Supply chain production batch and carbon emission coordination and decision-making method under low-carbon policy

Abstract

The invention discloses a coordination and decision-making method for supply chain production batch and carbon emission under a low-carbon policy, and relates to the technical field of sustainable development. The method comprises the following steps: constructing a supply chain model under two low-carbon policy combination schemes, determining the constraint of a customer demand rate on the production rate of the supply chain model, constructing an expectation equation of product processing duration on the basis of product production batch, listing a carbon emission equation and a profit equation under the two low-carbon policy combination schemes, constructing a multi-objective optimization model containing constraint, and optimizing the product processing duration. Derivation is carried out by applying a convex optimization theory to find out an optimal solution under the two low-carbon policy combination schemes, different scenes are created by changing model parameters by applying a numerical simulation and sensitivity analysis method, and carbon emission and profit performance under each scene are compared and analyzed; according to the coordination and decision-making method for supply chain production batch and carbon emission under the low-carbon policy, the construction of a more efficient and more coordinated low-carbon policy framework is assisted.

Description

TECHNICAL FIELD

[0001] The application relates to the technical field of sustainable development, in particular to a coordination and decision-making method for production batch and carbon emission of a supply chain under a low-carbon policy. BACKGROUND

[0002] In order to cope with the increasingly severe threat of global warming, countries have introduced low-carbon policies to control carbon emissions in the production operation of manufacturing industry; although the effectiveness of single low-carbon policies such as total control and trading system, carbon subsidies has been analyzed by existing research, the synergistic effect of these policies is still rarely discussed by scholars.

[0003] Although previous research has discussed the synergistic optimization problem of pricing, green investment and order quantity in the green supply chain model, most researches ignore the potential influence of production batch size on carbon emissions in the product production process, and these links have a significant impact on the total emissions of manufacturers, which provides practical enlightenment for policy makers and supply chain managers, aiming to design a comprehensive strategy that can achieve both profitability and sustainability. SUMMARY

[0004] The application aims to provide a coordination and decision-making method for production batch and carbon emission of a supply chain under a low-carbon policy, which systematically analyzes the coordination mechanism between manufacturers and retailers under the framework of total control and trading mechanism and low-carbon subsidy policy, deeply analyzes the strategic decision of supply chain members by constructing a Stackelberg game model, models the production process of manufacturers by using queuing theory, reveals the influence of production process details on carbon emissions, and compares and analyzes the supply chain scenarios under different low-carbon policy combinations.

[0005] In order to achieve the above-mentioned purpose, the application provides a coordination and decision-making method for production batch and carbon emission of a supply chain under a low-carbon policy, which comprises the following steps: S1, setting production batch , unit product emission reduction , retail price as independent variables to construct a supply chain model under two low-carbon policy combination schemes; S2, defining the constraint of customer demand rate on the production rate of the supply chain model constructed in S1; S3, constructing the product processing time expectation equation of the supply chain model in S1 based on the product production batch; S4, listing the carbon emission equations under the two low-carbon policy combination schemes according to S2 and S3; S5, listing the profit equations under the two low-carbon policy combination schemes according to S2-S4; S6, constructing a multi-objective optimization model with constraints, using the theory of convex optimization to find the optimal solution of production batch size, unit product emission reduction and retail price under two low-carbon policy combination schemes; S7, using numerical simulation and sensitivity analysis method to create different scenarios by changing model parameters, and comparing and analyzing carbon emissions and profit performance under different scenarios.

