Intelligent canteen-oriented purchase form automatic generation method and system

Abstract

The application relates to the technical field of big data processing, in particular to a purchase form automatic generation method and system for a smart canteen, which comprises the following steps: acquiring the order quantity of all dishes every day, the quantity of each raw material used by each dish, the inventory of each raw material in the current inventory and the storage time of each raw material; according to the order quantity change of different dishes every day, combining the order quantity of all dishes every day, the substitutability between different dishes and the expected order quantity of each dish are acquired; further combining the quantity of each raw material used by each dish, the expected consumption of each raw material is acquired; combining the expected consumption of each raw material and the storage time of each raw material, the purchase quantity of each raw material in the purchase form is acquired. The application can accurately predict the consumption of various raw materials by analyzing the substitutability between dishes and the difference in raw materials, and the purchase form generated based on the same can effectively avoid the waste of raw materials and the occurrence of out-of-stock.

Description

Technical Field

[0001] This invention relates to the field of big data processing technology, specifically to a method and system for automatically generating purchase forms for smart canteens. Background Technology

[0002] A smart canteen refers to the digital and intelligent upgrade of a traditional canteen through modern information technologies such as artificial intelligence, big data, the Internet of Things, and cloud computing, thereby improving the canteen's operational efficiency, service quality, and management level. Traditional canteen procurement often relies on manual order counting, inventory reports, and experience-based forecasts, resulting in long statistical cycles, information lag, stockouts or overstocking, highly manual form creation that is prone to errors and difficult to reuse, lack of automatic integration with backend inventory, budget, and supplier systems, and high management costs. Therefore, to achieve efficient operation and refined management of a smart canteen, it is necessary to predict the future raw material demand for each dish based on the smart canteen's ordering system and historical order numbers, and automatically generate procurement forms by combining current inventory and safety stock thresholds. This not only effectively avoids raw material waste and stockouts in smart canteens but also improves procurement efficiency, ensures stable meal supply, and reduces the risk of judgment errors caused by manual intervention. This promotes inventory turnover, reduces spoilage, and provides accurate data support for financial control and operational decisions, making it a key step in achieving "on-demand procurement and scientific replenishment." Summary of the Invention

[0003] This invention provides a method and system for automatically generating purchase forms for smart canteens to solve existing problems: traditional canteen procurement often relies on manual summarization of order numbers, inventory reports and experience-based forecasts, which results in long statistical cycles and information lag, leading to stockouts or excessive stockpiling.

[0004] The automatic procurement form generation method and system for smart canteens of the present invention adopts the following technical solution: Get the number of orders for all dishes every day within the historical reference range, the amount of each ingredient used in each dish, the current inventory of each ingredient, and the shelf life of each ingredient; Based on the daily order count of all dishes within the historical reference range, we obtain the prevalence of each dish within that range. Combining this with the daily order count changes for different dishes within the historical reference range, we obtain the substitutability between them. Based on the daily order count of all dishes within the historical reference range, we obtain the initial projected order count for all dishes. Combining this with the substitutability between different dishes, we obtain the initial projected correction coefficient for each dish, and then correct the initial projected order count for each dish to obtain the projected order count for each dish. Based on the expected number of orders for each dish and the amount of each raw material used in each dish, the baseline expected consumption of each raw material is obtained. The baseline expected consumption of each raw material is then adjusted according to the substitutability between different dishes to obtain the expected consumption of each raw material. Based on the storage time of each raw material, obtain the redundancy coefficient of each raw material, and combine it with the expected consumption of each raw material to obtain the purchase quantity of each raw material in the purchase order.

[0005] Preferably, the method for obtaining the prevalence of each day within the historical reference range based on the number of orders for all dishes each day includes: For the first within the historical reference range The day, within the scope of historical reference. The absolute value of the difference between the total number of orders for all dishes on a given day and the average total number of orders for all dishes on all days within the historical reference range is inversely normalized. This inversely normalized result is then used as the [value] of the [number]th [item] within the historical reference range. The prevalence of the sky.

