Auxiliary task-based constrained multi-objective industrial value chain optimization method and system

Abstract

The invention discloses a constrained multi-target industrial value chain optimization method and system based on an auxiliary task. The method comprises the following steps: constructing an industrial value chain; according to the method, optimization objective functions of a plurality of carbon constraint industry value chains are constructed from an economic dimension, an economic cost dimension, an energy efficiency and emission reduction dimension, an environmental protection industry chain development dimension, a public environmental protection guidance selection dimension, a communication and information transparency dimension and a recycling and value circulation dimension; constructing constraint conditions of a carbon constraint industrial value chain from a carbon emission dimension, and generating an industrial value chain model of a full life cycle value; and solving a full life cycle value model based on a multi-constraint multi-objective optimization algorithm, constructing an auxiliary task to continuously provide a complementary evolution direction for a main task, and constructing an optimal industrial value chain model.

Description

Technical Field

[0001] The present invention relates to the field of carbon constraints, and specifically relates to an optimization method and system for a constrained multi-objective industrial value chain based on auxiliary tasks. Background Art

[0002] In the manufacturing industry, the overall industrial value chain usually consists of links such as raw material procurement, R & D design, production manufacturing, sales and service. The coordination among the above links is an important factor related to the development of the industrial value chain. In the industrial value chain, the chain leader enterprise is in the core position, usually served by the manufacturing enterprises on the chain. In order to achieve the goal of carbon constraints, the chain leader enterprise needs to closely cooperate with the upstream and downstream enterprises of the industrial value chain. While ensuring product quality, jointly reduce carbon emissions and enhance the competitiveness of the entire industrial value chain. However, the industrial value chain in the whole life cycle includes stages such as product sales, use and recycling. Only considering the profit of the chain leader enterprise may lead to dissatisfaction among other enterprises on the chain, affect the consumption experience of the customer group, increase the risk of industrial value chain breakage, reduce the value added of the entire industrial value chain, and is not conducive to the development of the industrial value chain in the whole life cycle.

[0003] In the existing research process of maximizing the value added of the industrial value chain under carbon constraints, there are disadvantages such as inconsistent evaluation indicators for the industrial value chain in the whole life cycle and poor versatility. Summary of the Invention

[0004] To achieve the above object and other related objects, the present invention discloses an optimization method for a constrained multi-objective industrial value chain based on auxiliary tasks, including:

[0005] Construct an industrial value chain;

[0006] Construct multiple optimization objective functions for the carbon-constrained industrial value chain from the dimensions of economy, economic cost, energy efficiency and emission reduction, development of the environmental protection industrial chain, guiding public environmental protection choices, communication and information transparency, and recycling and value circulation. Construct the constraint conditions for the carbon-constrained industrial value chain from the carbon emission dimension, and generate an industrial value chain model of the whole life cycle value;

[0007] Based on the multi-constraint multi-objective optimization algorithm, solve the whole life cycle value model, construct an evolutionary direction in which the auxiliary task continuously provides supplements for the main task, and construct an optimal industrial value chain model.

[0008] Further, the construction of the constraint conditions for the carbon-constrained industrial value chain from the carbon emission dimension includes:

[0009] The carbon emission is:

[0010]

[0011] Among them, CPF is the carbon emission; NE a is the consumption of the a-th type of energy; NHV a is the average low calorific value of the fuel; ER a is the carbon content per unit calorific value of the fuel; O a is the oxygen content; 44 / 12 is the conversion coefficient for converting C to CO2;

[0012] The carbon emission intensity is:

[0013]

[0014] Among them, CFQ is the carbon emission intensity, and QCV is the added value of the enterprise;

[0015] Among them, the processing cost is:

[0016]

[0017] Among them, Y i represents the processing cost of enterprise i; Y ij represents the cost of the j-th type of energy of enterprise i; V j represents the innovation factor data of various types of energy, and the energy types include coal, natural gas, non-fossil energy, and green energy; CPF j represents the carbon emissions corresponding to various types of energy; C ij represents the price data of various types of energy of enterprise i; X i represents the carbon reduction target of enterprise i.

