Cargo management method, computing device and machine readable storage medium

Abstract

The embodiment of the invention discloses a cargo management method, computing equipment and a machine readable storage medium, and belongs to the technical field of big data processing. The cargo management method comprises the following steps: inputting a plurality of undetermined shipment prices corresponding to cargos into a preset price-quantity relationship large model, and obtaining a corresponding predicted shipment quantity of the cargos under each undetermined shipment price output by the preset price-quantity relationship large model; fitting each undetermined shipment price corresponding to the goods and the corresponding predicted shipment quantity to obtain a price and quantity fitting function corresponding to the goods by taking the shipment prices of the goods as independent variables and the shipment quantity of the goods as dependent variables; solving a first optimal solution of the first shipment pricing, a second optimal solution of the second shipment pricing and a third optimal solution of the target purchase quantity of each kind of goods obtained under the condition of maximizing the target function; and for each cargo, generating a cargo management strategy according to the corresponding first optimal solution, the second optimal solution and the third optimal solution.

Description

Technical Field

[0001] This application relates to the technical field of big data processing, and specifically to a method for managing goods, a computing device, and a machine-readable storage medium. Background Art

[0002] With the rapid development of Internet technology, enterprises can not only ship goods through offline retail physical stores, but also through Internet channels such as online shopping malls and cross-border e-commerce platforms. The number of ways for users to purchase goods is constantly increasing, and the shipping prices of each way are different, which will result in differences in the shipping quantity of goods.

[0003] In the actual goods management scenario, the shipping strategy is usually to set a fixed shipping price according to the cost of each good. When the demand for goods shows seasonal fluctuations, the fixed-price goods management strategy will affect the shipping quantity, thereby reducing the profit of the goods. In addition, the purchasing strategy is usually to purchase goods based on the interval time, and the inventory of goods is prone to overstock or shortage of supply, thereby reducing the profit of the goods. Summary of the Invention

[0004] The purpose of the embodiments of this application is to provide a method for managing goods, a computing device, and a machine-readable storage medium. The method for managing goods is used to solve the problem in the prior art that the fixed goods management strategy reduces the profit of goods.

[0005] To achieve the above purpose, the first aspect of this application provides a method for managing goods, which includes: For each type of good, input multiple pending shipping prices corresponding to the type of good into a preset price-quantity relationship large model, and obtain the expected shipping quantity corresponding to the type of good at each pending shipping price output by the preset price-quantity relationship large model; For each type of good, fit each pending shipping price corresponding to the type of good and the expected shipping quantity corresponding thereto, and obtain a price-quantity fitting function corresponding to the type of good with the shipping price of the good as the independent variable and the shipping quantity of the good as the dependent variable; Based on the first shipment price, second shipment price, first shipment quantity, second shipment quantity, and target purchase quantity of each type of goods, construct an objective function for the total profit for the current time period and the next time period. Among them, the first shipment price of any type of goods is the shipment price to be set for that type of goods within the current time period, and the first shipment price belongs to the decision variables. The second shipment price of any type of goods is the shipment price to be set for that type of goods within the next time period, and the second shipment price belongs to the decision variables. The first shipment quantity of any type of goods is the expected shipment quantity of that type of goods within the current time period and is characterized by the first shipment price through the price-volume fitting function of the goods. The second shipment quantity of any type of goods is the expected shipment quantity of that type of goods within the next time period and is characterized by the second shipment price through the price-volume fitting function of the goods. The target purchase quantity of any type of goods is the purchase quantity to be set for that type of goods within the current time period and belongs to the decision variables; Solve for the first optimal solution of the first shipment price, the second optimal solution of the second shipment price, and the third optimal solution of the target purchase quantity of each type of goods obtained under the condition of maximizing the objective function; For each type of goods, generate a management strategy for the goods according to the corresponding first optimal solution, second optimal solution, and third optimal solution.

[0006] In the embodiments of the present application, constructing an objective function for the total profit for the current time period and the next time period based on the first shipment price, second shipment price, first shipment quantity, second shipment quantity, and target purchase quantity of each type of goods includes: Determine the first shipment price, second shipment price, and target purchase quantity of each type of goods as decision variables; Determine the first effective shipment quantity corresponding to the current time period for each type of goods under the influence of the decision variables; Based on the first effective shipment quantity corresponding to each type of goods, determine the second effective shipment quantity corresponding to the next time period for that type of goods under the influence of the decision variables; For any type of goods among each type of goods, based on the first effective shipment quantity, first shipment price, and purchase price within the current time period corresponding to that type of goods, determine the first period profit corresponding to the current time period for that type of goods. Among them, the purchase price of that type of goods within the current time period is a known quantity queried through the supplier supply platform; For any type of goods among each type of goods, based on the second effective shipment quantity, second shipment price, and purchase price within the next time period corresponding to that type of goods, determine the second period profit corresponding to the next time period for that type of goods. Among them, the purchase price of that type of goods within the next time period is a known quantity predicted through the historical purchase price of that type of goods; Construct an objective function for the total profit of the current time period and the next time period based on the first-period profit and the second-period profit corresponding to all goods.

[0007] In the embodiments of the present application, determining the first effective shipment quantity corresponding to the current time period for each good under the influence of decision variables includes: For any one of the goods, substitute the first shipment price corresponding to the good into the price-quantity fitting function corresponding to the good to obtain the first shipment quantity of the good characterized by the first shipment price of the good; Based on the first shipment quantity corresponding to the good, the inventory quantity within the current time period, and the target purchase quantity, determine the first effective shipment quantity corresponding to the current time period under the influence of decision variables, where the inventory quantity within the current time period is a known quantity.

[0008] In the embodiments of the present application, based on the first effective shipment quantity corresponding to each good, determining the second effective shipment quantity corresponding to the next time period for the good under the influence of decision variables includes: For any one of the goods, substitute the first shipment price corresponding to the good into the price-quantity fitting function corresponding to the good to obtain the second shipment quantity of the good characterized by the second shipment price of the good; Based on the second shipment quantity corresponding to the good, the first effective shipment quantity, and the target purchase quantity, determine the second effective shipment quantity corresponding to the next time period under the influence of decision variables.