[0006] Preferably, the specific method for obtaining the substitutability between different dishes is as follows: For the first in the historical reference range The first day The dish will be the first The average number of orders for each dish per day within the historical reference range compared to the number of orders for the [number]th dish per day. This dish is the [number]th dish within the historical reference range. The difference between the number of orders per day is used as the first day within the historical reference range. The first day Sales trends of individual dishes; For the first in the historical reference range The first day The dish and the first The dish will be the first in the historical reference range. The first day The sales trend of individual dishes and the historical reference range The first day The product of the sales trends of each dish is used as the first... The dish and the first This dish is the [number]th dish within the historical reference range. The trend of coordinated change over the days will be the first The dish and the first This dish is the [number]th dish within the historical reference range. The trend of coordinated changes in the sky and the historical reference range The product of the universality of the days, as the first The dish and the first This dish is the [number]th dish within the historical reference range. The trend of synergistic change in the sky; The first The standard deviation of daily order volume for each dish within the historical reference range and the first The product of the daily order volume standard deviations for each dish within the historical reference range is used as the first... The dish and the first The degree of fluctuation in the number of orders for each dish within the historical reference range; The first The dish and the first The average daily revised co-variance trend of each dish within the historical reference range, compared to the previous day... The dish and the first The inverse of the ratio of the fluctuation in the number of orders for each dish within the historical reference range is used as the first... The dish and the first Substitutability between dishes.

[0007] Preferably, the method for obtaining the initial estimated order number for all dishes based on the daily order number for all dishes within the historical reference range includes: For the For each dish, a preset prediction range is given. Based on the ARIMA algorithm, through the first The number of orders for each dish per day within the historical reference range, predicting future... Heavenly The number of orders for each dish; in the future Heavenly The number of orders for each dish is denoted as the nth. Preliminary estimated order volume for each dish.

[0008] Preferably, the specific method for obtaining the initial prediction correction coefficient for each dish is as follows: For the The dish will be the first The average number of orders for each dish is expected to be within the forecast range, compared to the number of orders for the first dish. The difference between the average daily order volume for each dish within the historical reference range is used as the first... The projected sales change value for each dish will be the first The expected sales change of the first dish and the first The ratio of the average number of orders for each dish to the average number of orders per day within the historical reference range is used as the first... Projected sales growth rate for each dish; Obtain the projected sales growth rate for all dishes; For the The dish and the first Each dish, as described , No. The dish and the first Substitutability between dishes and the first The product of the projected sales growth rate of each dish will be used as the first... The dish is for the first The expected sales adjustment factor for each dish will be applied to all dishes in relation to the first dish. The sum of the expected sales correction factors for each dish is mapped to a range of -1 to 1, and the mapping result of the sum is used as the first... The initial prediction correction factor for each dish.

[0009] Preferably, the specific method for obtaining the estimated order quantity for each dish is as follows: For the The dish, combining 1 and the first The difference in the initial predicted correction factor for each dish, multiplied by the first... The product of the initial projected order numbers for each dish is used as the basis for determining the order quantity for the first dish. The estimated number of orders for each dish.

[0010] Preferably, the method for obtaining the baseline estimated consumption of each raw material based on the expected order quantity of each dish and the amount of each raw material used in each dish, and then adjusting the baseline estimated consumption of each raw material according to the substitutability between different dishes, to obtain the estimated consumption of each raw material includes: For any dish, the product of the expected number of orders for the dish and the quantity of each raw material used in the dish is used as the initial expected consumption of each raw material for the dish. For the One type of raw material, consuming all the ingredients for the first dish The sum of the primary consumption of each type of raw material is used as the basis for determining the amount of the first type of raw material consumed. The baseline estimated consumption of the raw materials; For the The dish and the first The dish, according to the first The dish uses the first The amount of the first raw material and the second The dish uses the first The absolute value of the difference between the quantities of the first and second raw materials is used as the first... The dish and the first The dish is in The difference in consumption of the first type of raw material will be the first The dish uses the first The amount of the first raw material and the second The dish uses the first The sum of the quantities of the various raw materials is used as the first... The dish and the first The consumption of each dish The total amount of each type of raw material; the first The dish and the first The dish is in The difference in consumption of one type of raw material and the first type The dish and the first The consumption of each dish The ratio of the total amount of each type of raw material is used as the first... The dish and the first The dish is in The degree of difference in the amount of raw materials used; According to the The baseline estimated consumption of each raw material, combined with the total consumption of all different dishes in the first... The degree of difference in the amount of raw materials used and the substitutability among all different dishes were used to obtain the first The estimated consumption of these raw materials.

[0011] Preferably, the acquisition of the first The estimated consumption of these raw materials, including the specific methods, is as follows: In the formula, Indicates the first The estimated consumption of these raw materials; Indicates the quantity of dishes; Indicates the first The baseline estimated consumption of the raw materials; Indicates the first The dish and the first Substitutability between dishes; Indicates the first The dish and the first The dish is in The degree of difference in the amount of raw materials used.

