Method and device for determining a recipe of a milk fat-based product based on a mathematical programming method

Abstract

The application discloses a kind of based on mathematical programming method's milk fat product formula determination method and device, wherein the method includes: obtaining the preset constraint condition of milk fat product formula;With production demand as target, with the kind of raw material to be selected, the amount of raw material to be selected as decision variable, establish objective function;Under the preset constraint condition, the objective function is solved, and a group of decision variables that meet production demand is obtained, and the group of decision variables is used as milk fat product formula.The application can efficiently design milk fat product formula, and the designed formula meets the requirements of production efficiency and cost benefit while meeting the requirements of nutrient content, reduces the dependence of formula design on the experience of practitioners.

Description

Technical Field

[0001] This invention relates to the field of formulation design technology, and in particular to a method and apparatus for determining the formulation of dairy fat products based on mathematical programming. Background Technology

[0002] This section is intended to provide background or context for the embodiments of the invention set forth in the claims. The description herein is not an admission that it is prior art simply because it is included in this section.

[0003] With the rapid development of the dairy industry, the demand for new dairy product research and development is also increasing. A key aspect of new dairy product development is designing product formulations according to the protein, fat, carbohydrate, and sodium content listed on nutrition labels. Because the types of raw materials are diverse, and each raw material can provide a certain amount of protein, fat, carbohydrates, or sodium, there are a wide variety of product formulations that can meet the core nutrient content requirements listed on nutrition labels.

[0004] Currently, the design of dairy fat product formulations mainly relies on enumeration, manually calculating nutrient content, and trial and error to determine the final formulation. This method is inefficient and highly dependent on the experience of practitioners. Therefore, improving the efficiency of product formulation design has become a major challenge for food researchers. Summary of the Invention

[0005] This invention provides a method for determining the formulation of dairy fat products based on mathematical programming. This method efficiently designs dairy fat product formulations that meet nutrient content requirements while also satisfying production efficiency and cost-effectiveness requirements. It also reduces the reliance on the experience of practitioners in formulation design. The method includes:

[0006] Obtain the preset constraints of the dairy fat product formula; the preset constraints include: a first constraint, a second constraint, a third constraint, and a fourth constraint; the first constraint includes the nutrient content requirements in the dairy fat product, the second constraint includes the restrictions on the amount of raw materials used by the dairy fat product production process equipment, the third constraint includes food safety standards, and the fourth constraint includes the restrictions on the amount of raw materials used by the time required for the dairy fat product production process.

[0007] With production demand as the objective and the types and quantities of raw materials to be selected as decision variables, an objective function is established. The production demand includes: minimizing product cost, minimizing production time, minimizing energy consumption of production equipment, and minimizing the difficulty in obtaining production raw materials.

[0008] The objective function is solved under preset constraints to obtain a set of decision variables that meet production requirements. This set of decision variables is then used as the formula for dairy fat products.

[0009] This invention also provides a device for determining the formulation of dairy fat products based on mathematical programming, which is used to efficiently design dairy fat product formulations. The designed formulations meet the requirements for nutrient content while also meeting the requirements for production efficiency and cost-effectiveness, reducing the dependence of formulation design on the experience of practitioners. The device includes:

[0010] The constraint module is used to obtain the preset constraints for the design of dairy fat product formulations. The preset constraints include: a first constraint, a second constraint, a third constraint, and a fourth constraint. The first constraint includes the nutrient content requirements in dairy fat products; the second constraint includes the restrictions on the amount of raw materials used by the dairy fat product production process equipment; the third constraint includes food safety standards; and the fourth constraint includes the restrictions on the amount of raw materials used based on the time required for the dairy fat product production process.

[0011] The objective function module is used to establish an objective function with production demand as the objective and the types and quantities of raw materials to be selected as decision variables. The production demand includes: minimizing product cost, minimizing production time, minimizing energy consumption of production equipment, and minimizing the difficulty in obtaining production raw materials.

[0012] The formula solving module is used to solve the objective function under preset constraints to obtain a set of decision variables that meet production requirements. This set of decision variables is then used as the formula for dairy fat products.

[0013] This invention also provides a computer device, 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 above-described method for determining the formulation of dairy fat products based on mathematical programming.

[0014] This invention also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method for determining the formulation of dairy fat products based on mathematical programming.