[0018] Furthermore, the optimization objective function for constructing the carbon-constrained industrial value chain from the economic dimension includes:

[0019] The economic optimization objective is the profit function of the products in the industrial value chain, including the product selling price PI, the procurement cost BK, the manufacturing cost BH, the value creation activity cost BC, and the loss cost BY. The calculation formula for the industrial value chain profit LR is shown as follows:

[0020] LR = PI - BK - BH - BC - BY

[0021]

[0022] Among them, Lj n is the cost for the parts supplier to purchase raw materials, and ZY m is the cost for the manufacturer to purchase parts; YL n is the cost in the manufacturing process of the raw material supplier, and SF m is the cost in the manufacturing and processing process of the parts supplier; KZ n and KZ m and KP are the value creation costs of the raw material supplier, the parts supplier, and the manufacturer respectively; KS n, KS m 、KH are the loss costs in the operation processes of raw material suppliers, parts suppliers, and manufacturers respectively.

[0023] Furthermore, the optimization objective function for constructing the carbon-constrained industrial value chain from the economic cost dimension includes:

[0024] min ECOF = GD + TC + CSB - FSC

[0025] GD is the fixed cost, TC is the logistics cost, CSB is the facility cost, and FSC is the loss cost.

[0026] Furthermore, the optimization objective function for constructing the carbon-constrained industrial value chain from the energy efficiency and emission reduction dimension includes:

[0027] max CRTEROF = CR + CER

[0028] where CR is the enterprise rectification parameter and CER is the enterprise emission reduction parameter.

[0029] Furthermore, the optimization objective function for constructing the carbon-constrained industrial value chain from the development dimension of the environmental protection industrial chain includes:

[0030] min GSCOF = WQE + BCE + FCE + CPHE

[0031] where WQE is the logistics carbon emission, BCE is the construction carbon emission, FCE is the functional personnel carbon emission, and CPHE is the harmful substance emission.

[0032] Furthermore, the optimization objective function for constructing the carbon-constrained industrial value chain from the dimension of guiding the public's environmental protection choices includes:

[0033] max PPGCOF = GEP + LPE

[0034] where GEP is the green facility performance parameter and LPE is the parameter of the facility guiding the public's environmental protection performance in the industrial value chain.

[0035] Furthermore, the optimization objective function for constructing the carbon-constrained industrial value chain from the dimension of communication and information transparency includes:

[0036] min SCCTOF = CCP + DIP

[0037] where CCP is the parameter of public accountability and communication, and DIP is the information of the industrial value chain that has not been publicly disclosed.

[0038] Furthermore, the optimization objective function for constructing the carbon-constrained industrial value chain from the dimension of communication and information transparency includes:

[0039] max RVCTOF = BLP + DGP + ZSL + CBS

[0040] Among them, BLP is the type of components participating in recycling, DGP is the resource utilization rate, ZSL is the carbon emission conversion rate, and CBS is the number of components participating in closed-loop production.

[0041] On the other hand, the present invention also provides a constraint multi-objective industrial value chain optimization system based on auxiliary tasks, including:

[0042] An industrial value chain construction module for constructing an industrial value chain;

[0043] A model construction module for constructing optimization objective functions of multiple carbon-constrained industrial value chains from the dimensions of economy, economic cost, energy efficiency and emission reduction, development of environmental protection industrial chain, guiding public environmental protection choices, communication and information transparency, and recycling and value circulation, and constructing constraint conditions of the carbon-constrained industrial value chain from the carbon emission dimension to generate an industrial value chain model of the full life cycle value;

[0044] A model solving module for solving the full life cycle value model based on the multi-constraint multi-objective optimization algorithm, constructing an evolutionary direction in which the auxiliary task continuously provides supplements for the main task, and constructing an optimal industrial value chain model.

