Commodity replenishment quantity determination method and related device

Abstract

The invention provides a commodity replenishment quantity determination method and a related device, and relates to the technical field of self-service sales. The commodity replenishment quantity determination method is applied to a host of the self-service sales system, the self-service sales system further comprises a vending machine, and the vending machine is in communication connection with the host. A plurality of types of commodities are stored in the vending machine. The method comprises the following steps: firstly, obtaining the total quantity of to-be-replenished goods, the sales volume of each commodity and the sales weight of each commodity; wherein the sum of the sales weight of each commodity is 1, then determining the sales proportion of each commodity according to the sales volume of each commodity, determining the weight proportion of each commodity according to the sales weight of each commodity, and then determining the replenishment proportion of each commodity according to the sales proportion and the weight proportion of each commodity, and finally, determining the replenishment quantity of each commodity according to the total quantity of the commodities to be replenished and the replenishment proportion of each commodity. The commodity replenishment quantity determination method and the related device provided by the invention have the advantages that the replenishment frequency can be reduced, and the workload of workers is reduced.

Description

Technical Field

[0001] The present application relates to the field of self-service sales technology, and in particular to a method for determining the quantity of replenishment of goods and a related device. Background Art

[0002] Since self-service vending machines have the advantages of small footprint and convenient sales, they are widely used in various places. In the current sales model, users generally scan codes to pay and obtain goods.

[0003] In a sales model where users can scan a code to watch an advertisement and get a product for free, it is necessary to set up multiple types of products in the self-service vending machine to attract different users. Therefore, when the products in the self-service vending machine are about to be taken out, they need to be replenished in time.

[0004] Existing self-service vending machines usually manage product replenishment based on fixed time intervals or simple sales volume. This method can easily lead to some products selling faster than others, causing some products to be out of stock frequently while others may be in excess. This not only affects the customer's shopping experience, but also increases the frequency and labor intensity of replenishment for staff.

[0005] In summary, the existing technology has the problem that the replenishment frequency of the self-service vending machine is high and the workload of the staff is high. Summary of the invention

[0006] The purpose of the present application is to provide a method for determining the replenishment quantity of goods and a related device to solve the problems existing in the prior art of high replenishment frequency of self-service vending machines and high workload of staff.

[0007] In order to achieve the above purpose, the technical solution adopted in the embodiment of the present application is as follows:

[0008] In a first aspect, an embodiment of the present application provides a method for determining a replenishment quantity of a commodity, which is applied to a host of a self-service sales system, wherein the self-service sales system further includes a vending machine, which is communicatively connected to the host; the vending machine stores multiple types of commodities; the method includes:

[0009] Get the total quantity to be replenished, the sales volume of each product, and the sales weight of each product; the sum of the sales weights of all types of products is 1;

[0010] Determine the sales ratio of each commodity according to the sales volume of each commodity, and determine the weight ratio of each commodity according to the sales weight of each commodity;

[0011] Determine the replenishment ratio of each commodity according to the sales ratio of each commodity and the weight ratio of each commodity;

[0012] The replenishment quantity of each commodity is determined according to the total quantity to be replenished and the replenishment ratio of each commodity.

[0013] Optionally, the replenishment ratio satisfies the formula:

[0014] W i =αS i +βP i

[0015] Among them, W i represents the replenishment ratio of the i-th commodity, S i represents the sales proportion of the i-th commodity, P i It represents the weight ratio of the i-th commodity, α and β are coefficients, α+β=1, and α>β.

[0016] Optionally, after the step of determining the replenishment quantity of each commodity according to the total quantity to be replenished and the replenishment ratio of each commodity, the method further includes:

[0017] When the determined replenishment quantity of the commodity is not an integer, add the decimals of the replenishment quantities of all types of commodities and obtain the decimal sum;

[0018] The commodities with non-integer replenishment quantities are arranged in descending order, and the replenishment quantities of the first n categories of commodities are increased by 1, and the replenishment quantities of the remaining categories of commodities are removed from the decimals; wherein the value of n is equal to the sum of the decimals.

[0019] Optionally, the step of obtaining the sales weight of each commodity includes:

[0020] Obtaining current date information and location information of the vending machine;

[0021] Determine the date parameter of each commodity according to the date information and a preset first parameter comparison table, and determine the location parameter of each commodity according to the location information and a preset second parameter comparison table;

[0022] The sales weight of each commodity is determined according to the date parameter and the location parameter.

[0023] Optionally, the sales weight of each commodity satisfies the formula:

[0024]

[0025] Among them, P i represents the sales weight of the i-th commodity, M i Represents the location parameter of the i-th commodity, N i Indicates the date parameter of the i-th commodity.