[0012] Preferably, the specific method for obtaining the redundancy coefficient of each raw material based on its shelf life, and combining this with the expected consumption of each raw material to obtain the purchase quantity of each raw material in the purchase order, includes: A primary redundancy coefficient is preset, for the first... The first type of raw material, for the first The shelf life of each raw material is linearly normalized, specifically within the range of shelf life for all raw materials; the shelf life of the first raw material is then linearly normalized. The product of the linearly normalized result of the shelf life of the first raw material and the primary redundancy coefficient is used as the product of the second raw material's shelf life. Redundancy coefficient of raw materials; The first item in the procurement form The specific methods for determining the purchase quantity of various raw materials are as follows: In the formula, Indicates the first item in the purchase form The amount of raw materials purchased; Indicates the first Redundancy coefficient of raw materials; Indicates the first The estimated consumption of these raw materials; Indicates the number of items in the current inventory. The stock of various raw materials.

[0013] Another embodiment of the present invention provides an automatic purchase form generation system for smart canteens, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps of any of the above-described automatic purchase form generation methods for smart canteens.

[0014] The beneficial effects of the technical solution of this invention are as follows: Since the raw materials of different dishes may overlap, that is, one raw material may be used to make multiple dishes, and the total number of orders in the canteen is usually stable every day, but the order numbers of different dishes in the canteen have a certain degree of substitutability. If the future order number of a dish is predicted simply based on the historical order number of a certain dish, without considering the overlap in the raw materials used by different dishes and the substitutability between different dishes, the generated purchase form may not accurately reflect the consumption of various raw materials in the smart canteen. Therefore, this application obtains the substitutability between different dishes by combining the daily order number changes of different dishes with the daily order number of all dishes; thereby correcting the initial estimated order number of each dish and accurately obtaining the estimated order number of each dish. Furthermore, since the raw materials used in different dishes in the canteen may overlap to some extent, and there is a certain degree of substitutability between different dishes, simply generating the purchase quantity of all raw materials based on the expected order quantity of all dishes and the raw materials used in all dishes may lead to structural redundancy of raw materials due to fluctuations in dish demand. By calculating the expected order quantity of each dish, combined with the quantity of each raw material used in each dish and the substitutability between different dishes, the expected consumption of each raw material can be obtained. Finally, by combining the expected consumption of each raw material with its shelf life, the purchase quantity of each raw material in the purchase order can be obtained. This generates a purchase order for the smart canteen, which can effectively avoid raw material waste and stockouts, thereby improving procurement efficiency, ensuring stable meal supply, and reducing the risk of judgment errors caused by human intervention. This promotes inventory turnover, reduces spoilage, and provides accurate data support for financial control and operational decisions, ultimately achieving "on-demand procurement and scientific replenishment." Attached Figure Description

[0015] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 This is a flowchart illustrating the steps of the automatic generation method for purchase forms in smart canteens according to the present invention. Detailed Implementation

[0017] To further illustrate the technical means and effects adopted by the present invention to achieve its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of the automatic generation method and system for purchasing forms for smart canteens proposed according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0018] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0019] The following description, in conjunction with the accompanying drawings, details the specific solution of the automatic procurement form generation method and system for smart canteens provided by this invention.

[0020] Please see Figure 1The diagram illustrates a flowchart of a method for automatically generating purchase forms for smart canteens according to an embodiment of the present invention. The method includes the following steps: Step S001: Obtain the number of orders for all dishes per day within the historical reference range, the amount of each raw material used in each dish, the current inventory of each raw material, and the storage time of each raw material.

[0021] It should be noted that traditional canteen purchasing forms often rely on manual summarization of order numbers, inventory reports, and experience-based forecasts. This results in long statistical cycles, information lag, leading to stockouts or excessive stockpiling. Furthermore, the highly manual nature of form creation makes it prone to errors and difficult to reuse. It also lacks automatic integration with backend inventory, budget, and supplier systems, leading to high management costs. Therefore, this embodiment presents an automatic purchasing form generation method for smart canteens. Specifically, it predicts the future raw material requirements for each dish based on the smart canteen's ordering system and historical order numbers, and combines this with current inventory and safety stock thresholds to automatically generate purchasing forms, achieving efficient operation and refined management of the smart canteen. To this end, it is first necessary to obtain the historical order numbers for each dish, predict the future order quantities for each dish, and combine this with the required quantities of various raw materials for each dish and the inventory levels of various raw materials to adaptively generate purchasing forms, thereby achieving "on-demand purchasing and scientific replenishment."