[0045] By adopting the above technical solutions, first, an industrial value chain is constructed, and then optimization objective functions of multiple carbon-constrained industrial value chains are constructed from the dimensions of economy, economic cost, energy efficiency and emission reduction, development of environmental protection industrial chain, guiding public environmental protection choices, communication and information transparency, and recycling and value circulation, and constraint conditions of the carbon-constrained industrial value chain are constructed from the carbon emission dimension to generate an industrial value chain model of the full life cycle value, and then it is solved, so as to quantify and unify the evaluation indexes of the full life cycle industrial value chain. Brief Description of the Drawings

[0046] Combined with the drawings and referring to the following detailed description, the above and other features, advantages and aspects of the embodiments of the present disclosure will become more obvious. The drawings are used to better understand the solution and do not limit the present disclosure. In the drawings, the same or similar reference numerals represent the same or similar elements, where:

[0047] Figure 1 It is a flowchart of a constraint multi-objective industrial value chain optimization method based on auxiliary tasks. Detailed Embodiments

[0048] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative efforts belong to the protection scope of the present invention.

[0049] Referring to Figure 1 , the embodiments of the present invention provide a method for optimizing a constrained multi-objective industrial value chain based on an auxiliary task, including the following steps:

[0050] S1: Construct an industrial value chain.

[0051] Specifically, the industrial value chain includes multiple suppliers, parts manufacturers, and manufacturers. The leading enterprises in the industrial value chain are mainly located downstream of the chain, close to the consumer market, and most of them are manufacturer enterprises responsible for the production of end products. According to the actual situation of the industrial value chain in this chapter, the industrial value chain of the present invention is an industrial value chain composed of three levels: "supplier - parts manufacturer - manufacturer (chain leader)". In this industrial value chain, the supplier supplies the raw materials required for producing parts to the parts manufacturer, such as ore, metal, rubber, etc.; the parts manufacturer has the function of processing raw materials and producing product parts; as the last link in product production, the manufacturer mainly provides functions such as assembly, manufacturing, and delivery.

[0052] Regarding the above, the specific numbers of suppliers, parts manufacturers, and manufacturers are set by those skilled in the art according to the actual situation and will not be elaborated here.

[0053] S2: Construct multiple optimization objective functions for carbon-constrained industrial value chains from the dimensions of economy, economic cost, energy efficiency and emission reduction, development of environmental protection industrial chains, guiding public environmental protection choices, communication and information transparency, and recycling and value circulation. Construct the constraint conditions for the carbon-constrained industrial value chain from the carbon emission dimension to generate an industrial value chain model of the full life cycle value.

[0054] Among them:

[0055] (U)

[0056] (L)

[0057] Among them, (U) is the optimization objective equation set, (L) is the constraint objective equation set, f1 is the objective function of the optimization algorithm, x is the decision variable, and W is the constraint condition of the decision variable; f2 is the objective function in the constraint, y is the decision variable, and w is the constraint condition of the decision variable. The carbon emission constraint function is as follows:

[0058]

[0059] Among them, CZ represents the total carbon footprint of the product, CZ(i) represents the carbon footprint contribution value of each enterprise, and CZ MAX represents the carbon footprint threshold of the product.

[0060] The constraint conditions for constructing the carbon-constrained industrial value chain from the carbon emission dimension include:

[0061] The carbon emission is:

[0062]

[0063] Among them, CPF is the carbon emission; NE a is the consumption of the a-th kind of energy; NHV a is the average low calorific value of the fuel; ER a is the carbon content per unit calorific value of the fuel; O a is the oxygen content; 44 / 12 is the conversion coefficient for converting C to CO2;

[0064] The carbon emission intensity is:

[0065]

[0066] Among them, CFQ is the carbon emission intensity, and QCV is the added value of the enterprise;

[0067] Among them, the processing cost is:

[0068]

[0069] Among them, Y i represents the processing cost of enterprise i; Y ij represents the cost of the j-th type of energy of enterprise i; V j represents the innovation factor data of various types of energy, and the energy types include coal, natural gas, non-fossil energy, and green energy; CPF j represents the carbon emissions corresponding to various types of energy; C ij represents the price data of various types of energy of enterprise i; X i represents the carbon reduction target of enterprise i.

