System and method for generating production strategy and channel selection strategy considering product demand

Abstract

The present invention discloses a system and method for generating a production strategy and a channel selection strategy that considers product demand. The present invention first collects product demand data and manufacturing cost data of manufacturers in each time period; secondly, obtains sales data of direct sales channels and entrusted sales channels; finally, inputs the data of the collection module and the data acquisition module into the supply chain production decision model to solve and obtain the optimal production strategy under different channels. The present invention also selects the optimal channel according to the optimal production strategy. The present invention has higher accuracy, and the generated strategy can provide a reference for manufacturers' production and channel selection.

Description

Technical Field

[0001] The present invention relates to the field of computer information processing technology, and in particular to a system and method for generating a production strategy and a channel selection strategy taking product demand into consideration. Background Art

[0002] In recent years, with the rapid development of e-commerce platforms, more and more manufacturers have opened online sales channels. Usually, producers have two channel options for online sales: selling through self-built official websites, which is called direct sales channels; or cooperating with e-commerce platforms to open official flagship stores on the platforms for sales, which is called commissioned sales channels. When producers want to directly access consumers through online retail channels, they face a key issue, which is which channel to choose. Therefore, more and more studies have begun to focus on the issue of manufacturers' online sales channel selection and the factors that affect channel selection.

[0003] The lot-sizing problem (LSP) is one of the most important problems in the field of production planning. LSP has always received extensive attention from scholars, especially the single-item lot-sizing problem (SILSP), because SILSP is relatively simple and is also particularly important as a sub-problem of the more complex LSP. Based on the basic single-item lot-sizing model, scholars have made a lot of extensions, among which the assumptions on demand, including out-of-stock losses and backlogs, and elastic demand are closely related to the research issues of this invention.

[0004] In existing research, the assumptions about demand mainly include backlog and lost sales. Backlog means that the current unmet demand can be met later, while lost sales means that the unmet demand will be lost. Existing research has taken backlog and lost sales into account, but the accuracy of production strategy and channel selection decisions still needs to be improved. Summary of the invention

[0005] In view of the problems existing in the prior art, the present invention provides a system and method for generating a production strategy and a channel selection strategy that takes product demand into consideration with higher accuracy.

[0006] In order to achieve the above-mentioned object of the invention, the present invention provides a production strategy generation system considering product demand, comprising:

[0007] The collection module is used to collect the product demand data and manufacturing cost data of the manufacturer in each time period;

[0008] Data acquisition module, used to obtain sales data of direct sales channels and commissioned sales channels;

[0009] Supply chain production decision model, specifically:

[0010]

[0011] i t-1 +x t =(D t -L t )+I t ,t=1,2,...,T;

[0012] L t ≤D t ,t=1,2,…,T;

[0013] I t ·L t =0,t=1,2,…,T;

[0014]

[0015]

[0016] In the formula, φ is the total profit, and the product production data includes I t ,L t ,D t , manufacturing cost data includes m, h, π, and sales data of direct sales channels and commissioned sales channels include μ, θ, α, The product production strategy is x t , x t is the manufacturer's product production in time period t, T is the total number of time periods, I t is the manufacturer’s product inventory at the end of time period t, L t is the manufacturer’s product shortage in time period t, D t is the demand for the product in time period t, is the pricing of the product in the direct sales channel and the commissioned sales channel in time period t, m is the unit production cost of the product, h is the unit inventory cost of the product, π is the unit out-of-stock loss cost of the product, μ is the market share of the direct sales channel, θ is the fixed fee that the manufacturer needs to pay to the e-commerce platform in each time period in the commissioned sales channel, and α is the profit sharing ratio of the e-commerce platform; when μ=1 and θ=0 and α=0, there is only the direct sales channel, and when θ>0 and 0<α<1, it is a mixed channel with both direct sales and commissioned sales channels;

[0017] The production strategy generation module is used to input the data from the collection module and the data acquisition module into the supply chain production decision model to solve the optimal production strategy under different channels.

[0018] Furthermore, the production strategy generation module specifically includes:

[0019] The model conversion unit is used to convert the supply chain production decision model into the following first linear programming model:

[0020] min-φ;

[0021]

[0022]

[0023]

[0024] …

[0025] I t ≥x t -D t ,t=1,2,...,T;

[0026] L t ≥D t -x t ,t=1,2,...,T;

[0027] x t ,I t ,L t ≥0,t=1,2,...,T.

[0028] The linear programming solving unit is used to solve the optimal production strategy under different channels of the manufacturer by analyzing the KKT conditions of the first linear programming model according to the data of the collection module and the data acquisition module.

[0029] The present invention also provides a channel selection strategy generation system considering product demand, comprising:

[0030] The collection module is used to collect the product demand data and manufacturing cost data of the manufacturer in each time period;

[0031] Supply chain production pricing decision model, specifically:

[0032]

[0033] i t-1 +x t =(D t -L t )+I t ,t=1,2,…,T;

[0034] L t ≤D t ,t=1,2,…,T;

[0035] I t ·L t =0,t=1,2,…,T;

[0036]

[0037]

[0038] In the formula, φ is the total profit, and the product production data includes I t ,L t ,D t , manufacturing cost data includes m, h, π, x t is the manufacturer's product production volume in time period t, is the generation strategy variable, T is the total number of time periods, I t is the manufacturer’s product inventory at the end of time period t, L t is the manufacturer’s product shortage in time period t, D t is the demand for the product in time period t, is the pricing of the product in the direct sales channel and the commissioned sales channel in time period t, is the pricing strategy variable, m is the unit production cost of the product, h is the unit inventory cost of the product, π is the unit out-of-stock loss cost of the product, μ is the market share of the direct sales channel, θ is the fixed fee that the manufacturer needs to pay to the e-commerce platform in each time period in the commissioned sales channel, and α is the profit sharing ratio of the e-commerce platform; when θ=0 and α=0 and μ=1, there is only the direct sales channel, and the others are mixed channels where both direct sales channels and commissioned sales channels exist;

[0039] The production strategy generation module is used to input the data of the collection module into the supply chain production pricing decision model to solve the optimal production strategy under different channels;

[0040] A pricing strategy generation module, used to solve the supply chain production pricing decision model based on the optimal production strategy to obtain the optimal pricing strategy under different channels;

[0041] The channel selection strategy generation module is used to determine the total profit under different channels based on the optimal production strategy and optimal pricing strategy under different channels, and select the channel with the largest total profit as the channel selection strategy output.