[0015] This invention also provides a computer program product, which includes a computer program that, when executed by a processor, implements the above-described method for determining the formulation of dairy fat products based on mathematical programming.

[0016] Compared to existing technologies that rely on enumeration to manually calculate nutrient content and trial-and-error to determine the formulation of dairy fat products, this invention uses mathematical modeling to address the actual problem of dairy fat product formulation design in R&D. It incorporates constraints such as nutrient content requirements on the product's nutrition label, limitations on raw material usage by the production equipment, food safety standards, and the time required for production. An objective function is established with production needs as the target, and the objective function is solved under these constraints to obtain a dairy fat product formulation that meets production requirements. This approach enables efficient formulation design, ensuring that the designed formulation meets nutrient content requirements while also achieving high production efficiency and cost-effectiveness, thus reducing the reliance on the experience of practitioners in formulation design. Attached Figure Description

[0017] 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. In the drawings:

[0018] Figure 1 This is a flowchart illustrating a method for determining the formulation of dairy fat products based on mathematical programming, as described in an embodiment of the present invention.

[0019] Figure 2 This is an example diagram illustrating the difficulty in obtaining monomeric oils in embodiments of the present invention;

[0020] Figure 3 This is an example diagram illustrating the solution for minimizing the difficulty in obtaining raw materials in an embodiment of the present invention;

[0021] Figure 4 This is an example diagram illustrating the difficulty in obtaining the compound oil before optimization in this embodiment of the invention;

[0022] Figure 5 This is an example diagram illustrating the difficulty in obtaining the optimized compound oil in this embodiment of the invention;

[0023] Figure 6 This is an example diagram illustrating the requirements for the moisture, fat, and non-fat milk solids content in butter in an embodiment of the present invention;

[0024] Figure 7 This is a histogram of the fat content of frozen whipped cream in an embodiment of the present invention;

[0025] Figure 8 This is a probability diagram of the fat content of frozen whipped cream in an embodiment of the present invention;

[0026] Figure 9This is a normal distribution diagram of the fat content of frozen whipped cream in an embodiment of the present invention;

[0027] Figure 10 This is an example diagram showing the initial values ​​of the decision variables for the butter recipe design in an embodiment of the present invention;

[0028] Figure 11 This is an example diagram showing the results of solving the butter formula in an embodiment of the present invention;

[0029] Figure 12 This is a schematic diagram of a device for determining the formulation of dairy fat products based on mathematical programming in an embodiment of the present invention. Detailed Implementation

[0030] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the embodiments of the present invention will be further described in detail below with reference to the accompanying drawings. Here, the illustrative embodiments of the present invention and their descriptions are used to explain the present invention, but are not intended to limit the present invention.

[0031] Current methods for designing dairy fat product formulations primarily rely on enumeration, manually calculating nutrient content, and trial-and-error to determine the formulation. This approach is inefficient and highly dependent on the experience of practitioners. To improve the efficiency of dairy fat product formulation design, this invention proposes a method for determining dairy fat product formulations based on mathematical programming. Figure 1 This is a flowchart illustrating a method for determining the formulation of dairy fat products based on mathematical programming, as described in an embodiment of the present invention. Figure 1 As shown, the method includes the following steps:

[0032] Step 101: Obtain the preset constraints of the dairy fat product formula; the preset constraints include: a first constraint, a second constraint, a third constraint, and a fourth constraint; the first constraint includes the nutrient content requirements in the dairy fat product; the second constraint includes the restrictions on the amount of raw materials used by the dairy fat product production process equipment; the third constraint includes food safety standards; and the fourth constraint includes the restrictions on the amount of raw materials used based on the time required for the dairy fat product production process.

[0033] Step 102: With production demand as the objective and the types and quantities of raw materials to be selected as decision variables, establish an objective function. The production demand includes: minimizing product cost, minimizing production time, minimizing energy consumption of production equipment, and minimizing the difficulty in obtaining production raw materials.

[0034] Step 103: Solve the objective function under preset constraints to obtain a set of decision variables that meet production requirements, and use this set of decision variables as the formula for dairy fat products.