[0022] Specifically, a historical reference duration is preset. The The specific value can be set according to the actual situation. This embodiment does not make a hard requirement. In this embodiment, it is used as... Taking the recent as an example, let's describe it. Using one month as a historical reference range, obtain the number of orders for all dishes in the smart canteen every day within the historical reference range; Furthermore, obtain the quantity of each ingredient used in each dish, the current inventory of each ingredient, and the shelf life of each ingredient.

[0023] Step S002: Based on the daily order count of all dishes within the historical reference range, obtain the prevalence of each dish within the historical reference range. Combine this with the daily order count changes of different dishes within the historical reference range to obtain the substitutability between different dishes. Based on the daily order count of all dishes within the historical reference range, obtain the initial estimated order count of all dishes. Combine this with the substitutability between different dishes to obtain the initial estimated correction coefficient for each dish. Then, correct the initial estimated order count for each dish to obtain the estimated order count for each dish.

[0024] It should be noted that, since the raw materials for different dishes may overlap (i.e., one raw material may be used to make multiple dishes), and while the total number of orders in a canteen is usually stable daily, there is a certain degree of substitutability between different dishes, where orders for one dish may increase at the expense of another. Simply predicting the future order volume of a dish based solely on its historical order volume, without considering the overlap in raw materials used in different dishes and the substitutability between them, may result in the generated purchase order form failing to accurately reflect the consumption of various raw materials in the smart canteen. Therefore, this embodiment, as an automatic purchase order generation method for smart canteens, specifically analyzes the historical order volume of each dish to obtain the substitutability between different dishes, accurately predicts the expected future sales volume of each dish, and generates a purchase order form for the smart canteen based on this, achieving "on-demand purchasing and scientific replenishment."

[0025] Preferably, in a specific embodiment of the present invention, for the first [number] within the historical reference range The day, within the scope of historical reference. The absolute value of the difference between the total number of orders for all dishes on a given day and the average total number of orders for all dishes on all days within the historical reference range is inversely normalized. This inversely normalized result is then used as the [value] of the [number]th [item] within the historical reference range. The prevalence of the sky.

[0026] It should be noted that, under normal circumstances, the total number of orders in the cafeteria is stable each day. A significant difference between the total number of orders and the usual daily total indicates an unexpected situation, such as fluctuations due to holidays. To avoid the influence of these special circumstances when calculating the substitutability of dishes, we first examine the cafeteria's historical data within a certain reference range. The total number of orders for a day is used to assess the prevalence of each day within a historical reference range. When calculating the substitutability between different dishes by using the number of orders for each dish within the historical reference range, the prevalence of each day within the historical reference range is used as the weight, thereby accurately quantifying the substitutability between different dishes.

[0027] Furthermore, for the first [item] within the historical reference range The first day The dish will be the first The average number of orders for each dish per day within the historical reference range compared to the number of orders for the [number]th dish per day. This dish is the [number]th dish within the historical reference range. The difference between the number of orders per day is used as the first day within the historical reference range. The first day Sales trends of individual dishes; For the first in the historical reference range The first day The dish and the first The dish will be the first in the historical reference range. The first day The sales trend of individual dishes and the historical reference range The first day The product of the sales trends of each dish is used as the first... The dish and the first This dish is the [number]th dish within the historical reference range. The trend of coordinated change over the days will be the first The dish and the first This dish is the [number]th dish within the historical reference range. The trend of coordinated changes in the sky and the historical reference range The product of the universality of the days, as the first The dish and the first This dish is the [number]th dish within the historical reference range. The trend of synergistic change in the sky; The first The standard deviation of daily order volume for each dish within the historical reference range and the first The product of the daily order volume standard deviations for each dish within the historical reference range is used as the first... The dish and the first The degree of fluctuation in the number of orders for each dish within the historical reference range; The first The dish and the first The average daily revised co-variance trend of each dish within the historical reference range, compared to the previous day... The dish and the first The inverse of the ratio of the fluctuation in the number of orders for each dish within the historical reference range is used as the first... The dish and the first Substitutability between dishes.

[0028] In one example, obtain the first... The dish and the first The specific formula for calculating the substitutability between dishes is as follows: In the formula, Indicates the first The dish and the first Substitutability between dishes Indicates the first The dish and the first The average daily adjusted co-variance trend of each dish within the historical reference range; Indicates the first Standard deviation of daily order volume for each dish within the historical reference range; Indicates the first The standard deviation of the number of orders for each dish per day within the historical reference range.