[0042] Furthermore, the production strategy generation module specifically includes:

[0043] The model conversion unit is used to convert the supply chain production pricing decision model into the following first linear programming model:

[0044] min-φ;

[0045]

[0046]

[0047]

[0048] …

[0049] I t ≥x t -D t , t=1,2,...,T;

[0050] L t ≥D t -x t , t=1,2,...,T;

[0051] x t , I t , L t ≥0, t=1, 2, ..., T.

[0052] The linear programming solving unit is used to solve the optimal production strategy under different channels of the manufacturer according to the data of the acquisition module by analyzing the KKT conditions of the first linear programming model.

[0053] Furthermore, the pricing strategy generation module specifically includes:

[0054] The model conversion unit is used to convert the supply chain production pricing decision model into the following second mathematical programming model:

[0055] min-φ′;

[0056]

[0057]

[0058] In the formula, represents the predicted value of the product demand uncertainty coefficient, ω represents the market percentage expanded by the entrusted sales channel for the manufacturer, b represents the price elasticity coefficient of the product, and a represents the demand coefficient;

[0059] The mathematical programming solving unit is used to solve the optimal pricing strategy of the manufacturer's direct sales channel according to the data of the acquisition module by analyzing the Lagrangian function and KKT conditions of the second mathematical programming model in the case of a single channel; in the case of a mixed channel, the method of solving nonlinear constrained optimization is used to solve the optimal pricing strategy of the manufacturer under different channels according to the data of the acquisition module.

[0060] The present invention also provides a method for generating a production strategy taking product demand into consideration, comprising the following steps:

[0061] Collect product demand data and manufacturing cost data of manufacturers in different time periods;

[0062] Obtain sales data from direct sales channels and commissioned sales channels;

[0063] The supply chain production decision model is constructed as follows:

[0064]

[0065] i t-1 +x t =(D t -L t )+I t , t=1,2,...,T;

[0066] L t ≤D t ,t=1,2,…,T;

[0067] I t ·L t =0,t=1,2,…,T;

[0068]

[0069]

[0070] In the formula, φ is the total profit, and the product production data includes I t ,L t ,D t , manufacturing cost data includes m, h, π, and sales data of direct sales channels and commissioned sales channels include μ, θ, α, The product production strategy is x t , x t is the manufacturer's product production in time period t, T is the total number of time periods, I t is the manufacturer’s product inventory at the end of time period t, L t is the manufacturer’s product shortage in time period t, D t is the demand for the product in time period t, is the pricing of the product in the direct sales channel and the commissioned sales channel in time period t, m is the unit production cost of the product, h is the unit inventory cost of the product, π is the unit out-of-stock loss cost of the product, μ is the market share of the direct sales channel, θ is the fixed fee that the manufacturer needs to pay to the e-commerce platform in each time period in the commissioned sales channel, and α is the profit sharing ratio of the e-commerce platform; when μ=1 and θ=0 and α=0, there is only the direct sales channel, and when θ>0 and 0<α<1, it is a mixed channel with both direct sales and commissioned sales channels;

[0071] The data from the collection module and the data acquisition module are input into the supply chain production decision model to obtain the optimal production strategy under different channels.

[0072] Furthermore, the data from the collection module and the data acquisition module are input into the supply chain production decision model to solve the optimal production strategy under different channels, specifically including:

[0073] The supply chain production decision model is converted into the following first linear programming model:

[0074] min-φ;

[0075]

[0076]

[0077]

[0078] …

[0079] I t ≥x t -D t ,t=1,2,...,T;

[0080] L t ≥D t -x t ,t=1,2,...,T;

[0081] x t ,I t ,L t ≥0,t=1,2,...,T.

[0082] By analyzing the KKT conditions of the first linear programming model, the optimal production strategy for the manufacturer under different channels is solved according to the data of the collection module and the data acquisition module.

[0083] The present invention also provides a method for generating a channel selection strategy taking product demand into consideration, comprising the following steps:

[0084] Collect product demand data and manufacturing cost data of manufacturers in different time periods;

[0085] The supply chain production pricing decision model is constructed as follows:

[0086]

[0087] i t-1 +x t =(D t -L t )+I t ,t=1,2,…,T;

[0088] L t ≤D t ,t=1,2,…,T;

[0089] I t ·L t =0,t=1,2,…,T;

[0090]

[0091]

[0092] In the formula, φ is the total profit, and the product production data includes I t ,L t ,D t , manufacturing cost data includes m, h, π, x t is the manufacturer's product production volume in time period t, is the generation strategy variable, T is the total number of time periods, I t is the manufacturer’s product inventory at the end of time period t, L t is the manufacturer’s product shortage in time period t, D t is the demand for the product in time period t, is the pricing of the product in the direct sales channel and the commissioned sales channel in time period t, is the pricing strategy variable, m is the unit production cost of the product, h is the unit inventory cost of the product, π is the unit out-of-stock loss cost of the product, μ is the market share of the direct sales channel, θ is the fixed fee that the manufacturer needs to pay to the e-commerce platform in each time period in the commissioned sales channel, and α is the profit sharing ratio of the e-commerce platform; when θ=0 and α=0 and μ=1, there is only the direct sales channel, and the others are mixed channels where both direct sales channels and commissioned sales channels exist;

[0093] Input the collected data into the supply chain production pricing decision model to solve the optimal production strategy under different channels;

[0094] Based on the optimal production strategy, solve the supply chain production pricing decision model to obtain the optimal pricing strategy under different channels;

[0095] According to the optimal production strategy and optimal pricing strategy under different channels, the total profit under different channels is determined, and the channel with the largest total profit is selected as the output of the channel selection strategy.