[0006] Preferably, the two low-carbon policy combination schemes in S1 include the combination of total amount control and trading mechanism with green investment subsidy and product subsidy respectively; The supply chain model in S1 includes Stackelberg game model and queuing theory model; The Stackelberg game model simulates the decision-making process of manufacturers and retailers in reality, sets the manufacturer as the leader and the retailer as the follower, sets the decision variable of the manufacturer as the production batch size and the unit product emission reduction, and sets the decision variable of the retailer as the product retail price, and the objective functions of the two are their respective profit functions; The manufacturer first decides the product production batch size and unit product emission reduction to maximize its own profit, and then passes it to the retailer; The retailer makes product retail price based on the decision made by the manufacturer to maximize its own profit; The specific solving process of the model is as follows: using the reverse induction method, first solve the optimal decision of the follower under the given decision of the leader, that is, first solve the profit function of the retailer to get the optimal retail price expression about production batch size and unit product emission reduction, then substitute it into the profit function of the leader to solve the optimal solution of production batch size and unit product emission reduction, and based on this, get the optimal retail price; The queuing theory model simulates the dynamic system of the manufacturer's production process, which is used to solve the relationship between product processing time and production batch size, and the specific process is as follows: The manufacturer's production process includes four core links: order collection, material processing, equipment debugging and manufacturing; When the market demand accumulates to the standard batch size Q , the manufacturer starts the production process, in which raw materials and parts are collected and transported to the production line for debugging, then produced in batches, and finally the finished products are directly delivered to the retailer.

[0007] Preferably, in S2, to determine that the production rate of the supply chain model meets the customer demand, the following constraint conditions must be met: ; Wherein, is the production batch size, is the expected function, is the production cycle,​​​ For customer demand rate, For consumer green awareness, For emission reduction, For price sensitivity, For retail price.

[0008] The specific calculation process of S3 is as follows: ; Where, is the expected time of order collection, is the expected time of material handling, is the expected time of setting, is the expected time of queuing for processing, is the expected time of processing; The calculation process of each period expected value is as follows: ; ; ; ; ; Where, is the raw material processing time, is the machine setting time, is the production rate; Therefore, the expected value of the total production process time is: .

[0009] The carbon emissions under the two low-carbon policy combination schemes in S4 are calculated as follows: The calculation process is the same, which is composed of the emissions in the production process and the emissions in the work-in-process inventory, and the equation is: ; Where, the unit of emissions is ton, and the emissions in production and in inventory are kg, so the emission reduction multiplied by 1000 to unify the units, is the fixed carbon emissions in the production process, is the carbon emissions per unit of product in the production process, is the length of the planning time range, is the fixed carbon emissions in the work-in-process inventory, is the carbon emissions per unit of time in the work-in-process inventory.

[0010] The profit of S5 includes the retailer's profit and the manufacturer's profit under the two low-carbon policy combination schemes, and the specific content is as follows: S51, Retailer's Profit under Total Quantity Control and Trading Mechanism Combined Green Investment Subsidy Scheme Calculation Formula: ; Wherein, is the wholesale price of the product, is the operating cost of the retailer per item of goods; Manufacturer's Profit Calculation Formula: ; Wherein, is the production cost per unit, is the equipment cost, is the carbon price, is the holding cost per unit of product per unit of time, is the carbon emission cap given by the relevant department, is the green investment cost coefficient, is the green investment subsidy coefficient; S52, Retailer's Profit under Total Quantity Control and Trading Mechanism Combined Product Subsidy Scheme Calculation Formula Same as S51 Calculation Process, Manufacturer's Profit Calculation Formula: ; Wherein, is the product unit price subsidy.

[0011] Preferably, the carbon price in S51 and S52 represents the carbon emission rights trading revenue or cost of the manufacturer, wherein represents the total carbon emissions within the planning period; when > 0, it means that the manufacturer can make a profit by selling unused carbon credit; when < 0, it means that the total emissions of the manufacturer have exceeded the carbon emission cap, and additional carbon credit needs to be purchased.

[0012] Preferably, the solving process of S6 is as follows: S61, Derive the Retailer's Profit Function with Respect to the Retail Price to Obtain that the Retailer's Profit Function is a Concave Function with Respect to the Retail Price; S62, Set the first-order derivative result of S61 to 0 to obtain the equation of the retail price and substitute it into the manufacturer's profit function; S63, Derive the Manufacturer's Profit Function of S62 with Respect to the Production Batch and the Emission Reduction per Unit of Product respectively; S64, judging whether the manufacturer profit function is a concave function through the Hessian matrix, then based on the convex optimization theory, obtaining the production batch through the first derivative function of the manufacturer profit function being 0 , the optimal solution expression of the unit product emission reduction and the retail price .