[0035] The inventors discovered that the design of dairy fat product formulations requires consideration of multiple factors, including but not limited to nutrient requirements, production costs, and flavor requirements. The following problems are frequently encountered in dairy fat product formulation design: how to determine a reasonable utilization scheme to maximize output and profit under limited production resources; how to select raw materials to minimize product costs; and how to minimize raw material waste while completing production tasks. This invention transforms these problems into mathematical programming problems, treating them as constrained extremum problems in mathematics. It uses mathematical language to transform the limitations of limited production resources, the influencing factors of raw material selection, and the utilization rate of raw materials into constraints.

[0036] In this embodiment of the invention, preset constraints are obtained for the formulation of dairy fat products. The preset constraints include: a first constraint, a second constraint, a third constraint, and a fourth constraint. The first constraint includes the nutrient content requirements in dairy fat products. The second constraint includes the limitation on the amount of raw materials used by the production process equipment for dairy fat products. The third constraint includes food safety standards. The fourth constraint includes the limitation on the amount of raw materials used by the time required for the production process of dairy fat products.

[0037] For example, the fat content of a certain whipping cream product should be greater than 34.5% and less than 36.2%. Since the fat content of this whipping cream should be the sum of the fat content of all the ingredients in the formula, the constraints can be obtained as shown in formulas (1) and (2):

[0038]

[0039]

[0040] In the formula, M i It is the amount of the i-th ingredient added in the formula, Fat i is the fat content of the i-th ingredient, and n is the number of ingredients added to the formula.

[0041] In one embodiment, the second constraint includes: the maximum volume of the material tank and the minimum volume required for the material tank to operate normally, which restricts the amount of raw materials used.

[0042] Trial production is a necessary step before mass production. To conserve resources, trial production is usually not carried out at full capacity, but rather at the minimum capacity level that meets the production line requirements. For example, the limitations on raw material usage in the production process of dairy products can be translated into mathematical language, as shown in formulas (3) and (4):

[0043]

[0044]

[0045] In the formula, m i M represents the mass of the i-th type of raw material added to a material tank, where n is the total number of types of raw materials to be added. max This is the maximum volume of the material tank, M. min This is the minimum volume required for the material tank to reach normal production.

[0046] To reduce energy consumption in production equipment, the production time of dairy fat products needs to be rationally planned. Therefore, in one embodiment, the fourth constraint includes: the limitation on the amount of raw materials used due to continuous sterilization of multiple material tanks, which needs to satisfy the inequality, as shown in formula (5):

[0047]

[0048] Among them, M tank C represents the mass of raw materials in each container to be filled. UHT T represents the production capacity of ultra-high temperature instantaneous sterilization technology. blending This represents the mixing time for each can of material.

[0049] In this embodiment of the invention, with production demand as the objective and the types and quantities of raw materials to be selected as decision variables, an objective function is established. The production demand includes: minimizing product cost, minimizing production time, minimizing energy consumption of production equipment, and minimizing the difficulty in obtaining production raw materials.

[0050] In this embodiment of the invention, the objective function is solved under preset constraints to obtain a set of decision variables that meet production requirements, and this set of decision variables is used as the formula for dairy fat products.

[0051] For example, there are mandatory regulations regarding the amounts of fat, linoleic acid, and alpha-linolenic acid in infant formula, as well as the ratio of linoleic acid to alpha-linolenic acid. Selecting the appropriate proportions from a wide variety of edible oils and blending them into oil products that comply with these mandatory regulations is crucial. The availability of raw materials is affected by many factors, such as supply chain production data, transportation data, and the number of suppliers.

[0052] In one embodiment, the difficulty in obtaining raw materials is determined by supply chain production data, transportation data, and the number of suppliers for the raw materials.

[0053] For example, surveys have revealed a significant decline in sunflower oil production in recent years; transportation time and costs from major production areas to consumer markets are constantly increasing; and the number of qualified suppliers of sunflower oil is limited. All of these factors contribute to the increased difficulty in obtaining sunflower oil.

[0054] Figure 2This is an example diagram illustrating the difficulty in obtaining individual oils in an embodiment of the present invention. In this embodiment, seven oils are available: coconut oil, soybean oil, corn oil, sunflower oil, high-oleic sunflower oil, high-oleic rapeseed oil, and palm oil. Based on factors such as supply chain production data, transportation data, and the number of suppliers for these oils, the difficulty in obtaining each individual oil is determined, and the results are as follows: Figure 2 As shown.