[0026] Optionally, the method further comprises:

[0027] Get the remaining quantity of each product and the sales speed of each product;

[0028] After the step of determining the replenishment quantity of each commodity according to the total quantity to be replenished and the replenishment ratio of each commodity, the method further includes:

[0029] Predict the number of days each product will be sold based on the remaining quantity of each product, the replenishment quantity of each product, and the sales speed of each product;

[0030] Determine whether the date parameter changes within the sales days;

[0031] If yes, determine the sales weight of each product by time period.

[0032] Optionally, after the step of determining the date parameter of each commodity according to the date information and a preset first parameter comparison table, and determining the location parameter of each commodity according to the location information and a preset second parameter comparison table, the method further includes:

[0033] Determine whether the date parameter of each product is the same as the date parameter of the last replenishment, and the location parameter of each product is the same as the location parameter of the last replenishment;

[0034] If yes, the replenishment ratio determined during the last replenishment is used as the current weight ratio;

[0035] If not, the step of determining the weight ratio of each commodity according to the sales weight of each commodity is performed.

[0036] In a second aspect, an embodiment of the present application further provides a device for determining the replenishment quantity of a commodity, which is applied to a self-service sales system, wherein the self-service sales system includes a vending machine and a host, wherein the vending machine is communicatively connected to the host; the vending machine stores multiple types of commodities; and the device includes:

[0037] The data acquisition module is used to obtain the total quantity to be replenished, the sales volume of each commodity, and the sales weight of each commodity; wherein the sum of the sales weight of each commodity is 1;

[0038] Data processing module: determining the sales ratio of each commodity according to the sales volume of each commodity, and determining the weight ratio of each commodity according to the sales weight of each commodity;

[0039] The data processing module is further used to determine the replenishment ratio of each commodity according to the sales ratio and the weight ratio;

[0040] The data processing module is also used to determine the replenishment quantity of each commodity according to the total quantity to be replenished of each commodity and the replenishment ratio of each commodity.

[0041] In a third aspect, an embodiment of the present application further provides an electronic device, including:

[0042] A memory for storing one or more programs;

[0043] processor;

[0044] When the one or more programs are executed by the processor, the above method is implemented.

[0045] In a fourth aspect, an embodiment of the present application further provides a computer-readable storage medium having a computer program stored thereon, which implements the above-mentioned method when executed by a processor.

[0046] Compared with the prior art, this application has the following beneficial effects:

[0047] The present application provides a method for determining the replenishment quantity of goods and a related device, which is applied to the host of a self-service sales system, and the self-service sales system also includes a vending machine, which is connected to the host in communication; multiple types of goods are stored in the vending machine. First, the total number of goods to be replenished, the sales volume of each commodity, and the sales weight of each commodity are obtained; wherein the sum of the sales weights of each commodity is 1, and then the sales ratio of each commodity is determined according to the sales volume of each commodity, the weight ratio of each commodity is determined according to the sales weight of each commodity, and then the replenishment ratio of each commodity is determined according to the sales ratio of each commodity and the weight ratio of each commodity, and finally the replenishment quantity of each commodity is determined according to the total number of goods to be replenished and the replenishment ratio of each commodity. Because the present application can use the sales ratio and weight ratio of each commodity to predict the possible sales speed of each commodity when determining the replenishment quantity of each commodity, and then adjust the corresponding replenishment ratio. Make the sales completion time of each commodity in the vending machine relatively balanced, thereby extending the replenishment interval time, reducing the replenishment frequency, and reducing the workload of the staff.

[0048] In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, preferred embodiments are specifically cited below and described in detail with reference to the attached drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments will be briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0050] Figure 1 A schematic diagram of the modules of the self-service sales system provided in an embodiment of the present application.

[0051] Figure 2 A schematic diagram of a module of a host provided in an embodiment of the present application.

[0052] Figure 3 This is a first exemplary flowchart of a method for determining a commodity replenishment quantity provided in an embodiment of the present application.

[0053] Figure 4 Provided in the embodiments of this application Figure 3 An exemplary flowchart of the sub-steps of S102.

[0054] Figure 5 A second exemplary flowchart of the method for determining the commodity replenishment quantity provided in an embodiment of the present application.

[0055] Figure 6 This is a third exemplary flow chart of the method for determining the commodity replenishment quantity provided in an embodiment of the present application.

[0056] Figure 7 A schematic diagram of a module of a device for determining a commodity replenishment quantity provided in an embodiment of the present application.

[0057] In the figure:

[0058] 110 - sales; 120 - host; 121 - processor; 122 - memory; 123 - communication bus; 130 - client; 200 - commodity replenishment quantity determination device; 210 - data acquisition module; 220 - data processing module. DETAILED DESCRIPTION

[0059] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments. The components of the embodiments of the present application described and shown in the drawings here can be arranged and designed in various different configurations.