[0013] Therefore, the low-carbon policy under the supply chain production batch and carbon emission coordination and decision method of the application adopts the above content, compared with the prior art, has the following beneficial effects: 1. The application constructs a double-layer model, which organically combines supply chain coordination and detailed production process planning. The supply chain coordination strategy is studied by applying the Stackelberg game model, and the queuing theory is used to capture the dynamic behavior characteristics of the production line. The model provides a new perspective for connecting operation decision and carbon emission management. 2. The application constructs two policy combination schemes, analyzes the synergistic effect of carbon trading and subsidy policy, and helps to build a more efficient and coordinated low-carbon policy framework. 3. By jointly optimizing the production batch size and green investment, the application provides a more realistic and feasible framework for achieving emission reduction through fine production planning, and opens up a new idea for the theory and practice of green supply chain management.

[0014] The technical solutions of the application will be further described in detail below with the help of the drawings and examples. DESCRIPTION OF DRAWINGS

[0015] Figure 1 is a supply chain model diagram of the low-carbon policy under the supply chain production batch and carbon emission coordination and decision method of the application; Figure 2 is a consumer green awareness influence effect diagram of case three of the low-carbon policy under the supply chain production batch and carbon emission coordination and decision method of the application; Figure 3 is a consumer green awareness influence effect diagram of case four of the low-carbon policy under the supply chain production batch and carbon emission coordination and decision method of the application; Figure 4 is a green investment subsidy and product subsidy influence comparison diagram of the low-carbon policy under the supply chain production batch and carbon emission coordination and decision method of the application. DETAILED DESCRIPTION

[0016] In the description of the present application, it should be noted that the terms "upper", "lower", "inner", "outer" and the like indicate the orientation or positional relationship shown in the drawings, or the orientation or positional relationship commonly used when the product of the present application is used, and are only for the convenience of describing the present application and simplifying the description, and do not indicate or imply that the devices or elements referred to must have a particular orientation, be constructed and operated in a particular orientation, and therefore cannot be understood as limiting the present application.