[0096] Furthermore, the collected data is input into the supply chain production pricing decision model to solve the optimal production strategy under different channels, specifically including:

[0097] The supply chain production pricing decision model is converted into the following first linear programming model:

[0098] min-φ;

[0099]

[0100]

[0101]

[0102] …

[0103] I t ≥x t -D t ,t=1,2,...,T;

[0104] L t ≥D t -x t ,t=1,2,...,T;

[0105] x t ,I t ,L t ≥0,t=1,2,...,T.

[0106] By analyzing the KKT conditions of the first linear programming model, the optimal production strategy for the manufacturer under different channels is solved based on the collected data.

[0107] Furthermore, based on the optimal production strategy, solving the supply chain production pricing decision model to obtain the optimal pricing strategy under different channels specifically includes:

[0108] The supply chain production pricing decision model is converted into the following second mathematical programming model:

[0109] min-φ′;

[0110]

[0111]

[0112] In the formula, represents the predicted value of the product demand uncertainty coefficient, ω represents the market percentage expanded by the entrusted sales channel for the manufacturer, b represents the price elasticity coefficient of the product, and a represents the demand coefficient;

[0113] In the case of a single channel, by analyzing the Lagrangian function and KKT conditions of the second mathematical programming model, the optimal pricing strategy of the manufacturer's direct sales channel is solved according to the data of the acquisition module; in the case of a mixed channel, the method of solving nonlinear constrained optimization is adopted, and the optimal pricing strategy of the manufacturer under different channels is solved according to the data of the acquisition module.

[0114] Compared with the prior art, the present invention has the following beneficial effects: the present invention can generate the optimal production strategy and the optimal channel selection strategy with higher accuracy, and can provide reference opinions for manufacturers. BRIEF DESCRIPTION OF THE DRAWINGS

[0115] Figure 1 is a system block diagram of a production strategy generation system considering product requirements provided by an embodiment of the present invention;

[0116] Figure 2 is a system block diagram of a channel selection strategy generation system considering product demand provided by an embodiment of the present invention;

[0117] Figure 3 It is a graph showing the optimal pricing changing with the demand price elasticity b;

[0118] Figure 4 This is a graph showing the impact of demand price elasticity and direct sales channel sales share on profits. DETAILED DESCRIPTION

[0119] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0120] Before describing the embodiments, the following description is first made of the problems solved by the embodiments of the present invention and the symbols.

[0121] Consider that in each time period t (t=1,2,...,T), a manufacturer produces a certain product and sells it online. The manufacturer has two sales channels i: direct sales channel O and commissioned sales channel C. Assume that the manufacturer has opened a direct sales channel and can choose to open or not open a commissioned sales channel. Therefore, the manufacturer has two channel models, one is to sell only through direct sales channels, called a single channel model; the other is to sell through both direct sales channels and commissioned sales channels, called a mixed channel model.

[0122] Assuming that the e-commerce platform has the same or stronger competitiveness as the manufacturer's official website, the manufacturer will attract more consumers and expand the market by opening a commissioned sales channel. ω represents the percentage of the market that can be expanded for the manufacturer by opening a commissioned sales channel. When the manufacturer does not open a commissioned sales channel, ω = 0; when the manufacturer opens a commissioned sales channel, ω > 0. In addition, the manufacturer's opening of a commissioned sales channel will also erode the market share of some direct sales channels. μ represents the market share of direct sales channels. When the manufacturer does not open a commissioned sales channel, μ = 1; when the manufacturer opens a commissioned sales channel, the two channels will share the total market share, and 0 < μ ≤ 0.5. If the manufacturer's official website and the e-commerce platform have the same competitiveness, then it is assumed that the manufacturer's official website and the e-commerce platform each account for half of the total market share, that is, μ = 0.5; if the manufacturer's official website is less competitive, then the market share of the manufacturer's official website is less than half of the total market share, that is, 0 < μ < 0.5, so 0 < μ ≤ 0.5.

[0123] Let x t is the manufacturer's product production in time period t; I t is the manufacturer’s product inventory at the end of time period t; L t is the product shortage quantity of the manufacturer in time period t. P is the price of the product; let is the product pricing in channel i at time period t, satisfying The prices are determined by the manufacturer. In order to distinguish the pricing of direct sales channels under the two channel models, represents the pricing of the product in the direct sales channel O at time period t under the single channel model. Let D t is the demand for the product in time period t. Let m be the unit production cost of the product, satisfying that the product pricing is not lower than the unit production cost; h is the unit inventory cost of the product; π is the unit out-of-stock loss cost of the product. Regardless of which channel model the manufacturer chooses, the unit production cost, unit inventory cost and unit out-of-stock cost of the product are unchanged. The manufacturer's costs include the production cost, inventory cost and out-of-stock loss cost of the product. Since the manufacturer can choose to open a commissioned sales channel, the manufacturer's costs also need to consider the service fee of the commissioned sales channel and the revenue shared with the platform. Let θ be the fixed fee that the manufacturer needs to pay to the e-commerce platform in each time period when opening the commissioned sales channel; let α be the revenue sharing ratio of the e-commerce platform. In the single channel mode, take θ=0 and α=0; in the mixed channel mode, take θ>0 and 0<α<1.

[0124] In view of the above problems, an embodiment of the present invention provides a production strategy generation system that takes product demand into consideration, such as Figure 1 As shown, including:

[0125] The collection module is used to collect the product demand data and manufacturing cost data of the manufacturer in each time period;

[0126] Data acquisition module, used to obtain sales data of direct sales channels and commissioned sales channels;

[0127] Supply chain production decision model, specifically:

[0128]

[0129] i t-1 +x t =(D t -L t )+I t ,t=1,2,...,T;

[0130] L t ≤D t ,t=1,2,...,T;

[0131] I t ·L t =0,t=1,2,...,T;

[0132]

[0133]

[0134] In the formula, φ is the total profit, and the product production data includes I t ,L t ,D t , manufacturing cost data includes m, h, π, and sales data of direct sales channels and commissioned sales channels include μ, θ, α, The product production strategy is x t , when μ=1, θ=0 and α=0, there is only direct sales channel, and the objective function is When θ>0 and 0<α<1, it is a mixed channel where both direct sales channel and commissioned sales channel exist;

[0135] The production strategy generation module is used to input the data from the collection module and the data acquisition module into the supply chain production decision model to solve the optimal production strategy under different channels.