[0009] In the embodiments of the present application, solving for the first optimal solution of the first shipment price, the second optimal solution of the second shipment price, and the third optimal solution of the target purchase quantity for each good obtained by maximizing the objective function includes: Based on the purchase price and the target purchase quantity of each good in the current time period, determine the total cost of each good in the current time period; According to the total cost and the target purchase quantity of each good, determine the constraint conditions of the objective function; Solve for the first optimal solution of the first shipment price, the second optimal solution of the second shipment price, and the third optimal solution of the target purchase quantity for each good obtained by maximizing the objective function under the condition of satisfying the constraint conditions.

[0010] In the embodiments of the present application, the preset price-quantity relationship large model is obtained through the following steps: For each good, determine the goods case information corresponding to each historical time period according to the historical shipment price, historical purchase quantity, and historical shipment quantity of the good in each historical time period; Train an initial large model based on all cargo case information to obtain a preset price - volume relationship large model.

[0011] In an embodiment of the present application, training an initial large model based on all cargo case information to obtain a preset price - volume relationship large model includes: For each cargo case information of each type of cargo, determine the historical shipment pricing and historical purchase quantity as the model input parameters of the sample, and determine the historical shipment quantity as the model output parameter of the sample, to obtain a training sample corresponding to the cargo case information; Iteratively train the initial large model based on all training samples until a preset price - volume relationship large model is obtained.

[0012] In an embodiment of the present application, training an initial large model based on all cargo case information to obtain a preset price - volume relationship large model includes: Based on all cargo case information of each type of cargo, construct a preset question. The preset question is used to construct a question - answering scenario for the shipment pricing corresponding to the shipment quantity. The question - answering scenario is used to guide the initial large model to output a corresponding estimated shipment quantity for the shipment pricing of any type of cargo input by the user in subsequent question - answering tasks; Input the preset question into the initial large model to obtain a preset price - volume relationship large model.

[0013] A second aspect of the present application provides a computing device, including: A memory configured to store instructions; A processor configured to call instructions from the memory and capable of implementing the above - mentioned cargo management method when executing the instructions.

[0014] A third aspect of the present application provides a machine - readable storage medium, on which instructions are stored. The instructions are used to cause a machine to execute the above - mentioned cargo management method.

[0015] The present application provides a goods management method, including: for each type of goods, inputting multiple pending shipment pricing corresponding to the type of goods into a preset price - quantity relationship large model to obtain the expected shipment quantity corresponding to the type of goods at each pending shipment pricing output by the preset price - quantity relationship large model; for each type of goods, fitting each pending shipment pricing corresponding to the type of goods and the corresponding expected shipment quantity to obtain a price - quantity fitting function corresponding to the type of goods with the shipment pricing of the goods as the independent variable and the shipment quantity of the goods as the dependent variable; based on the first shipment pricing, the second shipment pricing, the first shipment quantity, the second shipment quantity, and the target purchase quantity of each type of goods, constructing an objective function for the total profit for the current time period and the next time period; solving the first optimal solution of the first shipment pricing, the second optimal solution of the second shipment pricing, and the third optimal solution of the target purchase quantity of each type of goods obtained under the condition of maximizing the objective function; for each type of goods, generating a management strategy according to the corresponding first optimal solution, second optimal solution, and third optimal solution. By determining the shipment quantity affected by the shipment pricing through the large model, the management strategy in different shipment and purchase environments is further determined. Through the management strategy for shipment and purchase management, profit maximization can be achieved, and the situations of overstock or out - of - stock can be avoided.

[0016] Other features and advantages of the embodiments of the present application will be described in detail in the subsequent specific implementation part. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The drawings are used to provide a further understanding of the embodiments of the present application and constitute a part of the specification. Together with the following specific implementation, they are used to explain the embodiments of the present application, but do not constitute a limitation to the embodiments of the present application. In the drawings: Figure 1 Schematically shows a flowchart of a goods management method according to an embodiment of the present application; Figure 2 Schematically shows a structural diagram of a goods management device according to an embodiment of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0018] To make the objectives, technical solutions, and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. It should be understood that the specific implementation described here is only used to explain and illustrate the embodiments of the present application, and is not used to limit the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present application.

[0019] It should be noted that if there are directional indications involved in the embodiments of the present application, the directional indications are only used to explain the relative positional relationship, movement conditions, etc. between components in a certain specific posture. If the specific posture changes, the directional indications will also change accordingly.

[0020] In addition, if there are descriptions such as "first", "second", etc. involved in the embodiments of the present application, the descriptions of "first", "second", etc. are only for descriptive purposes and cannot be understood as indicating or implying their relative importance or implicitly specifying the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include at least one such feature. In addition, the technical solutions between various embodiments can be combined with each other, but it must be based on the ability of those of ordinary skill in the art to implement. When the combination of technical solutions results in contradictions or cannot be implemented, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection required by the present application.

[0021] Embodiment 1 Figure 1 A flowchart of a goods management method according to an embodiment of the present application is schematically shown. As Figure 1 shown, an embodiment of the present application provides a goods management method, and the goods management method includes: S110. For each type of goods, input a plurality of pending shipment pricing corresponding to the type of goods into a preset price-quantity relationship large model, and obtain the expected shipment quantity corresponding to the type of goods at each pending shipment pricing output by the preset price-quantity relationship large model; Generally, the profit of a type of goods is related to data such as the purchase price, the shipment price, and the shipment quantity. The shipment price and the purchase quantity can be artificially adjusted to maximize the profit of the goods. Generally, there is an inverse relationship between the shipment price and the shipment quantity, that is, the higher the shipment price, the lower the shipment quantity, and the lower the shipment price, the higher the shipment quantity. At the same time, the purchase price in the current time period is known, and the change in the purchase price will affect the shipment price and then affect the shipment quantity. When the expected shipment quantity is accurately obtained, the purchase quantity can be adjusted to be equal to the expected shipment quantity, so that the goods turnover and the capital collection efficiency are faster. When the shipment price changes, the actual shipment quantity will change. With the purchase price determined and the goal of maximizing profit, it can be determined that there is a fitting relationship between the shipment price and the shipment quantity of the goods.