[0017] Embodiment As Figure 1 shown, a low-carbon policy supply chain production batch and carbon emission coordination and decision-making method of the present application comprises the following steps: S1, set the production batch , the unit product emission reduction , the retail price as independent variables to construct a supply chain model under two low-carbon policy combination schemes; Among them, the two low-carbon policy combination schemes include the combination of total amount control and trading mechanism with green investment subsidy and product subsidy respectively; The supply chain model includes Stackelberg game model and queuing theory model; The Stackelberg game model simulates the decision-making process of manufacturers and retailers in reality, sets the manufacturer as the leader and the retailer as the follower, sets the production batch and the unit product emission reduction as the decision variables of the manufacturer, and sets the product retail price as the decision variable of the retailer, and the objective functions of the two are their respective profit functions; the manufacturer first decides the product production batch and the unit product emission reduction with the goal of maximizing its own profit, and passes it to the retailer; the retailer formulates the product retail price based on the decision made by the manufacturer to maximize its own profit; the specific solving process of the model is: using the backward induction method, first solve the optimal decision of the follower under the given leader decision, that is, first solve the profit function of the retailer to obtain the optimal retail price expression about the production batch and the unit product emission reduction, then substitute it into the profit function of the leader to solve the optimal solution of the production batch and the unit product emission reduction, and based on this, obtain the optimal retail price; The queuing theory model simulates the dynamic system of the manufacturer's production process, which is used to solve the relationship between product processing time and production batch, and the specific process is as follows: Suppose that the production process of the manufacturer includes four core links: order collection, material processing, equipment debugging and manufacturing; when the market demand accumulates to the standard batch Q , the manufacturer starts the production process, in which raw materials and parts are collected and transported to the production line for debugging, then produced in batches, and finally the finished products are directly delivered to the retailer; S2, the rate of customer demand constraints on the production rate of S1 constructed supply chain model; The production rate of the supply chain model meets the customer demand, must meet the following constraints: ; Where, is the production batch size, is the expected function, is the production cycle, is the customer demand rate, is the consumer green consciousness, is the emission reduction, is the price sensitivity, is the retail price; S3, based on the product production batch size to build S1 in the supply chain model of the product processing duration expectation equation; The specific calculation process is as follows: ; Where, is the order collection expected time, is the material handling expected time, is the set expected time, is the queuing waiting processing expected time, is the processing expected time; The expected value of each period is calculated as follows: ; ; ; ; ; Where, is the raw material processing time, is the machine setting time, is the production rate; Therefore, the expected value of the total production process time is: ; S4, according to S2 and S3 list two low carbon policy combination scheme under the carbon emission equation; Where the carbon emissions of the two low carbon policy combination schemes The calculation process is the same, both of which are composed of the emission amount in the production process and the emission amount of the work-in-process inventory after green investment, and the equation is: ; Where, the unit of emission is ton, and the unit of emission in production and inventory is kg, so the emission reduction amount The front times 1000 to unify the unit, The fixed carbon emissions in the production process, The variable carbon emissions in the production process per unit product, The length of the planning time range, The fixed carbon emissions in the workload list, The variable carbon emissions per piece of inventory per unit time; S5, according to S2-S4, list the profit equations under two low-carbon policy combination schemes; The profit includes the retailer's profit and the manufacturer's profit under two low-carbon policy combination schemes, as follows: S51, the retailer's profit under the total amount control and trading mechanism combined with green investment subsidy scheme The calculation formula is: ; Where, The wholesale price of the product, The operating cost of each item for the retailer; The manufacturer's profit The calculation formula is: ; Where, The production cost per unit, The equipment cost, The carbon price, The holding cost per unit of product per unit time, Carbon sequestration, The green investment cost coefficient, The green investment subsidy coefficient; S52, the retailer's profit under the total amount control and trading mechanism combined with product subsidy scheme The calculation formula is the same as S51 The calculation process, the manufacturer's profit The calculation formula is as follows: ; Where, The product unit price subsidy; The carbon price Indicates the manufacturer's carbon emissions trading revenue or cost, where Represents the total carbon emissions during the planning period; when >0, it means that the manufacturer can make a profit by selling unused carbon credits; when <0, it means that the manufacturer's total emissions have exceeded the carbon emissions cap and needs to purchase additional carbon credits; S6, construct a multi-objective optimization model with constraints, and find the optimal solution of production batch , unit product emission reduction , retail price under two low-carbon policy combination schemes by using the theory of convex optimization to derive; S61, derive the retail price by the retailer's profit function to obtain the concave function relationship between the retailer's profit function and the retail