[0136] Wherein, the production strategy generation module specifically includes a model conversion unit and a linear programming solution unit.

[0137] The model conversion unit is used to convert the supply chain production decision model into the first linear programming model. The specific conversion process is that the inventory quantity I in the problem can be converted into the first linear programming model according to the constraint conditions. t and the out-of-stock quantity L tWritten as production x t and demand D t The expression of Y t =x t -D t ,but

[0138]

[0139]

[0140] The objective function of the supply chain production decision model is equivalent to min-φ. Therefore, the problem is equivalent to an optimization problem of minimizing the objective, and the model can be further transformed into the following linear programming problem:

[0141] min-φ;

[0142]

[0143]

[0144]

[0145] …

[0146] I t ≥x t -D t ,t=1,2,...,T;

[0147] L t ≥D t -x t ,t=1,2,...,T;

[0148] x t ,I t ,L t ≥0,t=1,2,...,T.

[0149] The linear programming solving unit is used to solve the optimal production strategy under different channels of the manufacturer according to the data of the collection module and the data acquisition module by analyzing the KKT conditions of the first linear programming model.

[0150] The final optimal solution is: The optimal objective function value is:

[0151] The above optimal solution shows that the optimal production decision of the manufacturer is to produce according to the predicted demand in each time period. The optimal objective function value obtained is the profit under the optimal production decision. Based on such a production decision, the manufacturer's pricing decision is analyzed below.

[0152] The embodiment of the present invention also provides a channel selection strategy generation system considering product demand, such as Figure 2 As shown, including:

[0153] The collection module is used to collect the product demand data and manufacturing cost data of the manufacturer in each time period;

[0154] Supply chain production pricing decision model, specifically:

[0155]

[0156] i t-1 +x t =(D t -L t )+I t ,t=1,2,...,T;

[0157] L t ≤D t ,t=1,2,...,T;

[0158] I t ·L t =0,t=1,2,...,T;

[0159]

[0160]

[0161] In the formula, φ is the total profit, and the product production data includes I t ,L t ,D t , manufacturing cost data includes m, h, π, x t To generate policy variables, is the pricing strategy variable;

[0162] The production strategy generation module is used to input the data of the collection module into the supply chain production pricing decision model to solve the optimal production strategy under different channels;

[0163] A pricing strategy generation module, used to solve the supply chain production pricing decision model based on the optimal production strategy to obtain the optimal pricing strategy under different channels;

[0164] The channel selection strategy generation module is used to determine the total profit under different channels based on the optimal production strategy and optimal pricing strategy under different channels, and select the channel with the largest total profit as the channel selection strategy output.

[0165] Wherein, the production strategy generation module specifically includes a model conversion unit and a linear programming solution unit.

[0166] The model conversion unit is used to convert the supply chain production pricing decision model into the following first linear programming model:

[0167] min-φ;

[0168]

[0169]

[0170]

[0171] ……I t ≥x t -D t ,t=1,2,...,T;

[0172] L t ≥D t -x t ,t=1,2,...,T;

[0173] x t ,I t ,L t ≥0,t=1,2,...,T.

[0174] The linear programming solving unit is used to solve the optimal production strategy under different channels of the manufacturer according to the data of the acquisition module by analyzing the KKT conditions of the first linear programming model.

[0175] The pricing strategy generation module specifically includes a model conversion unit and a mathematical programming solution unit.

[0176] The model conversion unit is used to convert the supply chain production pricing decision model into the second mathematical programming model. The conversion process is as follows:

[0177] When studying the optimal pricing decision of the manufacturer, the optimal production decision is taken as the known production volume, and the total profit φ′ under the optimal production decision of the manufacturer in the total time period T is obtained as:

[0178]

[0179] To further study the manufacturer’s pricing decision, for each time period t, consider the manufacturer’s total product demand D t It's about pricing t i In the single-channel mode, the demand function is expressed as:

[0180]

[0181] In the hybrid mode, the demand function is expressed as:

[0182]

[0183] Obviously, the demand function under the single-channel model is the mixed-mode demand function when μ=1 and ω=0. Therefore, the mixed-mode demand function summarizes the demand functions under the two channel models. Considering that the demand for the product is elastic to the price, the price elasticity coefficient of the product demand b>1, the demand coefficient a>0, and ε represents the uncertainty coefficient of product demand, which can reflect the uncertainty of demand. This paper uses Represents the predicted value of ε. Similar demand functions have been widely used in existing literature and will not be described in detail.

[0184] Therefore, D in the expression of total profit φ′ is t Replace with and The expression of

[0185] min-φ′;

[0186]

[0187]

[0188] The mathematical programming solving unit is used to analyze the Lagrangian function and KKT conditions of the second mathematical programming model, and finally solve the optimal pricing decision and the corresponding optimal profit of the manufacturer under the optimal production decision under the single channel mode according to the data of the acquisition module:

[0189]

[0190]

[0191] In the mixed channel model, it is impossible to find the optimal pricing combination for manufacturers. and optimal profit The expression is calculated according to the specific example below. First, the optimal pricing combination and optimal profit of the manufacturer under the mixed channel model are obtained through numerical examples. Then, the influence of the product demand price elasticity and the competitiveness of the manufacturer's direct sales channel on the manufacturer's optimal pricing decision and the optimal channel model is analyzed. The parameters in the model are m = 20, h = 6, π = 30, a = 1500, P = 250. Considering the total time period T = 12, each time period t represents one month, and the total time period represents the whole year.

[0192] Since the variables and parameters do not change with time in the example, let In order to solve the optimal pricing of manufacturers in the hybrid channel model, we first calculate different pricing combinations (P O ,P C) to ensure that m<p O ≤P,m<p C ≤P to ensure the practical significance of the analysis, and take the pricing with the highest profit as the optimal pricing combination under the manufacturer's mixed channel model The highest total profit is taken as the optimal total profit φ′ under the manufacturer's optimal pricing * .