[0055] With the goal of minimizing the difficulty in obtaining oil products, the objective function is set as shown in formula (6):

[0056]

[0057] In the formula: a i The difficulty in obtaining monomeric oils, x i It refers to the proportion of monomeric oil in the compound oil.

[0058] Based on the nutritional requirements of infant formula, the following constraints are set:

[0059]

[0060]

[0061]

[0062]

[0063]

[0064]

[0065]

[0066]

[0067] In the above formula, LOC i It is the linoleic acid content of the i-th monomer oil, LONC i It is the linolenic acid content of the i-th monomer oil, TransOil i It is the trans fatty acid content of the i-th monomer oil, C12 i It is the lauric acid content of the i-th monomer oil, C14 i It is the myristic acid content of the i-th monomer oil, C22 i It is the erucic acid content of the i-th monomer oil.

[0068] The objective function is solved under the above constraints. Figure 3 This is an example diagram illustrating the solution for minimizing the difficulty in obtaining raw materials in an embodiment of the present invention. For example... Figure 3As shown, firstly, a raw material table is designed, and the initial proportion is entered in the column of single oil proportion according to experience; then, constraints and objective functions are set to solve the formula of infant formula compound oil with the lowest oil availability; the solved infant formula compound oil formula is automatically filled into the column of single oil proportion; finally, the results are verified to see if they meet various constraints.

[0069] Figure 4 This is an example diagram illustrating the difficulty in obtaining the compound oil before optimization in an embodiment of the present invention. Figure 5 This is an example diagram illustrating the difficulty in obtaining the optimized compound oil in this embodiment of the invention. (Comparison) Figure 4 and Figure 5 It can be seen that in the compound oil formula that incorporates the factor of the difficulty in obtaining single oil products, sunflower seed oil is no longer included. The difficulty in obtaining compound oil has been reduced from 13.43 to 10.97, and the optimized compound oil formula also meets the requirements for nutrient content.

[0070] In one embodiment, the dairy product formulation includes a butter formulation. For example, Figure 6 This is an example diagram illustrating the requirements for water, fat, and non-fat milk solids content in butter according to embodiments of the present invention. Figure 6 As shown, the butter recipe includes three main ingredients: light cream, butter, and anhydrous milk fat (AMF), and the physicochemical properties of these three main ingredients are displayed.

[0071] In one embodiment, the preset constraints may further include: the range of nutrient content values ​​for the candidate raw materials; the range of values ​​is determined as follows: the nutrient content of the candidate raw materials is analyzed using mathematical statistics methods to obtain statistical indicators of the nutrient content of the candidate raw materials; the statistical indicators include: mean, variance, standard deviation, etc.; based on the statistical indicators of the nutrient content of the candidate raw materials, a normality test is performed on the nutrient content of the candidate raw materials to obtain the range of nutrient content values ​​for the candidate raw materials.

[0072] For ingredients like whipping cream, frozen whipping cream is typically used in production, and the fat content of frozen whipping cream fluctuates within a certain normal range. This invention employs mathematical statistics to analyze the fluctuation of fat content in frozen whipping cream as a raw material, in order to determine the fat content to be input into the objective function.

[0073] For example, 255 batches of frozen cream samples were collected, and their fat content was analyzed using mathematical statistics methods to obtain statistical indicators such as mean, variance, and standard deviation, and a normality test was performed. Figure 7 This is a histogram of the fat content of frozen whipped cream in an embodiment of the present invention. Figure 8 This is a probability diagram of the fat content of frozen whipped cream in an embodiment of the present invention. Figure 7 and Figure 8 As shown: the mean fat content of the frozen whipped cream is μ = 42.25%, and the standard deviation is σ = 0.7561%. The p-value is a parameter for hypothesis testing, and the significance level is set to α = 0.05. Since p = 0.066 > 0.05, it indicates that the fat content of the 255 samples follows a normal distribution with a mean of 42.25% and a standard deviation of 0.756%, i.e., N(42.25%, 0.756%). For the fat content of the frozen whipped cream in this embodiment, according to the three-standard-deviation method, its reasonable range is determined to be [μ-3σ, μ+3σ]. Figure 9 This is a normal distribution diagram of the fat content of frozen whipped cream in an embodiment of the present invention. Figure 9 As shown, according to the normal distribution, the probability of a frozen whipping cream product with a fat content less than μ-3σ=42.25%-3·0.756%=39.982% is no greater than 0.15%, which is consistent with the expectation for such products. Therefore, 39.982% is determined as the fat content of the frozen whipping cream in this embodiment.