[0022] The large model of AIGC (Artificial Intelligence Generated Content) can intelligently generate corresponding text, videos and other results based on the prompt (question) input by the user. In this embodiment, the large model is pre-trained to obtain a preset price-volume relationship large model for predicting the shipment quantity. For each type of goods to be shipped, a plurality of pending shipment pricing corresponding to the goods are input into the preset price-volume relationship large model, and the preset price-volume relationship large model is queried multiple times to obtain the predicted shipment quantity corresponding to each pending shipment pricing of the goods output by the preset price-volume relationship large model.

[0023] S120, for each type of goods, fit each pending shipment pricing corresponding to the goods and the predicted shipment quantity corresponding thereto to obtain a price-volume fitting function corresponding to the goods with the shipment pricing of the goods as the independent variable and the shipment quantity of the goods as the dependent variable.

[0024] To maximize profits, different shipment pricings will be set in different time periods. A plurality of pending shipment pricing corresponding to the goods are input into the preset price-volume relationship large model for multiple queries to obtain the predicted shipment quantity corresponding to the pending shipment pricing under different time periods. Taking the shipment pricing and shipment quantity of the goods as coordinates, inputting a variety of pending shipment pricing into the preset price-volume relationship large model and performing multiple queries, multiple points between the shipment pricing and the shipment quantity can be obtained, and then taking the shipment pricing of the goods as the independent variable and the shipment quantity of the goods as the dependent variable.

[0025] By using a fitting function algorithm tool to fit multiple points, that is, for each type of goods, fit all the pending shipment pricing corresponding to the goods and the predicted shipment quantity to obtain a price-volume fitting function corresponding to the goods with the shipment pricing of the goods as the independent variable and the shipment quantity as the dependent variable. When the shipment pricing is determined, the shipment quantity corresponding to different shipment pricings can be determined through the fitting function. The type of the fitting function is set according to actual needs and is not limited herein. For ease of understanding, the fitting function in the embodiments of the present application is a differentiable explicit polynomial function with the shipment pricing as the variable.

[0026] After generating the management strategy for the goods, the purchase price of the goods is a known quantity, that is, the purchase price for the current time period can be queried and determined. For each type of goods, multiple pending selling prices are preset in advance. The multiple pending selling prices and the purchase price for the current time period are input into the preset price-volume relationship large model to obtain the estimated selling quantity corresponding to each pending selling price output by the preset price-volume relationship large model. By using the preset price-volume relationship large model for multiple Q&A sessions, multiple sets of coordinate points corresponding to the selling price and the selling quantity are obtained. For ease of understanding, in the embodiments of the present application, the selling price is used as the x-axis of the function, and the selling data is used as the y-axis of the function. The multiple sets of coordinate points obtained are fitted to generate a fitting function for characterizing the selling quantity.

[0027] S130. Based on the first selling price, the second selling price, the first selling quantity, the second selling quantity, and the target purchase quantity of each type of goods, construct an objective function for the total profit for the current time period and the next time period, where the first selling price of any type of goods is the selling price to be set for that type of goods within the current time period, and the first selling price belongs to the decision variable, the second selling price of any type of goods is the selling price to be set for that type of goods within the next time period, and the second selling price belongs to the decision variable, the first selling quantity of any type of goods is the estimated selling quantity of that type of goods within the current time period and is characterized by the first selling price through the price-volume fitting function of the goods, the second selling quantity of any type of goods is the estimated selling quantity of that type of goods within the next time period and is characterized by the second selling price through the price-volume fitting function of the goods, and the target purchase quantity of any type of goods is the purchase quantity to be set for that type of goods within the current time period and belongs to the decision variable.

[0028] In the case where the goods are unsalable recently, it usually causes the purchase price of the goods to decrease or the quantity of goods in the warehouse to be sufficient. When the purchase price in the current time period is low and it is determined that the selling quantity in the next time period is high, goods can be stockpiled in advance at a low purchase price in the current time period and sold in the current time period and the next time period.

[0029] In this implementation, the shipment prices for the t-th time period and the (t + 1)-th time period are determined respectively, where the t-th time period is the current time period, and the (t + 1)-th time period is the next time period after the current time period. The first shipment price of any kind of goods is the shipment price to be set for this kind of goods within the current time period, and the first shipment price belongs to the decision variables. The second shipment price of any kind of goods is the shipment price to be set for this kind of goods within the next time period, and the second shipment price also belongs to the decision variables. Based on the first shipment price, the second shipment price, the first shipment quantity, the second shipment quantity and the target purchase quantity of each kind of goods, an objective function for the total profit for the current time period and the next time period is constructed.

[0030] In this embodiment, the fitting function takes the shipment price of the goods as the independent variable and the shipment quantity of the goods as the dependent variable. The first shipment quantity of any kind of goods is the expected shipment quantity of this kind of goods within the current time period, and the first shipment quantity is characterized by the first shipment price through the price-volume fitting function of the goods. The second shipment quantity of any kind of goods is the expected shipment quantity of this kind of goods within the next time period, and the second shipment quantity is characterized by the second shipment price through the price-volume fitting function of the goods. The target purchase quantity of any kind of goods is the purchase quantity to be set for this kind of goods within the current time period, and the target purchase quantity belongs to the decision variables.