[0060] Therefore, the following detailed description of the embodiments of the present application provided in the accompanying drawings is not intended to limit the scope of the present application for which protection is sought, but merely represents selected embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the field without creative work are within the scope of protection of the present application.

[0061] It should be noted that similar reference numerals and letters represent similar items in the following drawings, so once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings. At the same time, in the description of this application, the terms "first", "second", etc. are only used to distinguish the description and cannot be understood as indicating or implying relative importance.

[0062] It should be noted that, in this document, relational terms such as first and second, etc. are merely used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations.

[0063] In conjunction with the accompanying drawings, some embodiments of the present application are described in detail below. In the absence of conflict, the following embodiments and features in the embodiments can be combined with each other.

[0064] As described in the background art, currently, the replenishment mechanism for self-service vending machines generally adopts a fixed time for replenishment, or replenishment is performed when the goods are sold out.

[0065] For the sales model where users scan the code to see the advertisement and receive the goods for free, in order to attract users to scan the code, it is generally necessary to set up a variety of goods in the self-service vending machine. On this basis, if the method of restocking at a fixed time is adopted, it may lead to the situation that all the goods have been received but not restocked in time, resulting in user loss. Therefore, it is generally adopted to restock the self-service vending machine in time when the goods are about to be received.

[0066] However, since there are many types of goods in the self-service vending machines, it is common that a certain type of goods has been taken away, but there are still many other goods left. For example, when a self-service vending machine is placed in a children's playground and the goods in the self-service vending machine include toys, the toys may be taken away quickly, while there are still many other types of goods left. When one of the goods is taken away, the staff needs to quickly restock it to ensure that there are enough types of goods, thereby attracting users to scan the code to see the advertisement or pay to take it.

[0067] Therefore, the prior art has the problem that the time for picking up each commodity is uneven, resulting in a high replenishment frequency and a heavy workload for the staff.

[0068] In view of this, in order to solve the above-mentioned problem, an embodiment of the present application provides a method for determining the replenishment quantity of goods, so as to achieve a relatively balanced collection completion time for each product.

[0069] It should be noted that the method for determining the quantity of replenishment of goods provided in this application is applied to the self-service sales system. Figure 1The self-service sales system includes a vending machine 110 and a host 120, and the vending machine 110 is in communication connection with the host 120. Of course, the self-service sales system may also include a client 130. The host 120 may be a backend server, and the client 130 may be a port used by staff.

[0070] It can be understood that there can be multiple vending machines 110, which are arranged in different areas, and each vending machine 110 can communicate with the host 120 and send relevant information to the host 120. For example, when the user picked up the goods and the type of the picked up goods are sent to the host 120. In one implementation, each vending machine 110 is provided with a number. When the host 120 sends an information acquisition instruction to the vending machine 110, the vending machine 110 sends the relevant data and its number information to the host 120. After receiving the relevant data, the host 120 determines the replenishment quantity required for each type of goods in this replenishment, sends the replenishment quantity to the client 130, and prompts the staff to replenish the goods.

[0071] On this basis, the commodity replenishment quantity determination method provided by this application can be applied to the host. Figure 2 A schematic structural block diagram of a host 120 provided in an embodiment of the present application is shown, and the host 120 includes a memory 122, a processor 121, and a communication bus 123. The memory 122, the processor 121, and the communication bus 123 are electrically connected to each other directly or indirectly to achieve data transmission or interaction. For example, these components can be electrically connected to each other through one or more communication buses or signal lines.

[0072] The memory 122 can be used to store software programs and modules, such as program instructions or modules corresponding to the device for determining the quantity of replenishment of goods provided in the embodiment of the present application. The processor 121 executes the software programs and modules stored in the memory 122 to perform various functional applications and data processing, thereby executing the steps of the method for determining the quantity of replenishment of goods provided in the embodiment of the present application. The communication bus 123 can be used to communicate signaling or data with other node devices.

[0073] Among them, the memory 122 can be, but is not limited to, random access memory (Random Access Memory, RAM), read only memory (Read Only Memory, ROM), programmable read-only memory (Programmable Read-Only Memory, PROM), erasable programmable read-only memory (Erasable Programmable Read-Only Memory, EPROM), electrically erasable programmable read-only memory (Electric Erasable Programmable Read-Only Memory, EEPROM), etc.

[0074] The processor 121 may be an integrated circuit chip with signal processing capability. The processor 121 may be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it may also be a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0075] Understandably, Figure 2 The structure shown is for illustration only. The host may also include Figure 2 More or fewer components as shown, or with Figure 2 Different configurations are shown. Figure 2 Each component shown in the figure can be implemented by hardware, software or a combination thereof.