[0193] According to the actual charging rules of a certain e-commerce platform, if the annual sales amount of a manufacturer on the platform reaches 180,000, it can enjoy a discount of half the annual service fee; if the annual sales amount of a manufacturer on the platform reaches 600,000, it can be exempted from paying the annual service fee. Represents the annual sales amount of the platform. When the manufacturer's annual sales φ C <180000,θ=5000; annual sales 180000≤φ C <600000, θ′=2500; annual sales φ C When ≥600000, θ″=0. Take parameter α=5%, select demand price elasticity b=1.1, 1.2, 1.3, 1.4, 1.5, 1.6, 1.7, 1.8, 1.9, 2.0, and take (μ, ω) equal to (10%, 1), (20%, 0.5), (30%, 0.1), (40%, 0.05) and (50%, 0.01) respectively in the mixed channel mode. Different combinations of (μ, ω) correspond to different channel competitiveness of the manufacturer's direct sales channel. For example, when (μ, ω)=(10%, 1), The competitiveness of the manufacturer's direct sales channel is very low. Only 10% of consumers choose to purchase through the direct sales channel in the mixed channel model, and the opening of the commissioned sales channel can greatly expand the manufacturer's market; (μ, ω) = (50%, 0.01) The competitiveness of the manufacturer's direct sales channel is high. In the mixed channel model, 50% of consumers still purchase through the direct sales channel, and the opening of the commissioned sales channel will hardly expand the demand market for the manufacturer. The optimal channel pricing under different scenarios of the mixed channel model can be solved through Python programming. The results are shown in Table 2.

[0194] Table 2 The optimal pricing combination of manufacturers under the hybrid channel model (p O* ,p C* )

[0195]

[0196] In the single-channel model, the optimal pricing and optimal profit of the manufacturer's direct sales channel are related to the price elasticity coefficient of demand for the product, b. Analyzing the monotonicity of the optimal pricing and optimal profit of the manufacturer in the single-channel model with respect to the price elasticity of demand for the product, we can obtain that: in the single-channel model, as the price elasticity coefficient of demand increases, the optimal pricing of the manufacturer Decreasing, the manufacturer's optimal profit Decreasing. This shows that if the manufacturer sells in a single channel model, the higher the demand price elasticity, the more the product should be sold at a lower price. The following is an analysis of the impact of demand price elasticity on the manufacturer's optimal pricing decision under the mixed channel model. The optimal channel pricing results under the single channel model and the mixed channel model are as follows: Figure 3 Analysis Figure 3 The results of (a)-(e) all lead to the conclusion that when the price elasticity of demand b is small, At this time, as b increases Decrease; when b increases to exceed a critical point b', as b increases Decreasing, Then when b increases to another critical point b″, Suddenly rise, Suddenly decreases, when b≥b″, as b increases Decreasing, Increasing.

[0197] It is known that products with higher demand price elasticity should be sold at a lower price. It can be seen that under the mixed channel model, the pricing of direct sales channels also has similar changing rules. The critical point b′ appears because when b reaches a certain large value, selling at a lower price in the direct sales channel can increase sales and enable manufacturers to obtain higher profits. When b=b″, Suddenly rise, The sudden decrease is mainly caused by the change of θ. Figure 3 From (a)-(e), we can find that the market share μ of the manufacturer’s direct sales channel also affects the values ​​of the critical points b′ and b″. It can be observed that: μ = 10% corresponds to b′ = 1.8; μ = 20% corresponds to b′ = 1.4, b″ = 2.0; when μ = 30%, it corresponds to b′ = 1.3, b″ = 1.9; μ = 40% corresponds to b′ = 1.2, b″ = 1.9; when μ = 50%, it corresponds to b′ = 1.1, b″ = 1.8. It can be concluded that the increase in the market share μ of the direct sales channel will reduce the values ​​of the critical points b′ and b″ of b.

[0198] The above conclusions show that if manufacturers adopt a mixed channel model, the pricing of direct sales channels should usually be higher than that of commissioned sales channels. For products with slightly lower demand price elasticity, the pricing of direct sales channels can be equal to the product's list price. For products with slightly higher demand price elasticity, the pricing of direct sales channels can be lower than the product's list price, adopting a strategy of small profits but quick turnover. In addition, the more competitive the manufacturer's direct sales channel is, the more it should lower the price of its products in the direct sales channel. When conducting channel pricing, the impact of platform charging rules should also be considered.

[0199] In order to analyze the impact of channel competitiveness on the optimal channel model of manufacturers, we first calculate the optimal profit of manufacturers under different channel selection models, and compare the profits to obtain the optimal channel model of manufacturers. If the profit under the single channel model is greater than the profit under the mixed channel model, then the optimal channel choice for the manufacturer is to open only the direct sales channel without opening the commissioned sales channel; if the profit under the mixed channel model is greater than the profit under the single channel model, then the optimal channel for the manufacturer is to open both channels at the same time. The results of the manufacturer's optimal profit are as follows: Figure 4 As shown. By comparing the total profits of the two channel selection modes, we can conclude that: when the value of μ is relatively small, the mixed channel mode can significantly increase the total profit of the manufacturer; when the value of μ is moderate, b is small, the mixed channel mode can significantly increase the total profit of the manufacturer; when b is large, the total profit under the mixed channel mode is slightly lower than the total profit of the single channel mode; when the value of μ is relatively large, the total profit of the single channel mode is slightly higher than the total profit of the mixed channel mode. It shows that manufacturers with different channel competitiveness will have different optimal channel selection modes. When the competitiveness of the manufacturer's direct sales channel is very low, the manufacturer can obtain greater profits by adopting the mixed channel mode. On the contrary, if the competitiveness of the manufacturer's direct sales channel is high, then the mixed channel mode will not bring greater profits to the manufacturer. In this case, the manufacturer should carefully consider whether to cooperate with the e-commerce platform. In addition, if the competitiveness of the manufacturer's direct sales channel is moderate, then there will be different optimal channel choices for different demand price elasticities of products. Products with lower demand price elasticity are more suitable for sales through the mixed channel mode, and products with higher demand price elasticity are suitable for sales through the single channel mode.