[0031] In the embodiments of the present application, based on the first shipment price, the second shipment price, the first shipment quantity, the second shipment quantity and the target purchase quantity of each kind of goods, an objective function for the total profit for the current time period and the next time period is constructed, including: Determine the first shipment price, the second shipment price and the target purchase quantity of each kind of goods as decision variables; Determine the first effective shipment quantity corresponding to the current time period of each kind of goods under the influence of the decision variables; Based on the first effective shipment quantity corresponding to each kind of goods, determine the second effective shipment quantity corresponding to the next time period of this kind of goods under the influence of the decision variables; For any kind of goods in each kind of goods, based on the first effective shipment quantity, the first shipment price and the purchase price within the current time period corresponding to this kind of goods, determine the first period profit corresponding to the current time period of this kind of goods, where the purchase price of this kind of goods within the current time period is a known quantity queried through the supplier supply platform; For any one of each type of goods, based on the second effective shipment quantity, the second shipment price, and the purchase price in the next time period corresponding to that one of each type of goods, determine the second-period profit corresponding to that one of each type of goods in the next time period, where the purchase price of that one of each type of goods in the next time period is a known quantity predicted from the historical purchase price of that one of each type of goods; Based on the first-period profit and the second-period profit corresponding to all goods, construct an objective function for the total profit for the current time period and the next time period.

[0032] Not only does the shipment price affect the shipment quantity, but the purchase quantity also affects the shipment quantity. When the purchase quantity is low, if the inventory quantity of the goods is insufficient, it is easy to have a situation of supply falling short of demand, resulting in the actual shipment quantity being lower than the required shipment quantity. Determine the first shipment price, the second shipment price, and the target purchase quantity of each type of goods as decision variables, and then determine the first effective shipment quantity corresponding to each type of goods in the current time period under the influence of the decision variables. In addition, the shipment quantity in the current time period will affect the inventory quantity in the next time period, and then the change in the inventory quantity will affect the shipment quantity in the next time period. Based on the first effective shipment quantity corresponding to each type of goods, determine the second effective shipment quantity corresponding to that type of goods in the next time period under the influence of the decision variables.

[0033] The shipment quantity, the purchase price, and the shipment price all affect the profit of the goods. For any one of each type of goods, based on the first effective shipment quantity, the first shipment price, and the purchase price in the current time period corresponding to that one of each type of goods, determine the first-period profit corresponding to that one of each type of goods in the current time period, where the purchase price of that one of each type of goods in the current time period is a known quantity queried through the supplier supply platform. In addition, the purchase price of any one of each type of goods in the current time period can also be queried through other channels, and the other channels are based on actual needs and can be on-site quotes from suppliers, etc., which are not limited here.

[0034] For any one of each type of goods, based on the second effective shipment quantity, the second shipment price, and the purchase price in the next time period corresponding to that one of each type of goods, determine the second-period profit corresponding to that one of each type of goods in the next time period, where the purchase price of that one of each type of goods in the next time period is a known quantity predicted from the historical purchase price of that one of each type of goods. It should be understood that in the case where there is no purchase in the next time period but only the inventory goods are shipped, then directly use the historical purchase price of that one of each type of goods as the purchase price in the next time period.

[0035] Based on the first-period profit and the second-period profit corresponding to all goods, construct an objective function for the total profit for the current time period and the next time period:

[0036] Formula (1) Wherein is the sum of the profits in the current time period and the next time period is the th kind of goods is the total number of goods is the first effective shipment quantity is the second effective shipment quantity is the purchase price at the current time period is the first shipment price at the current time period is the second shipment price at the next time period

[0037] In the embodiments of the present application, determining the first effective shipment quantity corresponding to the current time period for each kind of goods under the influence of decision variables includes: For any one kind of goods among each kind of goods, substituting the first shipment price corresponding to the any one kind of goods into the price - quantity fitting function corresponding to the any one kind of goods, to obtain the first shipment quantity characterized by the first shipment price of the any one kind of goods; Based on the first shipment quantity corresponding to the any one kind of goods, the inventory quantity and the target purchase quantity within the current time period, determining the first effective shipment quantity corresponding to the current time period under the influence of decision variables, wherein the inventory quantity within the current time period is a known quantity.

[0038] According to the fitting function corresponding to each kind of goods, determining the first predicted shipment quantity of each kind of goods changing with the shipment price within the current time period. In the case where the first predicted shipment quantity of each kind of goods has been determined in advance, for any one kind of goods among each kind of goods, substituting the first shipment price corresponding to the any one kind of goods into the price - quantity fitting function corresponding to the any one kind of goods, to obtain the first shipment quantity characterized by the first shipment price of the any one kind of goods: Formula (2) Wherein is the first effective shipment quantity at the current time period is the th kind of goods is the target purchase quantity within the current time period is the first predicted shipment quantity at the current time period is the inventory quantity at the current time period

[0039] Specifically, calculate the difference in the quantity of goods between the first projected shipment quantity and the inventory quantity to determine whether there is a shortage in quantity. Determine the minimum quantity of goods between the difference in the quantity of goods and the target purchase quantity to determine whether replenishment is needed in the current time period. In the case where the minimum quantity of goods is greater than zero, determine the minimum quantity of goods as the first effective shipment quantity. In the case where the minimum quantity of goods is less than or equal to zero, determine the value of the first effective shipment quantity as zero.

[0040] In an embodiment of the present application, based on the first effective shipment quantity corresponding to each type of goods, determine the second effective shipment quantity corresponding to the next time period of this type of goods under the influence of decision variables, including: For any one type of goods among each type of goods, substitute the first shipment price corresponding to this one type of goods into the price - quantity fitting function corresponding to this one type of goods to obtain the second shipment quantity of this one type of goods characterized by the second shipment price of this one type of goods; Based on the second shipment quantity, the first effective shipment quantity, and the target purchase quantity corresponding to this one type of goods, determine the second effective shipment quantity corresponding to the next time period under the influence of decision variables.

[0041] For any one type of goods among each type of goods, substitute the first shipment price corresponding to this one type of goods into the price - quantity fitting function corresponding to this one type of goods to obtain the second shipment quantity of this one type of goods characterized by the second shipment price of this one type of goods. Based on the second shipment quantity, the first effective shipment quantity, and the target purchase quantity corresponding to this one type of goods, determine the second effective shipment quantity corresponding to the next time period under the influence of decision variables: Formula (3) Wherein, is the second effective shipment quantity, is the th type of goods, is the target purchase quantity within the current time period, is the second projected shipment quantity for the next time period, is the first effective shipment quantity for the current time period.