[0076] The following uses the host as an exemplary execution entity to exemplify the method for determining the replenishment quantity of goods provided in the embodiment of the present application.

[0077] See also Figure 3 The method for determining the quantity of replenishment of goods provided in this application includes:

[0078] S102, obtaining the total quantity to be replenished, the sales volume of each commodity, and the sales weight of each commodity; wherein the sum of the sales weight of each commodity is 1.

[0079] S104, determining the sales ratio of each commodity according to the sales volume of each commodity, and determining the weight ratio of each commodity according to the sales weight of each commodity.

[0080] S106, determining the replenishment ratio of each commodity according to the sales ratio of each commodity and the weight ratio of each commodity.

[0081] S108, determining the replenishment quantity of each commodity according to the total quantity to be replenished and the replenishment ratio of each commodity.

[0082] In this application, the sales ratio and weight ratio of each commodity are used to predict the possible sales speed of each commodity, and then the corresponding replenishment ratio is adjusted and the corresponding replenishment is performed. Then, the replenishment quantity of each commodity can be adjusted so that the sales completion time of each commodity in the vending machine is relatively balanced, thereby extending the replenishment interval and reducing the replenishment frequency.

[0083] For example, in the traditional replenishment method, if the vending machine can accommodate 400 items, and the vending machine includes 4 types of goods, namely A, B, C, and D, then when replenishing, A, B, C, and D are 100 pieces respectively. If the average pick-up speed of A is 40 pieces / day, the average pick-up speed of B is 30 pieces / day, the average pick-up speed of C is 20 pieces / day, and the average pick-up speed of D is 10 pieces / day, then after 2.5 days, A has been picked up, but only 25 pieces of D have been picked up, and there are 25 pieces of B, 50 pieces of C, and 75 pieces of D left in the vending machine. However, in order to attract users and ensure that there are enough types of goods in the vending machine, the vending machine needs to be replenished in time after A is picked up. It can be understood that in this replenishment, A needs to be replenished with 100 pieces, B needs to be replenished with 75 pieces, C needs to be replenished with 50 pieces, and D needs to be replenished with 25 pieces.

[0084] However, if the replenishment ratio is adjusted so that the replenishment quantity of the goods with faster collection speed is higher among the goods after replenishment, it can be ensured that the time for each type to be collected is relatively balanced. For example, if after replenishment, A is 160 pieces, B is 120 pieces, C is 80 pieces, and D is 40 pieces, then according to the previous collection speed, the average time for A, B, C, and D to be collected is 4 days, so the staff can replenish after 4 days. Compared with the current replenishment after 2.5 days, after adjusting the replenishment quantity, the replenishment interval can be significantly extended, thereby reducing the workload of the staff.

[0085] The following is a step-by-step description of the solution provided in this application:

[0086] When staff is needed to restock, the host can obtain relevant data. Among them, the sales data of the vending machine (i.e., the data of the goods being picked up) can be uploaded in real time, or it can be uploaded to the host only when the replenishment quantity is determined, which is not limited in this application.

[0087] In one implementation, the staff can proactively replenish the goods. For example, the staff can send a replenishment instruction to the host through the client, and the host determines the replenishment quantity of each commodity and sends the replenishment quantity of each commodity to the client. In another implementation, the host can determine the replenishment quantity of each commodity and send the replenishment quantity of each commodity to the client when the goods in the vending machine are almost sold out.

[0088] When the host determines the replenishment quantity of each product, it needs to obtain the total quantity to be replenished, the sales volume of each product, and the sales weight of each product. Among them, the sum of the sales volume of each product is the total quantity to be replenished.

[0089] After the user scans the code to receive the product, the vending machine can record the type of product currently being sold and the time of sale, which is convenient for the host to count.

[0090] Among them, the actual sales volume of each commodity can be determined based on the statistical data, and the estimated sales volume of each commodity can be determined by determining the sales weight of each commodity. Then, the current required replenishment volume can be estimated based on the actual sales volume and the estimated sales volume.

[0091] The applicant found through statistics that the sales weight of each commodity is mainly related to the current time and the location of the vending machine. For example, when the commodities include seasonal commodities (such as handheld fans), the sales volume in summer is significantly higher than that in winter; or, when a certain activity is held at a certain time period, the number of active people at the place will increase sharply, and the sales volume of the commodity will increase significantly. Or, when the vending machine is set up downstairs of an office building, if the commodities include office supplies, the office supplies may be sold out quickly; and if the vending machine is set up in a residential area, if the commodities include daily necessities, the daily necessities may be sold out quickly.