[0200] Based on the above conclusions, we can analyze whether the manufacturer is suitable for opening a commissioned sales channel or for selling only through direct sales channels. (1) μ is small, and the manufacturer's direct sales channel has low competitiveness. For manufacturers with such characteristics, opening a commissioned sales channel can expand the product demand market and attract more consumers. Manufacturers with such characteristics, such as emerging companies with low product brand awareness, are more suitable for opening commissioned sales channels at the same time. (2) μ is moderate, and the manufacturer's direct sales channel has moderate competitiveness. Whether a manufacturer with such characteristics is suitable for opening a commissioned sales channel depends on the price elasticity of demand for the products it sells. If the products sold by the manufacturer are commodities with high price elasticity of demand (b is large), such as commodities with many substitutes, non-daily necessities or high-end commodities, then the manufacturer is suitable for selling only through direct sales channels; on the contrary, if the products sold by the manufacturer are commodities with low price elasticity of demand (b is small), then the manufacturer is more suitable for selling through commissioned sales channels. (3) μ is large, and the manufacturer's direct sales channel has strong competitiveness. For manufacturers with such characteristics, opening a commissioned sales channel will not expand the market, but they will need to pay a certain fee to the platform. Therefore, manufacturers that meet this characteristic, such as internationally renowned companies, are more suitable to sell only through direct sales channels.

[0201] In summary, the optimal channel model selection for manufacturers can be summarized as Table 3. The above conclusions can provide important decision-making basis for manufacturers involved in online sales.

[0202] Table 3 Optimal channel selection for manufacturers under different channel competitiveness and product demand price elasticity

[0203]

[0204] The embodiment of the present invention also provides a method for generating a production strategy taking into account product demand, comprising the following steps:

[0205] Collect product demand data and manufacturing cost data of manufacturers in different time periods;

[0206] Obtain sales data from direct sales channels and commissioned sales channels;

[0207] The supply chain production decision model is constructed as follows:

[0208]

[0209] i t-1 +x t =(D t -L t )+I t ,t=1,2,...,T;

[0210] L t ≤D t,t=1,2,...,T;

[0211] I t ·L t =0,t=1,2,...,T;

[0212]

[0213]

[0214] In the formula, φ is the total profit, and the product production data includes I t ,L t ,D t , manufacturing cost data includes m, h, π, and sales data of direct sales channels and commissioned sales channels include μ, θ, α, The product production strategy is x t , x t is the manufacturer's product production in time period t, T is the total number of time periods, I t is the manufacturer’s product inventory at the end of time period t, L t is the manufacturer’s product shortage in time period t, D t is the demand for the product in time period t, is the pricing of the product in the direct sales channel and the commissioned sales channel in time period t, m is the unit production cost of the product, h is the unit inventory cost of the product, π is the unit out-of-stock loss cost of the product, μ is the market share of the direct sales channel, θ is the fixed fee that the manufacturer needs to pay to the e-commerce platform in each time period in the commissioned sales channel, and α is the profit sharing ratio of the e-commerce platform; when μ=1 and θ=0 and α=0, there is only the direct sales channel, and when θ>0 and 0<α<1, it is a mixed channel with both direct sales and commissioned sales channels;

[0215] The data from the collection module and the data acquisition module are input into the supply chain production decision model to obtain the optimal production strategy under different channels.

[0216] The data from the collection module and the data acquisition module are input into the supply chain production decision model to solve the optimal production strategy under different channels, specifically including:

[0217] The supply chain production decision model is converted into the following first linear programming model:

[0218] min-φ;

[0219]

[0220]

[0221]

[0222] …

[0223] I t ≥x t -D t ,t=1,2,...,T;

[0224] L t ≥D t -x t ,t=1,2,...,T;

[0225] x t ,I t ,L t ≥0,t=1,2,...,T.

[0226] By analyzing the KKT conditions of the first linear programming model, the optimal production strategy for the manufacturer under different channels is solved according to the data of the collection module and the data acquisition module.

[0227] The embodiment of the present invention also provides a method for generating a channel selection strategy taking into account product demand, comprising the following steps:

[0228] Collect product demand data and manufacturing cost data of manufacturers in different time periods;

[0229] The supply chain production pricing decision model is constructed as follows:

[0230]

[0231] i t-1 +x t =(D t -L t )+I t ,t=1,2,...,T;

[0232] L t ≤D t ,t=1,2,...,T;

[0233] I t ·L t =0,t=1,2,...,T;

[0234]

[0235]

[0236] In the formula, φ is the total profit, and the product production data includes I t ,L t ,D t , manufacturing cost data includes m, h, π, xt is the manufacturer's product production volume in time period t, is the generation strategy variable, T is the total number of time periods, I t is the manufacturer’s product inventory at the end of time period t, L t is the manufacturer’s product shortage in time period t, D t is the demand for the product in time period t, is the pricing of the product in the direct sales channel and the commissioned sales channel in time period t, is the pricing strategy variable, m is the unit production cost of the product, h is the unit inventory cost of the product, π is the unit out-of-stock loss cost of the product, μ is the market share of the direct sales channel, θ is the fixed fee that the manufacturer needs to pay to the e-commerce platform in each time period in the commissioned sales channel, and α is the profit sharing ratio of the e-commerce platform; when θ=0 and α=0 and μ=1, there is only the direct sales channel, and the others are mixed channels where both direct sales channels and commissioned sales channels exist;

[0237] Input the collected data into the supply chain production pricing decision model to solve the optimal production strategy under different channels;

[0238] Based on the optimal production strategy, solve the supply chain production pricing decision model to obtain the optimal pricing strategy under different channels;

[0239] According to the optimal production strategy and optimal pricing strategy under different channels, the total profit under different channels is determined, and the channel with the largest total profit is selected as the output of the channel selection strategy.