[0074] In one embodiment, the preset constraints further include: the amount of fermented butter added is 0.4%, and the fat content of the final butter product is not less than 83.5% and not more than 86%.

[0075] Based on extensive practical experience, the amount of fermented light cream, which has a significant impact on flavor, was fixed at 0.4% as a constraint in the setting of conditions. Simultaneously, a statistical analysis of competing products was conducted, and based on the analysis results, the fat content of the butter products was fixed within the range of [83.5%, 86%]. Combined with... Figure 6 The nutrient requirements are set with the following constraints:

[0076]

[0077]

[0078]

[0079]

[0080] y4=0.4 (19)

[0081]

[0082] In the formula, y j It is the proportion of ingredient j in the butter recipe. j It is the fat content of the j-th raw material, Water j It is the water content of the j-th raw material, Acidity jy is the non-fat milk solids content of the j-th ingredient; where y4 is the proportion of fermented cream added to the butter recipe.

[0083] In this embodiment, in order to reduce the production cost of butter while meeting the nutrient requirements in the nutrition label, the objective is to minimize the product cost. Anhydrous butter, frozen cream, fermented cream, and water are the four raw materials used as decision variables, and an objective function is established as shown in formula (21):

[0084]

[0085] In the formula, b j It is the unit price of the j-th raw material.

[0086] Figure 10 This is an example diagram illustrating the initial values ​​of decision variables for the butter recipe design in this embodiment of the invention. Similar to the solution method in the previous embodiment, this embodiment designs an ingredient table and arbitrarily sets the initial values ​​for the proportions of various ingredients added, such as... Figure 10 As shown. Figure 11 This is an example diagram showing the result of solving the butter recipe in an embodiment of the present invention. Constraints and objective functions were set according to formulas (15)-(21), and then the butter recipe was solved. Although the initial ingredient ratios were problematic (e.g., the sum of the ingredient ratios was greater than 100%), the optimized ingredient ratios satisfied all constraints, such as... Figure 11 As shown, the butter recipe consists of: 78.95% anhydrous butter, 15.43% light cream, 0.4% fermented light cream, and 5.22% water. The nutrient content of the final butter recipe is shown in Table 1.

[0087] Table 1: Nutrient Content of Butter Recipes

[0088]

[0089]

[0090] The moisture content was 13% < 16%, the fat content was 83.5% < 86%, and the non-fat milk solids content was 1.7% < 2%, meeting the requirements for moisture, fat, and non-fat milk solids content in butter. Furthermore, the cost of producing butter using the obtained formula was reduced from 37,038.3 yuan / ton to 36,112 yuan / ton.

[0091] This invention also provides a device for determining the formulation of dairy fat products based on mathematical programming, as described in the following embodiments. Since the principle behind this device's problem-solving is similar to the method for determining the formulation of dairy fat products based on mathematical programming, the implementation of this device can refer to the implementation of the method for determining the formulation of dairy fat products based on mathematical programming; repeated details will not be elaborated further.

[0092] Figure 12 This is a schematic diagram of a device for determining the formulation of dairy fat products based on mathematical programming, as described in an embodiment of the present invention. Figure 12 As shown, the device includes:

[0093] The constraint module 1201 is used to obtain preset constraints for the design of dairy fat product formulations. The preset constraints include: a first constraint, a second constraint, a third constraint, and a fourth constraint. The first constraint includes the nutrient content requirements in dairy fat products; the second constraint includes the restrictions on the amount of raw materials used by the dairy fat product production process equipment; the third constraint includes food safety standards; and the fourth constraint includes the restrictions on the amount of raw materials used by the time required for the dairy fat product production process.

[0094] The objective function module 1202 is used to establish an objective function with production demand as the objective and the types and quantities of raw materials to be selected as decision variables. The production demand includes: minimizing product cost, minimizing production time, minimizing energy consumption of production equipment, and minimizing the difficulty in obtaining production raw materials.

[0095] The formula solving module 1203 is used to solve the objective function under preset constraints to obtain a set of decision variables that meet production requirements, and use this set of decision variables as the formula for dairy fat products.