[0092] Therefore, when determining sales weight, this application mainly determines it based on date parameters and location parameters. In view of this, please refer to Figure 4 , S122 includes:

[0093] S1021, obtaining the current date information and the location information of the vending machine.

[0094] S1022, determining the date parameter of each commodity according to the date information and a preset first parameter comparison table, and determining the location parameter of each commodity according to the location information and a preset second parameter comparison table.

[0095] S1023, determining the sales weight of each commodity according to the date parameter of each commodity and the location parameter of each commodity.

[0096] Generally speaking, once a vending machine is placed, its location information will not change. Of course, if the vending machine is moved, the location information may also change accordingly. As an implementation method, a positioning module may be set in the vending machine, and once the position of the vending machine changes, the vending machine reports the location information to the host. As another implementation method, when the position of the vending machine changes, the location information may also be manually updated. For example, the staff may send the updated location information to the host through the client. In addition, the host also needs to obtain the current date information in real time and determine the relevant parameters based on the date information.

[0097] Specifically, the date parameter of each commodity can be determined through date information and a preset first parameter comparison table. The preset first parameter comparison table is provided with the date parameter of each commodity on the current date, and the date parameter represents the sales probability of each commodity on the date. The first parameter comparison table can be adjusted dynamically.

[0098] For example, if a vending machine is set up in a living area, during the winter and summer vacations, the activity of children at home increases. Therefore, the probability of selling toys, stationery and other products that are biased towards children increases, and its date parameter should be increased.

[0099] Alternatively, if the vending machine is set up in a sports stadium or other place, if a certain sports competition is to be held during a certain period, the number of people at the venue will increase sharply, so the date parameters of sports-related products can be adjusted higher. Alternatively, if a certain writing competition is to be held during a certain period, the number of people at the venue will increase sharply, so the date parameters of stationery-related products can be adjusted higher.

[0100] Similarly, the location parameters can also be determined in the same way. In the preset second parameter comparison table, the location parameters of each commodity at the current location are set, and the location parameters represent the sales probability of each commodity at the location. Generally speaking, the second parameter comparison table is relatively fixed, and the content of the second parameter comparison table will only change when the location of the vending machine changes.

[0101] For the determination of location parameters, the main thing is to predict the possible active people at the location and the types of goods that the active people may select. For example, when the vending machine is set up downstairs in an office building, the office staff are more active, so the probability of office supplies being sold is greater, and a higher location parameter can be set. The probability of household goods being sold is relatively small, so a smaller location parameter can be set. However, if the same vending machine is set downstairs in a residential area, the residents are more active, so the probability of household goods being sold is relatively large, and a larger location parameter can be set; while the probability of office supplies being sold is small, so a smaller location parameter can be set.

[0102] After determining the date parameters and location parameters, the sales weight of each product can be determined accordingly.

[0103] Among them, the sales weight of each commodity satisfies the formula:

[0104]

[0105] Among them, P i represents the weight ratio of the i-th commodity, M i Represents the location parameter of the i-th commodity, N i Indicates the date parameter of the i-th commodity.

[0106] That is, in this application, the corresponding sales weight is determined by balancing the date parameter and location parameter of each commodity. Since the sum of the sales weights of all types of commodities is required to be 1, the sales weight or date parameter and location parameter need to be processed.

[0107] In one implementation, the sum of the date parameters of all types of goods can be set to 1, and the sum of the position parameters can be set to 1. In this case, the sum of the sales weights of all types of goods is also determined to be 1. For example, four types of goods A, B, C, and D are set in the vending machine, and the date parameters of A, B, C, and D are 0.4, 0.3, 0.2, and 0.1 respectively, and the position parameters of A, B, C, and D are 0.3, 0.2, 0.2, and 0.3 respectively. Then, the sales weights of A, B, C, and D are determined to be 0.35, 0.25, 0.2, and 0.2 respectively.

[0108] In another implementation, the date parameter and the location parameter may not be limited. However, after the sales weight is determined, the sales weight is proportionally increased or decreased until the sum of the sales weights of all types of goods is 1. For example, if the calculated sales weights of A, B, C, and D are 1, 2, 3, and 4, respectively, the sales weights of A, B, C, and D are proportionally decreased to 0.1, 0.2, 0.3, and 0.4, so that the sum of the sales weights of all types of goods is 1.

[0109] When determining the sales weight of each commodity, you can also determine the sales ratio of each commodity at the same time. The sales ratio is the ratio of the sales volume of each commodity to the total sales volume. For example, if 50 pieces of A, B, C, and D are sold respectively, the total sales volume is 400, and the total quantity to be replenished is also 400. The sales ratios of A, B, C, and D are all 0.25.