[0240] The collected data is input into the supply chain production pricing decision model to solve the optimal production strategy under different channels, specifically including:

[0241] The supply chain production pricing decision model is converted into the following first linear programming model:

[0242] min-φ;

[0243]

[0244]

[0245]

[0246] …

[0247] I t ≥x t -D t ,t=1,2,...,T;

[0248] L t ≥D t -x t ,t=1,2,...,T;

[0249] x t ,I t ,L t ≥0,t=1,2,...,T.

[0250] By analyzing the KKT conditions of the first linear programming model, the optimal production strategy for the manufacturer under different channels is solved based on the collected data.

[0251] Wherein, based on the optimal production strategy, solving the supply chain production pricing decision model to obtain the optimal pricing strategy under different channels specifically includes:

[0252] The supply chain production pricing decision model is converted into the following second mathematical programming model:

[0253] min-φ′;

[0254]

[0255]

[0256] In the formula, represents the predicted value of the product demand uncertainty coefficient, ω represents the market percentage expanded by the entrusted sales channel for the manufacturer, b represents the price elasticity coefficient of the product, and a represents the demand coefficient;

[0257] In the single-channel mode, by analyzing the Lagrangian function and KKT conditions of the model, the optimal pricing strategy of the manufacturer under the direct sales channel is solved according to the data of the acquisition module. In the mixed channel mode, the method of solving nonlinear constrained optimization is adopted to solve the optimal pricing strategy of the manufacturer under different channels according to the data of the acquisition module.

Claims

1. A production strategy generation system considering product demand, characterized in that: include: The collection module is used to collect the product demand data and manufacturing cost data of the manufacturer in each time period; Data acquisition module, used to obtain sales data of direct sales channels and commissioned sales channels; Supply chain production decision model, specifically: s.t.I t-1 +x t =(D t -L t )+I t ,t=1,2,...,T; L t ≤D t ,t=1,2,...,T; I t ·L t =0,t=1,2,...,T; In the formula, φ is the total profit, and the product production data includes I t ,L t ,D t , manufacturing cost data includes m, h, π, and sales data of direct sales channels and commissioned sales channels include μ, θ, α, Product production strategies include x t , x t is the manufacturer's product production in time period t, T is the total number of time periods, I t is the manufacturer’s product inventory at the end of time period t, L t is the manufacturer’s product shortage quantity in time period t, D t is the demand for the product in time period t, is the pricing of the product in the direct sales channel and the commissioned sales channel in time period t, m is the unit production cost of the product, h is the unit inventory cost of the product, π is the unit out-of-stock loss cost of the product, μ is the market share of the direct sales channel, θ is the fixed fee that the manufacturer needs to pay to the e-commerce platform in each time period in the commissioned sales channel, and α is the profit sharing ratio of the e-commerce platform; when μ=1 and θ=0 and α=0, there is only the direct sales channel, and when θ>0 and 0<α<1, it is a mixed channel with both direct sales and commissioned sales channels; The production strategy generation module is used to input the data from the collection module and the data acquisition module into the supply chain production decision model to solve the optimal production strategy under different channels.

2. The production strategy generation system considering product demand according to claim 1, characterized in that: The production strategy generation module specifically includes: The model conversion unit is used to convert the supply chain production decision model into the following first linear programming model: min-φ; …… I t ≥x t -D t ,t=1,2,...,T; L t ≥D t -x t ,t=1,2,...,T; x t ,I t ,L t ≥0,t=1,2,...,T. Among them, x k is the manufacturer’s product output in time period k, D k is the demand for the product in time period k; The linear programming solving unit is used to solve the optimal production strategy under different channels of the manufacturer by analyzing the KKT conditions of the first linear programming model according to the data of the collection module and the data acquisition module.

3. A channel selection strategy generation system considering product demand, characterized in that: include: The collection module is used to collect the product demand data and manufacturing cost data of the manufacturer in each time period; Supply chain production pricing decision model, specifically: s.t.I t-1 +x t =(D t -L t )+I t ,t=1,2,...,T; L t ≤D t ,t=1,2,...,T; I t ·L t =0,t=1,2,...,T; In the formula, φ is the total profit, and the product production data includes I t ,L t ,D t , manufacturing cost data includes m, h, π, x t is the manufacturer's product production volume in time period t, is the generation strategy variable, T is the total number of time periods, I t is the manufacturer’s product inventory at the end of time period t, L t is the manufacturer’s product shortage quantity in time period t, D t is the demand for the product in time period t, is the pricing of the product in the direct sales channel and the commissioned sales channel in time period t, is the pricing strategy variable, m is the unit production cost of the product, h is the unit inventory cost of the product, π is the unit out-of-stock loss cost of the product, μ is the market share of the direct sales channel, θ is the fixed fee that the manufacturer needs to pay to the e-commerce platform in each time period in the commissioned sales channel, and α is the profit sharing ratio of the e-commerce platform; when θ=0 and α=0 and μ=1, there is only the direct sales channel, and the others are mixed channels where both direct sales channels and commissioned sales channels exist; The production strategy generation module is used to input the data of the collection module into the supply chain production pricing decision model to solve the optimal production strategy under different channels; A pricing strategy generation module, used to solve the supply chain production pricing decision model based on the optimal production strategy to obtain the optimal pricing strategy under different channels; The channel selection strategy generation module is used to determine the total profit under different channels based on the optimal production strategy and optimal pricing strategy under different channels, and select the channel with the largest total profit as the channel selection strategy output.

4. The channel selection strategy generation system considering product demand according to claim 3 is characterized in that: The production strategy generation module specifically includes: The model conversion unit is used to convert the supply chain production pricing decision model into the following first linear programming model: min-φ; …… I t ≥x t -D t ,t=1,2,...,T; L t ≥D t -x t ,t=1,2,...,T; x t ,I t ,L t ≥0,t=1,2,...,T. Among them, x k is the manufacturer’s product output in time period k, D k is the demand for the product in time period k; The linear programming solving unit is used to solve the optimal production strategy under different channels of the manufacturer according to the data of the acquisition module by analyzing the KKT conditions of the first linear programming model.

