a processor, carries out the method according to any one of claims 1-6.