[0042] Specifically, determine the difference in the quantity of goods between the target purchase quantity and the second effective shipment quantity to determine whether there is a shortage in quantity of goods when the time is in the next time period. Determine the minimum value between the second projected shipment quantity and the difference in the quantity of goods as the second effective shipment quantity.

[0043] S140. Solve the first optimal solution of the first shipment price, the second optimal solution of the second shipment price, and the third optimal solution of the target purchase quantity of each type of goods obtained under the condition of maximizing the objective function.

[0044] Since the shipping price affects the quantity of goods shipped, the change in the shipping price also affects the profit of the goods. The quantity of goods shipped for each item is a known quantity in the objective function. Substitute the quantity of goods shipped in all the fitting functions into the objective function, and solve for maximizing the objective function under the condition that the shipping price affects the quantity of goods shipped, that is, find the maximum profit. Furthermore, solve for the first optimal solution of the first shipping price, the second optimal solution of the second shipping price, and the third optimal solution of the target purchase quantity of each item obtained under the condition of maximizing the objective function.

[0045] In the embodiments of the present application, solving for the first optimal solution of the first shipping price, the second optimal solution of the second shipping price, and the third optimal solution of the target purchase quantity of each item obtained under the condition of maximizing the objective function includes: Based on the purchase price and the target purchase quantity of each item in the current time period, determine the total cost of each item in the current time period; According to the total cost and the target purchase quantity of each item, determine the constraint conditions of the objective function; Solve for the first optimal solution of the first shipping price, the second optimal solution of the second shipping price, and the third optimal solution of the target purchase quantity of each item obtained under the condition of maximizing the objective function while satisfying the constraint conditions.

[0046] Based on the purchase price and the target purchase quantity of each item in the current time period, the total cost of each item in the current time period is determined as: Formula (4) Wherein, is the total cost in the current time period, is the th item, is the total number of items, is the target purchase quantity in the current time period, is the purchase price in the current time period.

[0047] According to the total cost and the target purchase quantity of each item, the constraint conditions of the objective function are determined as: s.t Formula (5) s.t Formula (6) Wherein, is the total cost in the current time period, is the purchase budget in the current time period, is the th item, is the first estimated quantity of goods to be shipped in the current time period, is the second estimated shipment quantity for the next time period, is the target purchase quantity within the current time period, is the inventory quantity of the current time period.

[0048] It should be understood that the purchase budget for the current time period is set according to the actual demand, which can be obtained by multiplying the profit of the (t - 1)th time period by a preset coefficient, and no specific limitation is made here. Based on all the goods case information, an initial large model is trained to obtain a preset price - quantity relationship large model. Substitute the shipment quantity corresponding to the current time period and the second shipment quantity corresponding to the next time period in all the fitting functions into the objective function, and solve for the first optimal solution of the first shipment price, the second optimal solution of the second shipment price, and the third optimal solution of the target purchase quantity of each good when maximizing the objective function under sufficient constraint conditions. In this embodiment, the first effective shipment quantity corresponding to the first shipment quantity and the second effective shipment quantity corresponding to the second shipment quantity are obtained, and the first effective shipment quantity and the second effective shipment quantity are substituted into the objective function for solution.

[0049] S150. For each good, generate a management strategy according to the corresponding first optimal solution, second optimal solution, and third optimal solution.

[0050] For each good, generate a management strategy according to the corresponding first optimal solution, second optimal solution, and third optimal solution. Through the management strategy, the purchase and shipment of goods are managed. Specifically, the purchase is carried out with the third optimal solution of the target purchase quantity, and the shipment is carried out at the first optimal solution of the first shipment price in the current time period and at the second optimal solution of the second shipment price in the next time period.

[0051] In the embodiment of the present application, the preset price - quantity relationship large model is obtained through the following steps: For each good, determine the goods case information corresponding to each historical time period according to the historical shipment price, historical purchase quantity, and historical shipment quantity of the good in each historical time period; Based on all the goods case information, train the initial large model to obtain the preset price - quantity relationship large model.

[0052] For each good, determine the goods case information corresponding to each historical time period according to the historical shipment price, historical purchase quantity, historical shipment quantity, and historical inventory quantity of the good in each historical time period. The historical time period is any period before the current time period, which will not be elaborated here. By organizing the data in the historical time period, the case information for training the large model is obtained. Based on all the goods case information, train the initial large model to obtain the preset price - quantity relationship large model, so as to obtain the fitting relationship between the shipment price and the shipment quantity.

[0053] It should be understood that the goods case information may also include other information about the goods, which is set according to actual needs and may include the goods name, goods type, goods raw materials, etc., and is not limited herein.

[0054] In the embodiments of the present application, an initial large model is trained based on all the goods case information to obtain a preset price-volume relationship large model, including: For each goods case information of each type of goods, the historical shipment pricing and historical purchase quantity are determined as the model input parameters of the sample, and the historical shipment quantity is determined as the model output parameter of the sample, to obtain a training sample corresponding to the goods case information; The initial large model is iteratively trained based on all the training samples until a preset price-volume relationship large model is obtained.

[0055] The type of the initial large model is set according to actual needs and may be any AIGC large model, which is not limited herein. Usually, the initial large model needs to be fine-tuned to obtain a preset price-volume relationship large model that can directly answer questions. The initial large model can be fine-tuned by adjusting the model parameters. Each goods case information is labeled respectively, and then a training sample is determined corresponding to each goods case information. Specifically, for each goods case information of each type of goods, the historical shipment pricing and historical purchase quantity are determined as the model input parameters of the sample, and the historical shipment quantity is determined as the model output parameter of the sample, to obtain a training sample corresponding to the goods case information. Determining the historical shipment quantity as the model output parameter of the sample, that is, determining the historical shipment quantity as the sample label, that is, labeling the sample according to the historical shipment quantity. The initial large model is iteratively trained based on all the training samples to iterate the parameters of the initial large model until the parameters of the large model converge or the number of iterations of the large model reaches a preset number of times, to obtain a preset price-volume relationship large model, and the value of the preset number of times is set according to actual needs and is not limited herein.