[0110] After determining the sales weight and sales ratio of each commodity, the replenishment ratio of each commodity can be determined accordingly. The replenishment ratio of each commodity satisfies the formula:

[0111] W i =αS i +βPi

[0112] Among them, W i represents the replenishment ratio of the i-th commodity, S i represents the sales proportion of the i-th commodity, P i It represents the weight ratio of the i-th commodity, α and β are coefficients, α+β=1, and α>β.

[0113] From this formula, it can be seen that when determining the actual replenishment ratio, this application estimates the replenishment ratio corresponding to the relatively balanced sales completion time of each commodity in the vending machine based on the actual sales data and the theoretical sales ratio. And because α>β, the actual sales data accounts for a larger proportion of the replenishment ratio determined by this application, making the estimated value more accurate. For example, α is 0.6 and β is 0.4.

[0114] After determining the replenishment ratio of each commodity, the replenishment quantity of each commodity can be determined based on the product of the total quantity to be replenished and the replenishment ratio of each commodity. For example, if the total quantity to be replenished is 400, and the replenishment ratios of A, B, C, and D are 0.2, 0.3, 0.3, and 0.2, then the replenishment quantities of A, B, C, and D are 80, 120, 120, and 80 respectively.

[0115] Of course, in actual applications, it may happen that the replenishment quantity of a product contains decimals, so please refer to Figure 5 , the method further comprises:

[0116] S1091: When the determined replenishment quantity of the commodity is not an integer, the decimals of the replenishment quantities of all types of commodities are added together to obtain the decimal sum.

[0117] S1092, arrange the commodities of which replenishment quantities are non-integer categories in descending order of replenishment quantities, increase the replenishment quantities of the first n categories of commodities by one, and remove decimals from the replenishment quantities of the remaining categories of commodities; wherein the value of n is equal to the sum of decimals.

[0118] For example, if the replenishment quantities of A, B, C, and D are determined to be 47.4, 94.8, 142.2, and 110.6, respectively, then first add the decimals of the replenishment quantities of the four commodities, that is, 0.4+0.8+0.2+0.6=2. Then arrange the four commodities in descending order of replenishment quantity, and the order is C, D, B, A. Finally, the round-up method and the truncation method are used. Since the sum of the decimals is 2, the round-up method is used for the first two commodities, and the truncation method is used for the last two commodities, and the replenishment quantities of A, B, C, and D are determined to be 47, 94, 143, and 111, respectively.

[0119] By combining the rounding up method with the truncation method, it can be ensured that when there is a decimal in the determined replenishment quantity, the goods with a greater sales probability are replenished first, thereby ensuring to a greater extent the balance of various types of goods when they are sold out.

[0120] In addition, the date parameters may change when determining the replenishment quantity of each product. For example, if the replenishment is carried out on January 1, but on January 3, a large-scale reading event is held in the area where the vending machine is located, the sales volume of stationery products will increase at this time, but it will not be affected during January 1 to January 2.

[0121] In view of this, please refer to Figure 6 , the method further comprises:

[0122] S110, obtaining the remaining quantity of each commodity and the sales speed of each commodity.

[0123] S112, predicting the sales days of each commodity based on the remaining quantity of each commodity, the replenishment quantity of each commodity, and the sales speed of each commodity.

[0124] S114, determine whether the date parameter changes within the sales days; if yes, execute S116, if not, execute S118.

[0125] S116, determining the sales weight of each commodity by time period, and re-determining the replenishment quantity of each commodity.

[0126] S118, maintain the replenishment quantity of each commodity.

[0127] That is, after determining the replenishment quantity of each commodity, the number of days the commodity can be sold can be predicted according to the sales speed of each commodity. The sales speed can be the historical average sales speed or the sales speed during the last sales process. For example, if the last replenishment was 10 days ago and 100 pieces of commodity A need to be replenished during this replenishment, the sales speed of commodity A is determined to be 10 pieces / day.

[0128] Based on the sales speed and the total amount of goods after replenishment, the predicted sales days of the goods can be determined. For example, if the replenishment quantity of product A is 100 pieces and there are 10 pieces left in the vending machine, the predicted sales days of product A is 110 / 10=11 days.

[0129] If the current replenishment time is January 1, it can be estimated that product A will be sold out around January 12. Therefore, it can be determined whether there are any changes in the date parameters during this time, such as whether special events are held during this period. If the date parameters change, the replenishment quantity of the product needs to be re-determined. For example, if a special event needs to be held on January 6, the replenishment quantity of the product before January 6 and the replenishment quantity of the product after January 6 can be determined separately, and then the two can be added together. If the date parameters do not change, there is no need to re-determine the replenishment quantity of the product.