[0096] In one embodiment, the second constraint includes: the maximum volume of the material tank and the minimum volume required for the material tank to operate normally, which restricts the amount of raw materials used.

[0097] In one embodiment, the fourth constraint includes: the limitation on the amount of raw materials used due to continuous sterilization of multiple material tanks, which needs to satisfy the following inequality:

[0098]

[0099] Among them, M tank C represents the mass of material in each container to be filled. UHT T represents the production capacity of ultra-high temperature instantaneous sterilization technology. blending This represents the mixing time for each can of material.

[0100] In one embodiment, the preset constraints further include: the range of nutrient content values ​​for the raw materials to be selected;

[0101] The range of values ​​is determined as follows:

[0102] The nutrient content of the candidate raw materials was analyzed using mathematical statistics methods to obtain statistical indicators of the nutrient content of the candidate raw materials; the statistical indicators included: mean, variance, and standard deviation.

[0103] Based on the statistical indicators of the nutrient content of the candidate raw materials, a normality test was performed on the nutrient content of the candidate raw materials to obtain the range of values ​​for the nutrient content of the candidate raw materials.

[0104] In one embodiment, the difficulty in obtaining raw materials is determined by supply chain production data, transportation data, and the number of suppliers for the raw materials.

[0105] In one embodiment, the dairy product formulation includes a butter formulation; the preset constraints also include: the amount of fermented butter added is 0.4%, and the fat content of the final butter product is not less than 83.5% and not more than 86%.

[0106] This invention also provides a computer device, 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 above-described method for determining the formulation of dairy fat products based on mathematical programming.

[0107] This invention also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method for determining the formulation of dairy fat products based on mathematical programming.

[0108] This invention also provides a computer program product, which includes a computer program that, when executed by a processor, implements the above-described method for determining the formulation of dairy fat products based on mathematical programming.

[0109] In this embodiment of the invention, preset constraints are obtained for the formulation of dairy fat products. These preset constraints include: a first constraint, a second constraint, a third constraint, and a fourth constraint. The first constraint includes the nutrient content requirements of the dairy fat products; the second constraint includes the limitations on the amount of raw materials used by the dairy fat product production process equipment; the third constraint includes food safety standards; and the fourth constraint includes the limitations on the amount of raw materials used by the time required for the dairy fat product production process. With production needs as the objective and the types and amounts of candidate raw materials as decision variables, an objective function is established. The production needs include: minimum product cost, shortest production time, lowest energy consumption of the production process equipment, and lowest difficulty in obtaining production raw materials. The objective function is solved under the preset constraints to obtain a set of decision variables that meet the production needs. This set of decision variables is then used as the formulation of the dairy fat products. Compared to existing technologies that rely on enumeration to manually calculate nutrient content and trial-and-error to determine the formulation of dairy fat products, this invention uses mathematical modeling to address the actual problem of dairy fat product formulation design in R&D. It incorporates constraints such as nutrient content requirements on the product's nutrition label, limitations on raw material usage by the production equipment, food safety standards, and the time required for production. An objective function is established with production needs as the target, and the objective function is solved under these constraints to obtain a dairy fat product formulation that meets production requirements. This approach enables efficient formulation design, ensuring that the designed formulation meets nutrient content requirements while also achieving high production efficiency and cost-effectiveness, thus reducing the reliance on the experience of practitioners in formulation design.

[0110] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0111] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0112] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0113] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0114] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above descriptions are merely specific embodiments of the present invention and are not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for determining the formulation of dairy fat products based on mathematical programming, characterized in that, include: Obtain the preset constraints for the formulation of dairy fat products; The preset constraints include: a first constraint, a second constraint, a third constraint, and a fourth constraint; the first constraint includes the nutrient content requirements in dairy fat products; the second constraint includes the restrictions on the amount of raw materials used by the production process equipment for dairy fat products; the third constraint includes food safety standards; and the fourth constraint includes the restrictions on the amount of raw materials used due to the time required for the production process of dairy fat products. With production demand as the objective and the types and quantities of raw materials to be selected as decision variables, an objective function is established. The production demand includes: minimizing product cost, minimizing production time, minimizing energy consumption of production equipment, and minimizing the difficulty in obtaining production raw materials. The objective function is solved under preset constraints to obtain a set of decision variables that meet production requirements. This set of decision variables is then used as the formula for dairy fat products.