[0056] In the embodiments of the present application, an initial large model is trained based on all the goods case information to obtain a preset price-volume relationship large model, including: Based on all the goods case information of each type of goods, a preset question is constructed. The preset question is used to construct a question-and-answer scenario for the shipment pricing corresponding to the shipment quantity, and the question-and-answer scenario is used to guide the initial large model to output the corresponding estimated shipment quantity for the shipment pricing of any type of goods input by the user in the subsequent question-and-answer task; The preset question is input into the initial large model to obtain a preset price-volume relationship large model.

[0057] The initial large model can be fine-tuned by constructing scenarios. Based on all the case information of each type of goods, preset questions are constructed. That is, for any one of the goods in each type of goods, all the case information of this one good is directly used as a prompt question. The preset questions are used to construct a question-and-answer scenario for the corresponding relationship between the shipping price and the shipping quantity. The question-and-answer scenario is used to guide the initial large model to output the corresponding estimated shipping quantity for the shipping price of any one of the goods input by the user in subsequent question-and-answer tasks. The preset questions are input into the initial large model, and a question-and-answer scenario for the corresponding relationship between the shipping price and the shipping quantity is constructed based on the initial large model. Then, without retraining the initial large model, a large model of the preset price-volume relationship is obtained. After constructing the question-and-answer scenario of the large model, multiple undetermined shipping prices corresponding to the goods and the purchase price in the current time period are input into the large model of the preset price-volume relationship, and the estimated shipping quantity corresponding to each undetermined shipping price output by the large model of the preset price-volume relationship is obtained. Using the output of the large model as the basis for generating the strategy can reduce the deviation of subjective judgment, and then manage the pricing and inventory of goods more efficiently.

[0058] This application provides a goods management method, including: for each type of goods, inputting multiple undetermined shipping prices corresponding to this type of goods into the large model of the preset price-volume relationship to obtain the estimated shipping quantity corresponding to each undetermined shipping price of this type of goods output by the large model of the preset price-volume relationship; for each type of goods, fitting each undetermined shipping price corresponding to this type of goods and the corresponding estimated shipping quantity to obtain a price-volume fitting function corresponding to this type of goods with the shipping price of the goods as the independent variable and the shipping quantity of the goods as the dependent variable; based on the first shipping price, the second shipping price, the first shipping quantity, the second shipping quantity and the target purchase quantity of each type of goods, constructing an objective function for the total profit for the current time period and the next time period; solving the first optimal solution of the first shipping price, the second optimal solution of the second shipping price and the third optimal solution of the target purchase quantity of each type of goods obtained under the condition of maximizing the objective function; for each type of goods, generating a management strategy for the goods according to the corresponding first optimal solution, second optimal solution and third optimal solution. By determining the shipping quantity affected by the shipping price through the large model, and then determining the management strategy in different shipping and purchase environments. Managing shipping and purchase through the management strategy can maximize profits and avoid situations of overstock or shortage of supply.

[0059] Embodiment 2 Figure 2 Schematically shows a structural diagram of a goods management device according to an embodiment of the present application. As Figure 2 shown, the embodiment of the present application provides a goods management device 200, and the goods management device 200 includes: A quantity prediction module 210, which is configured to input multiple pending shipment prices corresponding to each type of goods into a preset price - quantity relationship large - model for each type of goods, and obtain the predicted shipment quantity corresponding to each type of goods at each pending shipment price output by the preset price - quantity relationship large - model; A function fitting module 220, which is configured to fit each pending shipment price corresponding to each type of goods and the predicted shipment quantity corresponding thereto for each type of goods, and obtain a price - quantity fitting function corresponding to each type of goods with the shipment price of the goods as the independent variable and the shipment quantity of the goods as the dependent variable; A function construction module 230, which is configured to construct an objective function for the total profit in the current time period and the next time period based on the first shipment price, the second shipment price, the first shipment quantity, the second shipment quantity, and the target purchase quantity of each type of goods, where the first shipment price of any type of goods is the shipment price to be set for the any type of goods in the current time period, and the first shipment price belongs to the decision variables, the second shipment price of any type of goods is the shipment price to be set for the any type of goods in the next time period, and the second shipment price belongs to the decision variables, the first shipment quantity of any type of goods is the predicted shipment quantity of the any type of goods in the current time period and is characterized by the first shipment price through the price - quantity fitting function of the goods, the second shipment quantity of any type of goods is the predicted shipment quantity of the any type of goods in the next time period and is characterized by the second shipment price through the price - quantity fitting function of the goods, and the target purchase quantity of any type of goods is the purchase quantity to be set for the any type of goods in the current time period and belongs to the decision variables; A function solving module 240, which is configured to solve the first optimal solution of the first shipment price, the second optimal solution of the second shipment price, and the third optimal solution of the target purchase quantity of each type of goods obtained under the condition of maximizing the objective function; A strategy generation module 250, which is configured to generate a management strategy for each type of goods according to the corresponding first optimal solution, second optimal solution, and third optimal solution;

[0060] In the embodiments of the present application, the function construction module 230 includes: A variable determination sub - module, which is configured to determine the first shipment price, the second shipment price, and the target purchase quantity of each type of goods as decision variables; A first effective shipment quantity acquisition sub - module, which is configured to determine the first effective shipment quantity corresponding to the current time period of each type of goods under the influence of the decision variables; A second effective shipment quantity acquisition sub - module, which is configured to determine the second effective shipment quantity corresponding to the next time period of each type of goods under the influence of the decision variables based on the first effective shipment quantity corresponding to each type of goods; The first-period profit determination sub-module is used to determine the first-period profit corresponding to any one of each type of goods in the current time period based on the first effective shipment quantity, the first shipment price, and the purchase price in the current time period corresponding to the any one of each type of goods, where the purchase price of the any one of each type of goods in the current time period is a known quantity obtained by querying through the supplier supply platform; The second-period profit determination sub-module is used to determine the second-period profit corresponding to any one of each type of goods in the next time period based on the second effective shipment quantity, the second shipment price, and the purchase price in the next time period corresponding to the any one of each type of goods, where the purchase price of the any one of each type of goods in the next time period is a known quantity predicted from the historical purchase price of the any one of each type of goods; The objective function construction sub-module is used to construct an objective function for the total profit for the current time period and the next time period based on the first-period profit and the second-period profit corresponding to all goods.