[0130] In addition, after step S1022, the method may further include:

[0131] S1024, determine whether the date parameter of each commodity is the same as the date parameter of the last replenishment, and the location parameter of each commodity is the same as the location parameter of the last replenishment; if yes, execute S1025, if not, execute S1023.

[0132] S1025, using the replenishment ratio determined during the last replenishment as the current weight ratio.

[0133] Specifically, when the date parameter and the location parameter have not changed, it indicates that the sales weight has not changed, and the sales of this replenishment are basically similar to the sales of the last replenishment. Therefore, the replenishment ratio determined at the last replenishment can be used as the current weight ratio.

[0134] Among them, since the replenishment ratio determined at the last replenishment is also determined based on the actual sales ratio and the weight ratio, by determining the replenishment ratio determined last time as the current weight ratio, the weight ratio can be updated each time according to the actual sales situation. In addition, since the sales ratio accounts for a larger proportion than the weight ratio when the replenishment ratio is determined each time, the actual sales situation is more closely matched in each assignment process, thereby making the replenishment quantity of each commodity determined more accurate, ensuring that the sales completion time of each commodity in the vending machine is more balanced, and achieving the effect of minimizing the replenishment frequency.

[0135] Based on the above implementation, please refer to Figure 7 The embodiment of the present application also provides a commodity replenishment quantity determination device 200, which is applied to a self-service sales system. The self-service sales system includes a vending machine and a host, and the vending machine and the host are in communication connection; the vending machine stores multiple types of commodities; the device includes:

[0136] The data acquisition module 210 is used to obtain the total quantity to be replenished, the sales volume of each commodity and the sales weight of each commodity; wherein the sum of the sales weight of each commodity is 1.

[0137] It can be understood that the above S122 can be executed by the data acquisition module 210 .

[0138] The data processing module 220 is used to determine the sales ratio of each commodity according to the sales volume of each commodity, and determine the weight ratio of each commodity according to the sales weight of each commodity.

[0139] It can be understood that the above S104 can be executed by the data processing module 220 .

[0140] The data processing module 220 is further used to determine the replenishment ratio of each commodity according to the sales ratio of each commodity and the weight ratio of each commodity.

[0141] It can be understood that the above S106 can be executed by the data processing module 220.

[0142] The data processing module 220 is further used to determine the replenishment quantity of each commodity according to the total quantity to be replenished and the replenishment ratio of each commodity.

[0143] It can be understood that the above S108 can be executed by the data processing module 220.

[0144] In summary, the present application provides a method for determining the replenishment quantity of goods and a related device, which is applied to the host of a self-service sales system, and the self-service sales system also includes a vending machine, which is connected to the host in communication; multiple types of goods are stored in the vending machine. First, the total number of goods to be replenished, the sales volume of each commodity, and the sales weight of each commodity are obtained; wherein the sum of the sales weights of each commodity is 1, and then the sales ratio of each commodity is determined according to the sales volume of each commodity, the weight ratio of each commodity is determined according to the sales weight of each commodity, and then the replenishment ratio of each commodity is determined according to the sales ratio of each commodity and the weight ratio of each commodity, and finally the replenishment quantity of each commodity is determined according to the total number of goods to be replenished and the replenishment ratio of each commodity. Because the present application can use the sales ratio and weight ratio of each commodity to predict the possible sales speed of each commodity when determining the replenishment quantity of each commodity, and then adjust the corresponding replenishment ratio. Make the sales completion time of each commodity in the vending machine relatively balanced, thereby extending the replenishment interval time, reducing the replenishment frequency, and reducing the workload of the staff.

[0145] In the embodiments provided in the present application, it should be understood that the disclosed devices and methods may also be implemented in other ways. The device embodiments described above are merely schematic, for example, the flowcharts and block diagrams in the accompanying drawings show the possible architectures, functions and operations of the devices, methods and computer program products according to the embodiments of the present application. In this regard, each box in the flowchart or block diagram may represent a module, a program segment or a part of a code, and a module, a program segment or a part of a code includes one or more executable instructions for implementing a specified logical function.

[0146] It should also be noted that in some alternative implementations, the functions marked in the blocks may also occur in a different order than that marked in the accompanying drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in the opposite order, depending on the functions involved.

[0147] It should also be noted that each box in the block diagram and / or flowchart, and combinations of boxes in the block diagram and / or flowchart, can be implemented by a dedicated hardware-based system that performs the specified functions or actions, or can be implemented by a combination of dedicated hardware and computer instructions.

[0148] In addition, the functional modules in the embodiments of the present application may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.