price; S62, set the first-order derivative result of S61 to 0 to obtain the equation of the retail price and substitute it into the manufacturer's profit function; S63, take the derivative of the manufacturer's profit function in S62 with respect to production batch and unit product emission reduction ; S64, judge whether the manufacturer's profit function is a concave function by Hessian matrix, and then based on the theory of convex optimization, obtain the optimal solution expression of production batch , unit product emission reduction and retail price by setting the first-order derivative function of the manufacturer's profit function to 0; The solving process of the combination scheme of total quantity control and trading mechanism combined with green investment subsidy: By deriving the derivative of the retailer's profit function, we can get: ; Therefore, the retailer's profit function is a concave function of the retail price , and by setting , we can get: ; Substitute the above retail price equation into the manufacturer's profit function to get: ; By the derivative of , we can get: ; The Hessian matrix is: ; When , we can get: ; Therefore, has joint concavity on and , and by setting the first-order derivative function to zero, i.e. , the emission reduction The optimal production batch size can be expressed as: ; Substitute the equation of the optimal emission reduction amount into the objective function, and set the first-order derivative of the objective function with respect to the optimal production batch size to zero, i.e., set Q , we can obtain the optimal production batch size solution , and its specific value can be solved by the following equation: ; where ; The constraint condition is: ; At this time, the optimal emission reduction amount and the optimal retail price are respectively: ; The solving process under the combination scheme of total quantity control and transaction mechanism combined with product subsidy: The derivation process of the retailer's profit function is consistent with that under the combination scheme of total quantity control and transaction mechanism combined with green investment subsidy; Substitute the above retail price into the manufacturer's profit function, we can get: ; Take the derivative of , we can get: ; The Hessian matrix is: ; When , we can deduce that: ; Therefore, has joint concavity on and . By setting the first-order derivative to zero, i.e., , the emission reduction amount can be expressed as: ; Substitute the equation of the emission reduction amount into , and set the first-order derivative of the objective function with respect to the optimal production batch size to zero, i.e., set Q , we can obtain the optimal production batch size solution , and its specific value can be solved by the following equation: ;​​​​ ; where, ; The constraints are as follows: ; The optimal emission reduction amount and the optimal retail price are respectively: ; S7, numerical simulation and sensitivity analysis method is used to create different scenarios by changing the model parameters, and to compare and analyze the carbon emissions and profit performance under each scenario; The data collected from a machine tool enterprise in China are as follows: the original market demand rate is = 2, the consumer green sensitivity coefficient is assumed to be = 0.01, the price sensitivity coefficient is = 0.002, the material handling time is = 0.05 hours, the equipment preparation time is = 0.05 hours, the production efficiency is = 15 hours, the monetary unit is RMB, the equipment preparation cost is = 1000 yuan, the work-in-process holding cost is = 5 yuan, the production cost is = 50 yuan, the product wholesale price is = 350 yuan, the retailer operating cost is = 20 yuan, the green investment cost coefficient is set to = 60, the green investment subsidy coefficient is = 10, the product subsidy coefficient is = 20 yuan / piece, according to the carbon emission trading data of China provided by the International Carbon Exchange Organization (CUFE) in 2019, the average carbon price is set to 23 yuan / ton, the carbon emission cap is set to 30 tons, the fixed carbon emission of production process is = 10 tons / year, the fixed carbon emission of work-in-process inventory is = 8 tons / year, and 10 kg of carbon emission is consumed to produce one product, while the product emits 0.5 kg of carbon per hour during the inventory stage. In order to calculate the profit of each supply chain participant, an annual production plan is developed, assuming that the manufacturer works 8 hours a day and 20 x 12 = 240 days a year, so the total working hours in a year is 1920 hours; The numerical simulation analysis of four cases is carried out. In the first case, the manufacturer does not make green investment and directly purchases carbon credits from the carbon market; in the second case, the manufacturer makes green investment and participates in carbon credit trading; in the third case, the subsidy provider provides green investment subsidies to the manufacturer; and in the fourth case, the subsidy provider provides product subsidies to the manufacturer. The key indicators of the above four cases are shown in Table 1. When the manufacturer does not make green investment, its total emissions are higher and it needs to purchase additional carbon credits. After implementing green investment, the manufacturer can not only obtain higher profits but also achieve less total emissions. The application of the subsidy policy can further improve the profit level and carbon emission reduction effect. Under the current subsidy coefficient setting, investment subsidies will lead to the increase of batch size, retail price and emission reduction level. The production emissions and work-in-process inventory under investment subsidies are higher than those under product subsidies, but investment subsidies can help the manufacturer achieve greater emission reduction, so the total emissions are lower. The manufacturer's profit is higher under product subsidies, while the retailer's profit is higher under investment subsidies. Investment subsidies can help the manufacturer sell more carbon credits by improving the emission reduction effect, and the relevant departments spend less on investment subsidies than on product subsidies within a year. Therefore, in this case, the relevant departments should choose to apply the green investment subsidy policy.