[0029] It should be further explained that the existing Pearson correlation coefficient calculation formula is the product of the daily co-variance trend mean of two different dishes within the historical reference range and the standard deviation of the number of orders for the two dishes within the historical reference range. Since the total number of orders in the canteen is usually stable each day, a large difference between the total number of orders and the usual total indicates an unexpected situation. To avoid interference from unexpected situations when calculating the substitutability of different dishes, the correlation between different dishes is accurately quantified by using the prevalence of each day within the historical reference range as the daily weight. The stronger the negative correlation between different dishes, the stronger their substitutability. The stronger the substitutability, the more likely substitution is to occur between the dishes, and the more necessary it is to adjust the future order numbers for each dish to accurately obtain the expected order numbers for each dish.

[0030] Preferably, in a specific embodiment of the present invention, for the first For each dish, a preset prediction range is given. The The specific value can be set according to the actual situation. This embodiment does not make a hard requirement. In this embodiment, it is used as... Taking the example of the ARIMA algorithm, the first step is to describe the process. The number of orders for each dish per day within the historical reference range, predicting future... Heavenly The number of orders for each dish; since the ARIMA algorithm is a well-known existing technology, it will not be described in detail in this embodiment; [The remaining text appears to be incomplete and requires further context.] Heavenly The number of orders for each dish is denoted as the nth. Preliminary estimated order quantity for each dish; The first The average number of orders for each dish is expected to be within the forecast range, compared to the number of orders for the first dish. The difference between the average daily order volume for each dish within the historical reference range is used as the first... The projected sales change value for each dish will be the first The expected sales change of the first dish and the first The ratio of the average number of orders for each dish to the average number of orders per day within the historical reference range is used as the first... Projected sales growth rate for each dish; Similarly, obtain the projected sales growth rate for all dishes; Furthermore, regarding the first The dish and the first Each dish, as described (No. The dish and the first Each dish is a different dish), the first The dish and the first Substitutability between dishes and the first The product of the projected sales growth rate of each dish will be used as the first... The dish is for the first The expected sales adjustment factor for each dish will be applied to all dishes in relation to the first dish. The sum of the expected sales correction factors for each dish is mapped to a range of -1 to 1, and the mapping result of the sum is used as the first... The initial prediction correction factor for each dish.

[0031] In one example, obtain the first... The specific formula for calculating the initial prediction correction factor for each dish is as follows: In the formula, Indicates the first The initial estimated correction factor for each dish; Indicates the quantity of dishes; Indicates the first Projected sales growth rate for each dish; Indicates the first The dish and the first Substitutability between dishes; This refers to the `premnmx` function, which in this embodiment is used to... The calculation results are mapped to the range of -1 to 1.

[0032] It should be noted that the first The higher the projected sales growth rate of a dish, the better. The more a dish sells in the future, the better. The dish and the first The higher the substitutability between dishes, the better for the future... The more likely a dish is to be replaced by the first one. Each dish, therefore, requires more attention to the first... The initial order estimates for each dish were revised to accurately predict future orders. The number of orders for each dish; conversely, when the number of orders for the first dish is less than the number of orders for the second dish is less than the number of orders for the third dish, the order number of orders for the first dish is less than the number of orders for the third dish is less than the number of orders for the first dish. The estimated number of orders for each dish.

[0033] Preferably, in a specific embodiment of the present invention, for the first The dish, combining 1 and the first The difference in the initial predicted correction factor for each dish, multiplied by the first... The product of the initial projected order numbers for each dish is used as the basis for determining the order quantity for the first dish. The estimated number of orders for each dish.

[0034] It should be noted that the first The larger the initial prediction correction factor for a dish, the better for the future prediction of the [number]th dish. The more likely a dish is to be replaced by the first one. Each dish, that is, the future number The actual number of orders for a particular dish may be less, therefore The smaller the value, the more likely the future number will be... The fewer orders a dish may receive, the better.

[0035] At this point, the estimated order numbers for all dishes have been obtained.

[0036] Step S003: Based on the expected number of orders for each dish and the amount of each raw material used in each dish, obtain the baseline expected consumption of each raw material. Adjust the baseline expected consumption of each raw material according to the substitutability between different dishes to obtain the expected consumption of each raw material.

[0037] It should be noted that the raw materials used in different dishes in the canteen may overlap to some extent, and there is a certain degree of substitutability between different dishes. Therefore, if the purchase quantity of all raw materials is directly generated based on the expected order quantity of all dishes and the raw materials used in all dishes, structural redundancy of raw materials may occur due to fluctuations in dish demand. Therefore, this embodiment obtains the expected consumption of raw materials based on the expected order quantity of all dishes, combined with the substitutability between different dishes and the quantity of each raw material used in each dish.