[0149] If the function is implemented in the form of a software function module and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the method of the embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as USB flash drives, mobile hard disks, read-only memories, random access memories, magnetic disks or optical disks.

[0150] Although the present invention is disclosed as above, the present invention is not limited thereto. Any person skilled in the art can make various changes and modifications without departing from the spirit and scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the scope defined by the claims.

Claims

1. A method for determining the quantity of commodity replenishment, characterized in that: A host applied to a self-service sales system, wherein the self-service sales system further comprises a vending machine, wherein the vending machine is communicatively connected to the host; wherein the vending machine stores a plurality of types of commodities; and the method comprises: Get the total quantity to be replenished, the sales volume of each product, and the sales weight of each product; the sum of the sales weights of all types of products is 1; Determine the sales ratio of each commodity according to the sales volume of each commodity, and determine the weight ratio of each commodity according to the sales weight of each commodity; Determine the replenishment ratio of each commodity according to the sales ratio of each commodity and the weight ratio of each commodity; The replenishment quantity of each commodity is determined according to the total quantity to be replenished and the replenishment ratio of each commodity.

2. The method for determining the quantity of commodity replenishment according to claim 1, characterized in that: The replenishment ratio satisfies the formula: W i =αS i +βP i Among them, W i represents the replenishment ratio of the i-th commodity, S i represents the sales proportion of the i-th commodity, P i It represents the weight ratio of the i-th commodity, α and β are coefficients, α+β=1, and α>β.

3. The method for determining the quantity of commodity replenishment according to claim 1, characterized in that: After the step of determining the replenishment quantity of each commodity according to the total quantity to be replenished and the replenishment ratio of each commodity, the method further includes: When the determined replenishment quantity of the commodity is not an integer, add the decimals of the replenishment quantities of all types of commodities and obtain the decimal sum; The commodities with non-integer replenishment quantities are arranged in descending order, and the replenishment quantities of the first n categories of commodities are increased by 1, and the replenishment quantities of the remaining categories of commodities are removed from the decimals; wherein the value of n is equal to the sum of the decimals.

4. The method for determining the quantity of commodity replenishment according to claim 1, characterized in that: The steps to obtain the sales weight of each product include: Obtaining current date information and location information of the vending machine; Determine the date parameter of each commodity according to the date information and a preset first parameter comparison table, and determine the location parameter of each commodity according to the location information and a preset second parameter comparison table; The sales weight of each product is determined according to the date parameter of each product and the location parameter of each product.

5. The method for determining the quantity of commodity replenishment according to claim 4, characterized in that: The sales weight of each commodity satisfies the formula: Among them, P i represents the sales weight of the i-th commodity, M i Represents the location parameter of the i-th commodity, N i Indicates the date parameter of the i-th commodity.

6. The method for determining the quantity of commodity replenishment according to claim 4, characterized in that: The method further comprises: Get the remaining quantity of each product and the sales speed of each product; After the step of determining the replenishment quantity of each commodity according to the total quantity to be replenished and the replenishment ratio of each commodity, the method further includes: Predict the number of days each product will be sold based on the remaining quantity of each product, the replenishment quantity of each product, and the sales speed of each product; Determine whether the date parameter changes within the sales days; If yes, determine the sales weight of each product by time period.

7. The method for determining the quantity of commodity replenishment according to claim 4, characterized in that: After the steps of determining the date parameter of each commodity according to the date information and a preset first parameter comparison table, and determining the location parameter of each commodity according to the location information and a preset second parameter comparison table, the method further includes: Determine whether the date parameter of each product is the same as the date parameter of the last replenishment, and the location parameter of each product is the same as the location parameter of the last replenishment; If yes, the replenishment ratio determined during the last replenishment is used as the current weight ratio; If not, the step of determining the weight ratio of each commodity according to the sales weight of each commodity is performed.

8. A device for determining the quantity of replenishment of goods, characterized in that: Applied to a self-service sales system, the self-service sales system includes a vending machine and a host, the vending machine is in communication connection with the host; the vending machine stores multiple types of commodities; the device includes: The data acquisition module is used to obtain the total quantity to be replenished, the sales volume of each commodity, and the sales weight of each commodity; wherein the sum of the sales weight of each commodity is 1; Data processing module: determining the sales ratio of each commodity according to the sales volume of each commodity, and determining the weight ratio of each commodity according to the sales weight of each commodity; The data processing module is further used to determine the replenishment ratio of each commodity according to the sales ratio of each commodity and the weight ratio of each commodity; The data processing module is also used to determine the replenishment quantity of each commodity according to the total quantity to be replenished and the replenishment ratio of each commodity.

9. An electronic device, characterized in that: include: A memory for storing one or more programs; processor; When the one or more programs are executed by the processor, the method according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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