2. The method as described in claim 1, characterized in that, The second constraint includes the limitation on the amount of raw materials used by the maximum volume of the material tank and the minimum volume required for normal production of the material tank.

3. The method as described in claim 1, characterized in that, The fourth constraint includes the limitation on the amount of raw materials used due to continuous sterilization of multiple material tanks, which needs to satisfy the following inequality: Among them, M tank C represents the mass of material in each container to be filled. UHT T represents the production capacity of ultra-high temperature instantaneous sterilization technology. blending This represents the mixing time for each can of material.

4. The method as described in claim 1, characterized in that, The preset constraints also include: the range of nutrient content values ​​for the raw materials to be selected; The range of values ​​is determined as follows: The nutrient content of the candidate raw materials was analyzed using mathematical statistics methods to obtain statistical indicators of the nutrient content of the candidate raw materials; the statistical indicators included: mean, variance, and standard deviation. Based on the statistical indicators of the nutrient content of the candidate raw materials, a normality test was performed on the nutrient content of the candidate raw materials to obtain the range of values ​​for the nutrient content of the candidate raw materials.

5. The method as described in claim 1, characterized in that, The difficulty in obtaining raw materials is determined by the production output data, transportation data, and number of suppliers in the raw material supply chain.

6. The method as described in claim 1, characterized in that, The formula for dairy fat products includes: a butter formula; the preset constraints also include: the amount of fermented butter added is 0.4%, and the fat content of the final butter product is not less than 83.5% and not more than 86%.

7. A device for determining the formulation of dairy fat products based on mathematical programming, characterized in that, include: The constraint module is used to obtain the preset design constraints for dairy fat product formulations. The preset constraints include: a first constraint, a second constraint, a third constraint, and a fourth constraint; the first constraint includes the nutrient content requirements in dairy fat products; the second constraint includes the restrictions on the amount of raw materials used by the production process equipment for dairy fat products; the third constraint includes food safety standards; and the fourth constraint includes the restrictions on the amount of raw materials used due to the time required for the production process of dairy fat products. The objective function module is used to establish an objective function with production demand as the objective and the types and quantities of raw materials to be selected as decision variables. The production demand includes: minimizing product cost, minimizing production time, minimizing energy consumption of production equipment, and minimizing the difficulty in obtaining production raw materials. The formula solving module is used to solve the objective function under preset constraints to obtain a set of decision variables that meet production requirements. This set of decision variables is then used as the formula for dairy fat products.

8. The apparatus as claimed in claim 7, characterized in that, The second constraint includes the limitation on the amount of raw materials used by the maximum volume of the material tank and the minimum volume required for normal production of the material tank.

9. The apparatus as claimed in claim 7, characterized in that, The fourth constraint includes the limitation on the amount of raw materials used due to continuous sterilization of multiple material tanks, which needs to satisfy the following inequality: Among them, M tank C represents the mass of material in each container to be filled. UHT T represents the production capacity of ultra-high temperature instantaneous sterilization technology. blending This represents the mixing time for each can of material.

10. The apparatus as claimed in claim 7, characterized in that, The preset constraints also include: the range of nutrient content values ​​for the raw materials to be selected; The range of values ​​is determined as follows: The nutrient content of the candidate raw materials was analyzed using mathematical statistics methods to obtain statistical indicators of the nutrient content of the candidate raw materials; the statistical indicators included: mean, variance, and standard deviation. Based on the statistical indicators of the nutrient content of the candidate raw materials, a normality test was performed on the nutrient content of the candidate raw materials to obtain the range of values ​​for the nutrient content of the candidate raw materials.

11. The apparatus as claimed in claim 7, characterized in that, The difficulty in obtaining raw materials is determined by the production output data, transportation data, and number of suppliers in the raw material supply chain.

12. The apparatus as claimed in claim 7, characterized in that, The formula for dairy fat products includes: a butter formula; the preset constraints also include: the amount of fermented butter added is 0.4%, and the fat content of the final butter product is not less than 83.5% and not more than 86%.

13. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the method of any one of claims 1 to 6.

14. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the method of any one of claims 1 to 6.

15. A computer program product, characterized in that, The computer program product includes a computer program that, when executed by a processor, implements the method of any one of claims 1 to 6.

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