[0061] In an embodiment of the present application, the first effective shipment quantity acquisition sub-module is further used to, for any one of each type of goods, substitute the first shipment price corresponding to the any one of each type of goods into the price-quantity fitting function corresponding to the any one of each type of goods to obtain the first shipment quantity of the any one of each type of goods characterized by the first shipment price of the any one of each type of goods; Based on the first shipment quantity corresponding to the any one of each type of goods, the inventory quantity in the current time period, and the target purchase quantity, determine the first effective shipment quantity corresponding to the current time period under the influence of decision variables, where the inventory quantity in the current time period is a known quantity.

[0062] In an embodiment of the present application, the second effective shipment quantity acquisition sub-module is used to determine the second effective shipment quantity corresponding to the next time period of each type of goods under the influence of decision variables based on the first effective shipment quantity corresponding to each type of goods, including: For any one of each type of goods, substitute the first shipment price corresponding to the any one of each type of goods into the price-quantity fitting function corresponding to the any one of each type of goods to obtain the second shipment quantity of the any one of each type of goods characterized by the second shipment price of the any one of each type of goods; Based on the second shipment quantity corresponding to the any one of each type of goods, the first effective shipment quantity, and the target purchase quantity, determine the second effective shipment quantity corresponding to the next time period under the influence of decision variables.

[0063] In an embodiment of the present application, the function solving module 240 includes: The cost determination module is used to determine the total cost of each type of goods in the current time period based on the purchase price and the target purchase quantity of each type of goods in the current time period; A constraint determination module, configured to determine the constraint conditions of the objective function according to the total cost and the target purchase quantity of each type of goods; An objective function solution sub-module, configured to solve the first optimal solution of the first shipment price, the second optimal solution of the second shipment price, and the third optimal solution of the target purchase quantity of each type of goods obtained by maximizing the objective function under the sufficient constraint conditions.

[0064] In the embodiments of the present application, the preset price-volume relationship large model is obtained through the following steps: For each type of goods, according to the historical shipment price, historical purchase quantity, and historical shipment quantity of the goods in each historical time period, determine the goods case information corresponding to each historical time period; Train the initial large model based on all the goods case information to obtain the preset price-volume relationship large model.

[0065] In the embodiments of the present application, training the initial large model based on all the goods case information to obtain the preset price-volume relationship large model includes: For each goods case information, determine the historical shipment price, historical purchase price, historical purchase quantity, and historical inventory quantity as samples, and determine the historical shipment quantity as the sample label to obtain the training samples corresponding to the goods case information; Iteratively train the initial large model based on all the training samples until the preset price-volume relationship large model is obtained.

[0066] In the embodiments of the present application, training the initial large model based on all the goods case information to obtain the preset price-volume relationship large model includes: Based on all the goods case information of each type of goods, construct a preset question, which is used to construct a question-and-answer scenario for the shipment price corresponding to the shipment quantity. The question-and-answer scenario is used to guide the initial large model to output the corresponding inferred shipment quantity for any shipment price of the goods input by the user in the subsequent question-and-answer task; Input the preset question into the initial large model to obtain the preset price-volume relationship large model.

[0067] The embodiments of the present application further provide a computing device, including: A memory, configured to store instructions; A processor, configured to call instructions from the memory and be able to implement the above-mentioned goods management method when executing the instructions.

[0068] The embodiments of the present application further provide a machine-readable storage medium, on which instructions are stored, and the instructions are used to cause the machine to execute the above-mentioned goods management method.

[0069] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0070] The present application is described with reference to the flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each flow and / or block in the flowchart and / or block diagram, as well as the combination of flows and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate means for implementing the functions specified in Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

[0071] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory generate a manufactured article including instruction means, and the instruction means implements the functions specified in Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

[0072] These computer program instructions can also be loaded onto a computer or other programmable data processing device, so that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process. Thus, the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

[0073] In a typical configuration, a computing device includes one or more processors (CPUs), an input / output interface, a network interface, and memory.

[0074] The memory may include non-permanent memory in the computer-readable medium, in the form of random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash memory (flash RAM). The memory is an example of a computer-readable medium.

[0075] A computer-readable medium includes permanent and non-permanent, removable and non-removable media that can implement information storage by any method or technology. The information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory, or other memory technologies, CD-ROM, digital versatile disk (DVD), or other optical storage, magnetic cassette tapes, disk storage, or other magnetic storage devices, or any other non-transitory medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer-readable medium does not include transitory computer-readable media, such as modulated data signals and carrier waves.

[0076] It should also be noted that the term "comprising", "including", or any other variant thereof is intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a series of elements includes not only those elements but also other elements not expressly listed, or elements that are inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the statement "comprising an..." does not exclude the presence of additional identical elements in the process, method, article, or apparatus that comprises the element.

[0077] The above are only embodiments of the present application and are not used to limit the present application. For those skilled in the art, various changes and modifications can be made to the present application. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present application shall be included within the scope of the claims of the present application.