5. The channel selection strategy generation system considering product demand according to claim 3 is characterized in that: The pricing strategy generation module specifically includes: The model conversion unit is used to convert the supply chain production pricing decision model into the following second mathematical programming model: min-φ′; In the formula, represents the predicted value of the product demand uncertainty coefficient, ω represents the market percentage expanded by the entrusted sales channel for the manufacturer, b represents the price elasticity coefficient of the product, and a represents the demand coefficient; The mathematical programming solving unit is used to solve the optimal pricing strategy of the manufacturer's direct sales channel according to the data of the acquisition module by analyzing the Lagrangian function and KKT conditions of the second mathematical programming model in the case of a single channel; in the case of a mixed channel, the method of solving nonlinear constrained optimization is used to solve the optimal pricing strategy of the manufacturer under different channels according to the data of the acquisition module.

6. A method for generating a production strategy taking into account product demand, characterized in that: The steps include: Collect product demand data and manufacturing cost data of manufacturers in different time periods; Obtain sales data from direct sales channels and commissioned sales channels; The supply chain production decision model is constructed as follows: s.t.I t-1 +x t =(D t -L t )+I t ,t=1,2,...,T; L t ≤D t ,t=1,2,...,T; I t ·L t =0,t=1,2,…,T; In the formula, φ is the total profit, and the product production data includes I t ,L t ,D t , manufacturing cost data includes m, h, π, and sales data of direct sales channels and commissioned sales channels include μ, θ, α, Product production strategies include x t , x t is the manufacturer's product production in time period t, T is the total number of time periods, I t is the manufacturer’s product inventory at the end of time period t, L t is the manufacturer’s product shortage quantity in time period t, D t is the demand for the product in time period t, is the pricing of the product in the direct sales channel and the commissioned sales channel in time period t, m is the unit production cost of the product, h is the unit inventory cost of the product, π is the unit out-of-stock loss cost of the product, μ is the market share of the direct sales channel, θ is the fixed fee that the manufacturer needs to pay to the e-commerce platform in each time period in the commissioned sales channel, and α is the profit sharing ratio of the e-commerce platform; when μ=1 and θ=0 and α=0, there is only the direct sales channel, and when θ>0 and 0<α<1, it is a mixed channel with both direct sales and commissioned sales channels; The data from the collection module and the data acquisition module are input into the supply chain production decision model to obtain the optimal production strategy under different channels.

7. The method for generating a production strategy taking product demand into consideration according to claim 6, characterized in that: The data from the acquisition module and the data acquisition module are input into the supply chain production decision model to solve the optimal production strategy under different channels, specifically including: The supply chain production decision model is converted into the following first linear programming model: min-φ; …… I t ≥x t -D t ,t=1,2,...,T; L t ≥D t -x t ,t=1,2,...,T; x t ,I t ,L t ≥0,t=1,2,...,T. Among them, x k is the manufacturer’s product output in time period k, D k is the demand for the product in time period k; By analyzing the KKT conditions of the first linear programming model, the optimal production strategy for the manufacturer under different channels is solved according to the data of the collection module and the data acquisition module.

8. A method for generating a channel selection strategy considering product demand, characterized in that: The steps include: Collect product demand data and manufacturing cost data of manufacturers in different time periods; The supply chain production pricing decision model is constructed as follows: s.t.I t-1 +x t =(D t -L t )+I t ,t=1,2,…,T; L t ≤D t ,t=1,2,…,T; I t ·L t =0,t=1,2,…,T; In the formula, φ is the total profit, and the product production data includes I t ,L t ,D t , manufacturing cost data includes m, h, π, x t is the manufacturer's product production volume in time period t, is the generation strategy variable, T is the total number of time periods, I t is the manufacturer’s product inventory at the end of time period t, L t is the manufacturer’s product shortage quantity in time period t, D t is the demand for the product in time period t, is the pricing of the product in the direct sales channel and the commissioned sales channel in time period t, is the pricing strategy variable, m is the unit production cost of the product, h is the unit inventory cost of the product, π is the unit out-of-stock loss cost of the product, μ is the market share of the direct sales channel, θ is the fixed fee that the manufacturer needs to pay to the e-commerce platform in each time period in the commissioned sales channel, and α is the profit sharing ratio of the e-commerce platform; when θ=0 and α=0 and μ=1, there is only the direct sales channel, and the others are mixed channels where both direct sales channels and commissioned sales channels exist; Input the collected data into the supply chain production pricing decision model to solve the optimal production strategy under different channels; Based on the optimal production strategy, solve the supply chain production pricing decision model to obtain the optimal pricing strategy under different channels; According to the optimal production strategy and optimal pricing strategy under different channels, the total profit under different channels is determined, and the channel with the largest total profit is selected as the output of the channel selection strategy.

9. The method for generating a channel selection strategy considering product demand according to claim 8, characterized in that: The collected data is input into the supply chain production pricing decision model to solve the optimal production strategy under different channels, specifically including: The supply chain production pricing decision model is converted into the following first linear programming model: min-φ; …… I t ≥x t -D t ,t=1,2,...,T; L t ≥D t -x t ,t=1,2,...,T; x t ,I t ,L t ≥0,t=1,2,...,T. Among them, x k is the manufacturer’s product output in time period k, D k is the demand for the product in time period k; By analyzing the KKT conditions of the first linear programming model, the optimal production strategy for the manufacturer under different channels is solved based on the collected data.

10. The method for generating a channel selection strategy considering product demand according to claim 8, characterized in that: Based on the optimal production strategy, solving the supply chain production pricing decision model to obtain the optimal pricing strategy under different channels specifically includes: The supply chain production pricing decision model is converted into the following second mathematical programming model: min-φ′; In the formula, represents the predicted value of the product demand uncertainty coefficient, ω represents the market percentage expanded by the entrusted sales channel for the manufacturer, b represents the price elasticity coefficient of the product, and a represents the demand coefficient; In the case of a single channel, by analyzing the Lagrangian function and KKT conditions of the second mathematical programming model, the optimal pricing strategy of the manufacturer's direct sales channel is solved according to the data of the acquisition module; in the case of a mixed channel, the method of solving nonlinear constrained optimization is adopted, and the optimal pricing strategy of the manufacturer under different channels is solved according to the data of the acquisition module.

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