[0018] Table 1 Supply chain performance under four cases

[0019] Consumer environmental awareness is a key factor in the green market. As shown in Figures 2-3 , the impact of consumer environmental awareness on the models of case 3 and case 4 is shown. It can be observed that the improvement of consumer environmental awareness is always beneficial to the development of the supply chain under the two low-carbon policy scenarios. When consumer environmental awareness is high, the manufacturer can choose a larger production batch size, and the retailer can set a higher retail price. When consumer environmental awareness is low, the manufacturer's emission reduction is smaller, so it needs to purchase more carbon credit quotas. The improvement of consumer environmental awareness encourages the manufacturer to increase environmental protection efforts, so that its total emissions are lower than the carbon emission cap, thereby selling more carbon credit quotas. More active environmental protection actions will attract more green consumers, thereby increasing the demand rate. Although larger production batch sizes will prolong the production cycle, the improvement of the demand rate shortens the order collection time, so that the delivery cycle can be shortened under high consumer environmental awareness. By comparing Figure 2 and Figure 3 , it is found that under the green investment subsidy policy, the improvement of consumer environmental awareness not only significantly improves the manufacturer's profit, but also helps it achieve a larger emission reduction target. As shown in Figure 4As shown, the influence of the subsidy coefficient on the emission reduction effect is shown, when the subsidy coefficient is 0, it means that no subsidy is provided, it can be seen that the implementation of the two subsidy policies can encourage manufacturers to achieve higher emission reduction targets, and at the same time improve the economic benefits of both parties, the implementation of the subsidy policy helps the manufacturer to achieve more significant emission reduction effect, so as to attract more green consumers, the growth of product demand will also prompt the retailer to increase the retail price, within a year cycle, the investment subsidy can achieve greater emission reduction effect with less subsidy expenditure compared with the product subsidy, in addition, increasing the investment subsidy ratio is an effective method to encourage manufacturers to achieve more carbon emission reduction, but the higher the subsidy ratio, the greater the financial expenditure that the relevant department needs to bear, the relevant department should find a balance point between the carbon emission reduction effect and the financial expenditure.

[0020] Therefore, the low-carbon policy under the supply chain production batch and carbon emission coordination and decision method of the above content is adopted, under the framework of the total amount control and transaction mechanism and the low-carbon subsidy policy, the coordination mechanism between the manufacturer and the retailer is analyzed, the Stackelberg game model is constructed to deeply analyze the strategic decision of the supply chain members, the queuing theory is used to model the production process of the manufacturer, the influence of the production process details on the carbon emission is revealed, and the supply chain scenarios are compared and analyzed under different low-carbon policy combinations.

[0021] Finally, it should be noted that: the above examples are only used to illustrate the technical solutions of the present application but not to limit it, although the present application has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that: the technical solutions of the present application can still be modified or replaced by equivalents, and these modifications or equivalent replacements cannot make the modified technical solutions deviate from the spirit and scope of the technical solutions of the present application.

Claims

1. A method for coordination and decision of production lot and carbon emission of supply chain under low-carbon policy, characterized in that, It comprises the following steps: S1, production batch , unit product emission reduction , retail price The supply chain model under two low-carbon policy combination schemes is constructed with independent variables; S2, determine the customer demand rate constraint on the production rate of the supply chain model constructed in S1; S3, based on the product production batch, construct the product processing time expectation equation of the supply chain model in S1; S4, according to S2 and S3, list the carbon emission equations under two low-carbon policy combination schemes; S5, according to S2-S4, list the profit equations under two low-carbon policy combination schemes; S6, Construct a multi-objective optimization model with constraints, use the theory of convex optimization to find the optimal solution of production batch size, unit product emission reduction, retail price under two low-carbon policy combination schemes ​​​ S7, use numerical simulation and sensitivity analysis method to create different scenarios by changing model parameters, and compare and analyze the carbon emissions and profits under each scenario.

2. The low-carbon policy supply chain production batch and carbon emission coordination and decision method according to claim 1, wherein: The two low-carbon policy combination schemes in S1 include total amount control and transaction mechanism combined with green investment subsidy and product subsidy respectively; The supply chain model in S1 includes Stackelberg game model and queuing theory model; The Stackelberg game model simulates the decision-making process of manufacturers and retailers in reality, sets the manufacturer as the leader and the retailer as the follower, sets the production batch and unit product emission reduction of the manufacturer as the decision variable, sets the product retail price of the retailer as the decision variable, and sets the profit function of each as the objective function. The manufacturer first decides the product production batch and unit product emission reduction to maximize its own profit, and then transmits it to the retailer. The retailer makes product retail price based on the decision made by the manufacturer to maximize its own profit. The specific solving process of the model is as follows: using the backward induction method, first solve the optimal decision of the follower under the given decision of the leader, that is, solve the retailer's profit function to get the optimal retail price expression about production batch and unit product emission reduction, then substitute it into the leader's profit function to solve the optimal solution of production batch and unit product emission reduction, and based on this, get the optimal retail price; The queuing theory model simulates the dynamic system of the manufacturer's production process, providing a model basis for the relationship between product processing time and production batch in subsequent solving. The specific process is as follows: Suppose the manufacturer's production process includes four core links: order collection, material processing, equipment debugging and manufacturing; when the market demand accumulates to the standard batch Q , the manufacturer starts the production process, in which raw materials and parts are collected and transported to the production line for debugging, then produced in batches, and finally the finished products are directly delivered to retailers.