Claims

1. A cargo management method, characterized in that: The cargo management method comprises: For each type of goods, multiple pending shipping prices corresponding to the goods are input into a preset price-volume relationship macromodel, and the preset price-volume relationship macromodel outputs an estimated shipping quantity of the goods corresponding to each pending shipping price; For each type of goods, each pending shipping price corresponding to the goods and the corresponding expected shipping quantity are fitted to obtain a price-volume fitting function corresponding to the goods with the shipping price of the goods as an independent variable and the shipping quantity of the goods as a dependent variable; Based on the first shipping price, the second shipping price, the first shipping quantity, the second shipping quantity and the target purchase quantity of each type of goods, an objective function for the total profit of the current time period and the next time period is constructed, wherein the first shipping price of any type of goods is the shipping price to be set for any type of goods in the current time period, and the first shipping price is a decision variable, the second shipping price of any type of goods is the shipping price to be set for any type of goods in the next time period, and the second shipping price is a decision variable, the first shipping quantity of any type of goods is the expected shipping quantity of any type of goods in the current time period and is represented by the first shipping price through the price-quantity fitting function of the goods, the second shipping quantity of any type of goods is the expected shipping quantity of any type of goods in the next time period and is represented by the second shipping price through the price-quantity fitting function of the goods, and the target purchase quantity of any type of goods is the purchase quantity to be set for any type of goods in the current time period and is a decision variable; Solving for a first optimal solution of the first shipping price, a second optimal solution of the second shipping price, and a third optimal solution of the target purchase quantity for each commodity obtained under the condition of maximizing the objective function; For each type of goods, a management strategy for the goods is generated according to the corresponding first optimal solution, the second optimal solution and the third optimal solution.

2. The cargo management method according to claim 1, characterized in that: The objective function for total profit of the current time period and the next time period is constructed based on the first shipping price, the second shipping price, the first shipping quantity, the second shipping quantity and the target purchase quantity of each product, including: Determine the first shipping price, the second shipping price and the target purchase quantity of each product as decision variables; Determine the first effective shipment quantity of each product corresponding to the current time period under the influence of the decision variables; Based on the first effective shipment quantity corresponding to each type of goods, determine the second effective shipment quantity corresponding to the next time period under the influence of the decision variable for the type of goods; For any one of each type of goods, based on the first effective shipment quantity, the first shipment price and the purchase price in the current time period corresponding to the any one of the goods, determine the first period profit corresponding to the any one of the goods in the current time period, wherein the purchase price of the any one of the goods in the current time period is a known quantity obtained by querying the supplier supply platform; For any one of each type of goods, based on the second effective shipment quantity, the second shipment price and the purchase price in the next time period corresponding to the any one of the goods, determine the second period profit corresponding to the any one of the goods in the next time period, wherein the purchase price of the any one of the goods in the next time period is a known quantity obtained by predicting the historical purchase price of the any one of the goods; Based on the first-period profit and the second-period profit corresponding to all goods, an objective function for the total profit of the current time period and the next time period is constructed.

3. The cargo management method according to claim 2, characterized in that: The determining of the first effective shipment quantity of each product corresponding to the current time period under the influence of the decision variable includes: For any one of each type of goods, the first shipping price corresponding to the any one of the goods is substituted into the price-volume fitting function corresponding to the any one of the goods to obtain the first shipping quantity of the any one of the goods represented by the first shipping price of the any one of the goods; Based on the first shipping quantity corresponding to any one type of goods, the inventory quantity in the current time period and the target purchase quantity, determine the first effective shipping quantity corresponding to the current time period under the influence of the decision variable, wherein the inventory quantity in the current time period is a known quantity.

4. The cargo management method according to claim 2, characterized in that: The determining, based on the first effective shipment quantity corresponding to each type of goods, a second effective shipment quantity corresponding to the next time period under the influence of the decision variable for the type of goods includes: For any one of each type of goods, the first shipping price corresponding to the any one of the goods is substituted into the price-volume fitting function corresponding to the any one of the goods to obtain the second shipping quantity of the any one of the goods represented by the second shipping price of the any one of the goods; Based on the second shipping quantity, the first effective shipping quantity and the target purchase quantity corresponding to any one type of goods, the second effective shipping quantity corresponding to the next time period under the influence of the decision variable is determined.

5. The cargo management method according to claim 1, characterized in that: The solving of the first optimal solution of the first shipping price, the second optimal solution of the second shipping price and the third optimal solution of the target purchase quantity for each product obtained under the condition of maximizing the objective function includes: Determine the total cost of each of the goods in the current time period based on the purchase price of each of the goods in the current time period and the target purchase quantity; Determining the constraint conditions of the objective function according to the total cost and target purchase quantity of each of the goods; A first optimal solution of the first shipping price, a second optimal solution of the second shipping price, and a third optimal solution of the target purchase quantity for each commodity are obtained by maximizing the objective function under the constraints.

6. The cargo management method according to claim 1, characterized in that: The preset price-volume relationship model is obtained by the following steps: For each of the goods, determine the goods case information corresponding to each historical time period according to the historical shipment pricing, historical purchase quantity, and historical shipment quantity of the goods in each historical time period; An initial large model is trained based on all the cargo case information to obtain the preset price-volume relationship large model.

7. The cargo management method according to claim 6, characterized in that: The initial large model is trained based on all the cargo case information to obtain the preset price-volume relationship large model, including: For each case information of each type of goods, the historical shipping price and the historical purchase quantity are determined as the model input parameters of the sample, and the historical shipping quantity is determined as the model output parameter of the sample to obtain a training sample corresponding to the case information of the goods; The initial large model is iteratively trained based on all the training samples until the preset price-volume relationship large model is obtained.

8. The cargo management method according to claim 6, characterized in that: The initial large model is trained based on all the cargo case information to obtain the preset price-volume relationship large model, including: Based on all the cargo case information of each cargo, a preset question is constructed, wherein the preset question is used to construct a question-and-answer scenario of the corresponding shipment quantity of the shipment price, and the question-and-answer scenario is used to guide the initial large model to output the corresponding estimated shipment quantity for the shipment price of any cargo input by the user in a subsequent question-and-answer task; The preset question is input into the initial big model to obtain the preset price-volume relationship big model.

9. A computing device, characterized in that include: a memory configured to store instructions; A processor is configured to call the instructions from the memory and implement the cargo management method according to any one of claims 1 to 8 when executing the instructions.

10. A machine-readable storage medium, characterized in that: The machine-readable storage medium stores instructions for causing a machine to execute the cargo management method according to any one of claims 1 to 8.

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