[0038] Preferably, in a specific embodiment of the present invention, for any dish, the product of the expected number of orders for the dish and the amount of each raw material used in the dish is used as the initial expected consumption of each raw material for the dish. For the One type of raw material, consuming all the ingredients for the first dish The sum of the primary consumption of each type of raw material is used as the basis for determining the amount of the first type of raw material consumed. The baseline estimated consumption of the raw materials; Furthermore, regarding the first The dish and the first Each dish, as described (No. The dish and the first Each dish is a different dish), according to the first The dish uses the first The amount of the first raw material and the second The dish uses the first The absolute value of the difference between the quantities of the first and second raw materials is used as the first... The dish and the first The dish is in The difference in consumption of the first type of raw material will be the first The dish uses the first The amount of the first raw material and the second The dish uses the first The sum of the quantities of the various raw materials is used as the first... The dish and the first The consumption of each dish The total amount of each type of raw material; the first The dish and the first The dish is in The difference in consumption of one type of raw material and the first type The dish and the first The consumption of each dish The ratio of the total amount of each type of raw material is used as the first... The dish and the first The dish is in The degree of difference in the amount of raw materials used; According to the The baseline estimated consumption of each raw material, combined with the total consumption of all different dishes in the first... The degree of difference in the amount of raw materials used and the substitutability among all different dishes were used to obtain the first The estimated consumption of this raw material is calculated using the following formula: In the formula, Indicates the first The estimated consumption of these raw materials; Indicates the quantity of dishes; Indicates the first The baseline estimated consumption of the raw materials; Indicates the first The dish and the first Substitutability between dishes; Indicates the first The dish and the first The dish is in The degree of difference in the amount of raw materials used.

[0039] It should be noted that, This represents the consumption of all dishes on the first... The sum of the initial consumption of each type of raw material (including the possible overlap in raw materials used in different dishes, leading to the second...) The baseline estimated consumption of each raw material includes overlapping raw materials); when different dishes are in the first... When the difference in the amount of raw materials used is small, even if different dishes are substituted for each other, it will not affect the result. The consumption of each raw material has a significant impact. Furthermore, since the substitutability of different dishes varies, it is necessary to assign a calculation weight based on the substitutability of different dishes in order to accurately obtain the expected consumption of each raw material.

[0040] This gives us the estimated consumption of each raw material.

[0041] Step S004: Based on the storage time of each raw material, obtain the redundancy coefficient of each raw material, and combine it with the expected consumption of each raw material to obtain the purchase quantity of each raw material in the purchase order.

[0042] It should be noted that this embodiment is a method for automatically generating purchase forms for smart canteens. Specifically, it generates purchase forms based on the future consumption of each raw material and the current inventory of each raw material. Therefore, after obtaining the expected consumption of each raw material through step S003, it is also necessary to combine the current inventory of each raw material to obtain the purchase quantity of each raw material, thereby generating the purchase form for the smart canteen.

[0043] It should be further explained that, in order to avoid the occurrence of raw material shortages during the operation of the smart canteen, when obtaining the purchase quantity of each raw material, a redundancy quantity needs to be set for each raw material to ensure that the amount of raw materials in the inventory is always maintained above the safe quantity. Also, since the shelf life of different raw materials varies, in order to avoid the stored raw materials from expiring, the purchase quantity of each raw material also needs to be adjusted according to the shelf life of the raw materials.

[0044] Preferably, in a specific embodiment of the present invention, a primary redundancy coefficient is preset. The specific value of the primary redundancy coefficient can be set according to the actual situation. This embodiment does not make a rigid requirement. In this embodiment, the primary redundancy coefficient is 0.3 as an example. The first type of raw material, for the first The shelf life of each raw material is linearly normalized, specifically within the range of shelf life for all raw materials; the shelf life of the first raw material is then linearly normalized. The product of the linearly normalized result of the shelf life of the first raw material and the primary redundancy coefficient is used as the product of the second raw material's shelf life. Redundancy coefficient of raw materials; According to the The redundancy coefficient of the first type of raw material, combined with the first... The projected consumption of the first type of raw material and the current inventory of the first type. The inventory of each type of raw material, and the information in the purchase order. The specific formula for calculating the purchase quantity of each type of raw material is as follows: In the formula, Indicates the first item in the purchase form The amount of raw materials purchased; Indicates the first Redundancy coefficient of raw materials; Indicates the first The estimated consumption of these raw materials; Indicates the number of items in the current inventory. The stock of various raw materials.