[0070] The optimization objective function for constructing the carbon-constrained industrial value chain from the economic dimension includes:

[0071] The economic optimization objective is the profit function of the industrial value chain product, including the product selling price PI, the procurement cost BK, the manufacturing cost BH, the value creation activity cost BC, and the loss cost BY. The calculation formula for the industrial value chain profit LR is shown as follows:

[0072] LR = PI - BK - BH - BC - BY

[0073]

[0074] Among them, Lj n is the cost for parts suppliers to purchase raw materials, and ZY m is the cost for manufacturers to purchase components; YL n is the cost of the raw material supplier in the manufacturing process, and SF m is the cost of the parts supplier in the manufacturing and processing process; KZ n and KZ m and KP are the value creation costs of the raw material supplier, parts supplier, and manufacturer respectively; KS n and KS m and KH are the loss costs of the raw material supplier, parts supplier, and manufacturer during the operation process respectively.

[0075] The optimization objective function for constructing the carbon-constrained industrial value chain from the economic cost dimension includes:

[0076] mnECOF = GD + TC + CSB - FSC

[0077] where GD is the fixed cost, TC is the logistics cost, CSB is the facility cost, and FSC is the loss cost.

[0078] The optimization objective function for constructing the carbon-constrained industrial value chain from the energy efficiency and emission reduction dimension includes:

[0079] max CRTEROF = CR + CER

[0080] where CR is the enterprise rectification parameter and CER is the enterprise emission reduction parameter.

[0081] The optimization objective function for constructing the carbon-constrained industrial value chain from the environmental protection industrial chain development dimension includes:

[0082] min GSCOF = WQE + BCE + FCE + CPHE

[0083] where WQE is the logistics carbon emission, BCE is the construction carbon emission, FCE is the functional personnel carbon emission, and CPHE is the harmful substance emission.

[0084] The optimization objective function for constructing the carbon-constrained industrial value chain from the dimension of guiding public environmental protection choices includes:

[0085] max PPGCOF = GEP + LPE

[0086] where GEP is the green facility performance parameter and LPE is the facility's environmental protection performance parameter for guiding the public industrial value chain.

[0087] The optimization objective function for constructing the carbon-constrained industrial value chain from the dimensions of communication and information transparency includes:

[0088] mnSCCTOF = CCP + DIP

[0089] Where CCP is the public accountability and communication parameter, and DIP is the information of the industrial value chain that has not been publicly disclosed.

[0090] The optimization objective function for constructing the carbon-constrained industrial value chain from the dimensions of communication and information transparency includes:

[0091] maxRVCTOF = BLP + DGP + ZSL + CBS

[0092] Where BLP is the type of components participating in recycling, DGP is the resource utilization rate, ZSL is the carbon emission conversion rate, and CBS is the number of components participating in closed-loop production.

[0093] S3: Solve the full-life cycle value model based on the multi-constraint multi-objective optimization algorithm, construct an evolutionary direction in which the auxiliary task continuously provides supplements for the main task, and construct an optimal industrial value chain model.

[0094] Specifically including:

[0095] The auxiliary task can be described as follows:

[0096] min f(x) = (f1(x), f2(x), …, f M (x))

[0097] s.t.G(x) ≤ ∈ T

[0098] Where T is the current generation, and T represents the constraint boundary value of the T-th generation.

[0099]

[0100] Where MaxT is the maximum generation, and pp is the parameter controlling ∈ T For the parameter of the descent rate, set to 0.5, and ∈0 is the initial constraint violation degree value, which is equal to the maximum G value of the initial main task population and the auxiliary population.

[0101] The auxiliary task and the main task have the same objective function. However, different from the main task, the constraint function of the auxiliary task is dynamically changing. In addition, the constraint boundary ∈ T Gradually decreases to drive the population into the feasible region.

[0102] As mentioned above, when solving the model, a certain optimization objective function can be solved according to actual needs, which will not be elaborated here.