3. The low-carbon policy supply chain production batch and carbon emission coordination and decision method according to claim 2, wherein: In S2, to determine that the production rate of the supply chain model meets the customer demand, the following constraint conditions must be met: ； wherein, is the production batch, is the desired function, is the production cycle, is the customer demand rate, is the consumer green consciousness, is the emission reduction, is the price sensitivity, is the retail price.

4. The low-carbon policy supply chain production batch and carbon emission coordination and decision method according to claim 3, wherein: The specific calculation process of S3 is as follows: ； wherein, is an order collection expected time, is a material handling expected time, is a setup expected time, is a queue wait for processing expected time, is a processing expected time; The expected value of each period is calculated as follows: ； ； ； ； ； wherein, is raw material handling time, is machine setup time, is production rate; Therefore, the expected value of the total production process time is: 。 5. The low-carbon policy supply chain production batch and carbon emission coordination and decision method according to claim 4, wherein: Carbon emissions under the two low-carbon policy combination schemes in S4 The calculation process is the same, and is composed of the sum of emissions in the production process and emissions in the green investment after the work-in-process inventory. The equation is: ； where the unit of emission is ton, and the unit of emission in production and inventory is kg, so the reduction of emission is multiplied by 1000 to unify the unit, is the emission of fixed carbon in the production process, is the emission of carbon per unit product in the production process, is the length of the planning time horizon, is the emission of fixed carbon in the work-in-process inventory, is the emission of carbon per unit of work-in-process inventory per unit time.

6. The low-carbon policy supply chain production batch and carbon emission coordination and decision method according to claim 5, wherein: The profit of S5 includes the retailer's profit and the manufacturer's profit under two low-carbon policy combination schemes, and the specific content is as follows: S51, Retailer's Profit under Green Investment Subsidy Scheme with Total Quantity Control and Trading Mechanism Calculation Formula: ； wherein, is the wholesale price for the product, is the retailer's per item operating cost; manufacturer's profit Calculation formula: ； wherein, is the production cost per piece, is the equipment cost, is the carbon price, is the holding cost per piece per unit of time, is the upper limit of carbon emissions given by the relevant department, is the green investment cost coefficient, is the green investment subsidy coefficient; S52, Retailer Profit under Total Quantity Control and Trade Mechanism Combined with Product Subsidy Scheme The calculation formula is the same as S51 The calculation process is as follows: The calculation formula is as follows: ； wherein, is the product unit price subsidy.

7. The method of claim 6, wherein the method further comprises: Carbon price in S51 and S52 represents the manufacturer's carbon emission rights trading revenue or cost, wherein represents the total carbon emissions in the planning period; when > 0, it means that the manufacturer can make a profit by selling unused carbon credits; when < 0, it means that the total emissions of the manufacturer have exceeded the carbon emission cap, and additional carbon credits need to be purchased.

8. The method of claim 7, wherein the method further comprises: The solving process of S6 is as follows: S61, the retailer's profit function is concave with the retail price by deriving the retailer's profit function with respect to the retail price through the retailer's profit function; S62, make the first derivative result of S61 to 0, get the retail price of the equation and substitute into the manufacturer profit function; S63, the manufacturer's profit function of S62 is differentiated with respect to production batch size and unit product abatement respectively; S64, judge whether the manufacturer profit function is a concave function by Hessian matrix, then based on convex optimization theory, get the optimal solution expression of production batch, unit product emission reduction and retail price by the first derivative of the manufacturer profit function is 0 ​​​

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