[0045] It should be noted that the first The smaller the redundancy coefficient of a raw material, the better. The shorter the time frame for purchasing raw materials, the more likely they are to expire. To avoid this, during the procurement process... When purchasing raw materials, one should not buy too much of the first type. This embodiment analyzes the substitutability of various dishes in a smart canteen and the differences in raw materials for different dishes to accurately obtain the consumption of various raw materials. This information is then used to generate a procurement form for the smart canteen. This not only effectively avoids waste and stockouts of raw materials in the smart canteen, but also improves procurement efficiency, ensures stable meal supply, and reduces the risk of misjudgments due to human intervention. Furthermore, it promotes inventory turnover, reduces spoilage, and provides accurate data support for financial control and operational decisions, ultimately achieving "on-demand procurement and scientific replenishment."

[0046] Another embodiment of the present invention provides an automatic procurement form generation system for smart canteens, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the automatic procurement form generation method for smart canteens in steps S001 to S004.

[0047] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for automatically generating purchase forms for smart canteens, characterized in that, The method includes the following steps: Get the number of orders for all dishes every day within the historical reference range, the amount of each ingredient used in each dish, the current inventory of each ingredient, and the shelf life of each ingredient; Based on the daily order count of all dishes within the historical reference range, we obtain the prevalence of each dish within that range. Combining this with the daily order count changes for different dishes within the historical reference range, we obtain the substitutability between them. Based on the daily order count of all dishes within the historical reference range, we obtain the initial projected order count for all dishes. Combining this with the substitutability between different dishes, we obtain the initial projected correction coefficient for each dish, and then correct the initial projected order count for each dish to obtain the projected order count for each dish. Based on the expected number of orders for each dish and the amount of each raw material used in each dish, the baseline expected consumption of each raw material is obtained. The baseline expected consumption of each raw material is then adjusted according to the substitutability between different dishes to obtain the expected consumption of each raw material. Based on the storage time of each raw material, obtain the redundancy coefficient of each raw material, and combine it with the expected consumption of each raw material to obtain the purchase quantity of each raw material in the purchase order.

2. The method for automatically generating purchase forms for smart canteens according to claim 1, characterized in that, The method for obtaining the prevalence of each day within the historical reference range based on the number of orders for all dishes each day includes: For the first within the historical reference range The day, within the scope of historical reference. The absolute value of the difference between the total number of orders for all dishes on a given day and the average total number of orders for all dishes on all days within the historical reference range is inversely normalized. This inversely normalized result is then used as the [value] of the [number]th [item] within the historical reference range. The prevalence of the sky.

3. The method for automatically generating purchase forms for smart canteens according to claim 1, characterized in that, The specific methods for obtaining the substitutability between different dishes are as follows: For the first in the historical reference range The first day The dish will be the first The average number of orders for each dish per day within the historical reference range compared to the number of orders for the [number]th dish per day. This dish is the [number]th dish within the historical reference range. The difference between the number of orders per day is used as the first day within the historical reference range. The first day Sales trends of individual dishes; For the first in the historical reference range The first day The dish and the first The dish will be the first in the historical reference range. The first day The sales trend of individual dishes and the historical reference range The first day The product of the sales trends of each dish is used as the first... The dish and the first This dish is the [number]th dish within the historical reference range. The trend of coordinated change over the days will be the first The dish and the first This dish is the [number]th dish within the historical reference range. The trend of coordinated changes in the sky and the historical reference range The product of the universality of the days, as the first The dish and the first This dish is the [number]th dish within the historical reference range. The trend of synergistic change in the sky; The first The standard deviation of daily order volume for each dish within the historical reference range and the first The product of the daily order volume standard deviations for each dish within the historical reference range is used as the first... The dish and the first The degree of fluctuation in the number of orders for each dish within the historical reference range; The first The dish and the first The average daily revised co-variance trend of each dish within the historical reference range, compared to the previous day... The dish and the first The inverse of the ratio of the fluctuation in the number of orders for each dish within the historical reference range is used as the first... The dish and the first Substitutability between dishes.

4. The method for automatically generating purchase forms for smart canteens according to claim 1, characterized in that, The method for obtaining the initial estimated order number for all dishes based on the daily order number within the historical reference range includes: For the For each dish, a preset prediction range is given. ; Based on the ARIMA algorithm, through the first The number of orders for each dish per day within the historical reference range, predicting future... Heavenly The number of orders for each dish; in the future Heavenly The number of orders for each dish is denoted as the nth. Preliminary estimated order volume for each dish.