[0103] An embodiment of the present invention discloses a method for optimizing a constrained multi-objective industrial value chain based on an auxiliary task. First, an industrial value chain is constructed, and then multiple optimization objective functions of the carbon-constrained industrial value chain are constructed from the economic dimension, economic cost dimension, energy efficiency and emission reduction dimension, environmental protection industrial chain development dimension, guiding public environmental protection choices dimension, communication and information transparency dimension, and recycling and value circulation dimension. The constraint conditions of the carbon-constrained industrial value chain are constructed from the carbon emission dimension, and an industrial value chain model with full life cycle value is generated. Then, it is solved to quantify and unify the evaluation indexes of the full life cycle industrial value chain.

[0104] An embodiment of the present invention also provides a system, including:

[0105] An industrial value chain construction module, configured to construct an industrial value chain;

[0106] A model construction module, configured to construct multiple optimization objective functions of the carbon-constrained industrial value chain from the economic dimension, economic cost dimension, energy efficiency and emission reduction dimension, environmental protection industrial chain development dimension, guiding public environmental protection choices dimension, communication and information transparency dimension, and recycling and value circulation dimension, construct the constraint conditions of the carbon-constrained industrial value chain from the carbon emission dimension, and generate an industrial value chain model with full life cycle value;

[0107] A model solving module, configured to solve the full life cycle value model based on a multi-constraint multi-objective optimization algorithm, construct an evolutionary direction in which the auxiliary task continuously provides supplementation for the main task, and construct an optimal industrial value chain model.

[0108] Those skilled in the art of the present technology can understand that, unless otherwise defined, all terms (including technical terms and scientific terms) used here have the same meaning as the general understanding of those of ordinary skill in the art in the field to which the present invention belongs. It should also be understood that terms such as those defined in a general dictionary should be understood to have a meaning consistent with the meaning in the context of the prior art, and will not be interpreted with an idealized or overly formal meaning unless specifically defined.

[0109] For the method embodiment, for the sake of simple description, it is all expressed as a series of action combinations. However, those skilled in the art should know that the embodiments of the present invention are not limited by the described action sequence, because according to the embodiments of the present invention, certain steps can be performed in other sequences or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all preferred embodiments, and the actions involved are not necessarily essential for the embodiments of the present invention.

[0110] From the description of the above embodiments, those skilled in the art can clearly understand that this application can be implemented by means of software plus a necessary general hardware platform. Based on such an understanding, the technical solution of this application, in essence, or the part that makes contributions to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions for causing a computer device (which can be a personal computer, server, or network device, etc.) to execute the methods described in various embodiments or some parts of the embodiments of this application.

[0111] Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements on some or all of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for optimizing a constrained multi-objective industrial value chain based on an auxiliary task, characterized in that, Including: Construct an industrial value chain; Construct an optimization objective function for multiple carbon-constrained industrial value chains from the dimensions of economy, economic cost, energy efficiency and emission reduction, development of the environmental protection industrial chain, guiding the public's environmental protection choices, communication and information transparency, and recycling and value circulation. Construct the constraint conditions of the carbon-constrained industrial value chain from the carbon emission dimension to generate an industrial value chain model of the full life cycle value; Solve the full life cycle value model based on the multi-constraint multi-objective optimization algorithm, construct an evolutionary direction in which the auxiliary tasks continuously provide supplements for the main task, and construct an optimal industrial value chain model.

2. The method according to claim 1, wherein The constraint conditions for constructing the carbon-constrained industrial value chain from the carbon emission dimension include: The carbon emission amount is: Among them, CPF is the carbon emission; NE a is the consumption of the a-th type of energy; NHV a is the average low calorific value of the fuel; ER a is the carbon content per unit calorific value of the fuel; O a is the oxygen content; 44 / 12 is the conversion coefficient for converting C to CO2; The carbon emission intensity is: Among them, CFQ is the carbon emission intensity, and QCV is the added value of the enterprise; Among them, the processing cost is: Among them, Y i represents the processing cost of enterprise i; Y ij represents the cost of energy type j of enterprise i; V j represents the innovation factor data of various energy sources, and the energy types include coal, natural gas, non-fossil energy, and green energy; CPF j represents the carbon emissions corresponding to various energy sources; C ij represents the price data of various energy sources of enterprise i; X i represents the carbon emission reduction target of enterprise i.

3. The method according to claim 1, characterized in that, The optimization objective function for constructing the carbon-constrained industrial value chain from the economic dimension includes: The economic optimization objective is the profit function of the products in the industrial value chain, including the product selling price PI, the procurement cost BK, the manufacturing cost BH, the value creation activity cost BC, and the loss cost BY. The calculation formula of the industrial value chain profit LR is shown as follows: LR = PI - BK - BH - BC - BY Among them, Lj n is the cost for the parts supplier to purchase raw materials, and ZY m is the cost for the manufacturer to purchase components; YL n is the cost in the manufacturing process of the raw material supplier, and SF m is the cost in the manufacturing and processing process of the parts supplier; KZ n , KZ m , and KP are the value creation costs of the raw material supplier, parts supplier, and manufacturer respectively; KS n , KS m , and KH are the loss costs in the operation process of the raw material supplier, parts supplier, and manufacturer respectively.

4. The method according to claim 1, wherein The optimization objective function for constructing the carbon-constrained industrial value chain from the economic cost dimension includes: min ECOF = GD + TC + CSB - FSC GD is the fixed cost, TC is the logistics cost, CSB is the facility cost, and FSC is the loss cost.

5. The method according to claim 1, wherein The optimization objective function for constructing the carbon-constrained industrial value chain from the energy efficiency and emission reduction dimension includes: max CRTEROF = CR + CER Among them, CR is the enterprise rectification parameter, and CER is the enterprise emission reduction parameter.

6. The method according to claim 1, characterized in that The optimization objective function for constructing the carbon-constrained industrial value chain from the development dimension of the environmental protection industrial chain includes: min GSCOF = WQE + BCE + FCE + CPHE Among them, WQE is the logistics carbon emission, BCE is the construction carbon emission, FCE is the functional personnel carbon emission, and CPHE is the harmful substance emission.

7. The method according to claim 1, characterized in that The optimization objective function for constructing the carbon-constrained industrial value chain from the dimension of guiding the public's environmental protection choices includes: maxPPGCOF = GEP + LPE Among them, GEP is the green facility performance parameter, and LPE is the facility's environmental protection performance parameter for guiding the public industrial value chain.

8. The method according to claim 1, wherein The optimization objective function for constructing the carbon-constrained industrial value chain from the dimension of communication and information transparency includes: min SCCTOF = CCP + DIP Among them, CCP is the public accountability and communication parameter, and DIP is the information of the industrial value chain that has not been publicly disclosed.

9. The method according to claim 1, wherein The optimization objective function for constructing the carbon-constrained industrial value chain from the dimension of communication and information transparency includes: max RVCTOF = BLP + CGP + ZSL + CBS Among them, BLP is the type of components participating in recycling, DGP is the resource utilization rate, ZSL is the carbon emission conversion rate, and CBS is the number of components participating in closed-loop production.

10. The constrained multi-objective industrial value chain optimization system based on auxiliary tasks is characterized in that, Including: An industrial value chain construction module for constructing an industrial value chain; The model construction module is used to construct multiple optimization objective functions of the carbon-constrained industrial value chain from the dimensions of economy, economic cost, energy efficiency and emission reduction, development of the environmental protection industrial chain, guiding the public's environmental protection choices, communication and information transparency, and recycling and value circulation, construct the constraint conditions of the carbon-constrained industrial value chain from the dimension of carbon emissions, and generate an industrial value chain model of the full life cycle value; The model solving module is used to solve the full life cycle value model based on the multi-constraint multi-objective optimization algorithm, construct an evolutionary direction in which the auxiliary tasks continuously provide supplements for the main task, and construct an optimal industrial value chain model.

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