5. The method for automatically generating purchase forms for smart canteens according to claim 1, characterized in that, The specific method for obtaining the initial predicted correction coefficient for each dish is as follows: For the The dish will be the first The average number of orders for each dish is expected to be within the forecast range, compared to the number of orders for the first dish. The difference between the average daily order volume for each dish within the historical reference range is used as the first... The projected sales change value for each dish will be the first The expected sales change of the first dish and the first The ratio of the average number of orders for each dish to the average number of orders per day within the historical reference range is used as the first... Projected sales growth rate for each dish; Obtain the projected sales growth rate for all dishes; For the The dish and the first Each dish, as described , No. The dish and the first Substitutability between dishes and the first The product of the projected sales growth rate of each dish will be used as the first... The dish is for the first The expected sales adjustment factor for each dish will be applied to all dishes in relation to the first dish. The sum of the expected sales correction factors for each dish is mapped to a range of -1 to 1, and the mapping result of the sum is used as the first... The initial prediction correction factor for each dish.

6. The method for automatically generating purchase forms for smart canteens according to claim 1, characterized in that, The specific methods for obtaining the estimated order quantity for each dish are as follows: For the The dish, combining 1 and the first The difference in the initial predicted correction factor for each dish, multiplied by the first... The product of the initial projected order numbers for each dish is used as the basis for determining the order quantity for the first dish. The estimated number of orders for each dish.

7. The method for automatically generating purchase forms for smart canteens according to claim 1, characterized in that, The method for obtaining the baseline estimated consumption of each raw material by calculating the expected order quantity for each dish and the quantity of each raw material used in each dish, and then adjusting the baseline estimated consumption of each raw material based on the substitutability between different dishes, includes the following specific methods: For any dish, the product of the expected number of orders for the dish and the quantity of each raw material used in the dish is used as the initial expected consumption of each raw material for the dish. For the One type of raw material, consuming all the ingredients for the first dish The sum of the primary consumption of each type of raw material is used as the basis for determining the amount of the first type of raw material consumed. The baseline estimated consumption of the raw materials; For the The dish and the first The dish, according to the first The dish uses the first The amount of the first raw material and the second The dish uses the first The absolute value of the difference between the quantities of the first and second raw materials is used as the first... The dish and the first The dish is in The difference in consumption of the first type of raw material will be the first The dish uses the first The amount of the first raw material and the second The dish uses the first The sum of the quantities of the various raw materials is used as the first... The dish and the first The consumption of each dish The total amount of various raw materials; The first The dish and the first The dish is in The difference in consumption of one type of raw material and the first type The dish and the first The consumption of each dish The ratio of the total amount of each type of raw material is used as the first... The dish and the first The dish is in The degree of difference in the amount of raw materials used; According to the The baseline estimated consumption of each raw material, combined with the total consumption of all different dishes in the first... The degree of difference in the amount of raw materials used and the substitutability among all different dishes were used to obtain the first The estimated consumption of these raw materials.

8. The method for automatically generating purchase forms for smart canteens according to claim 7, characterized in that, The acquisition of the first The estimated consumption of these raw materials, including the specific methods, is as follows: In the formula, Indicates the first The estimated consumption of these raw materials; Indicates the quantity of dishes; Indicates the first The baseline estimated consumption of the raw materials; Indicates the first The dish and the first Substitutability between dishes; Indicates the first The dish and the first The dish is in The degree of difference in the amount of raw materials used.

9. The method for automatically generating purchase forms for smart canteens according to claim 1, characterized in that, The specific method for obtaining the redundancy coefficient of each raw material based on its shelf life, and then combining this with the expected consumption of each raw material to determine the purchase quantity of each raw material in the purchase order, includes the following: A primary redundancy coefficient is preset, for the first... The first type of raw material, for the first The shelf life of each raw material is linearly normalized, specifically within the range of shelf life for all raw materials; the shelf life of the first raw material is then linearly normalized. The product of the linearly normalized result of the shelf life of the first raw material and the primary redundancy coefficient is used as the product of the second raw material's shelf life. Redundancy coefficient of raw materials; The first item in the procurement form The specific methods for determining the purchase quantity of various raw materials are as follows: In the formula, Indicates the first item in the purchase form The amount of raw materials purchased; Indicates the first Redundancy coefficient of raw materials; Indicates the first The estimated consumption of these raw materials; Indicates the number of items in the current inventory. The stock of various raw materials.

10. An automatic procurement form generation system for smart canteens, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the computer program is executed by the processor, it implements the steps of the automatic generation method for purchasing forms for smart canteens as described in any one of claims 1-9.

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