A method, system, electronic device and medium for allocating carbon quotas in shipping industry

Abstract

The present invention provides a method, system, electronic device and medium for allocating carbon quotas in the shipping industry, which belongs to the field of carbon asset management. The method includes: obtaining historical operating data of each shipping enterprise in a target area; establishing a first objective function based on the historical operating data, wherein the goal of the first objective function is to maximize the total profit of the shipping enterprises in the target area; obtaining historical carbon emission data of the shipping industry and each shipping enterprise in the target area, and calculating the emission reduction index of each shipping enterprise in the target area on this basis, and then establishing constraints and a second objective function, wherein the goal of the second objective function is to minimize the total carbon emission intensity value of the shipping enterprises in the target area; establishing a multi-objective optimization model based on the first objective function, the second objective function and the constraints, and solving to obtain the free carbon quota and turnover of each shipping enterprise in the target area in the current cycle. The present invention takes into account both the rationality of carbon quota allocation and economic development.

Description

Technical Field

[0001] The present invention relates to the field of carbon asset management, and in particular to a method, system, electronic equipment and medium for allocating carbon quotas in the shipping industry. Background Art

[0002] According to statistics from the United Nations International Maritime Organization (IMO), the global shipping industry emits about 1 billion tons of greenhouse gases each year, accounting for 3% of the world's total emissions, equivalent to the world's sixth largest emitter. The total cargo volume of the shipping industry accounts for about 80% of global trade. It is expected that in the next 30 years, with the growth of the world economy, the demand for maritime transportation is expected to continue to increase. If effective emission reduction measures are not taken, the total greenhouse gas emissions of the global shipping industry will increase significantly. As an economical and effective means of reducing greenhouse gases and responding to global climate change, the carbon emission trading system can reduce CO2 emissions at a lower cost. In the short term, the carbon emission trading system provides an incentive mechanism for efficient and clean enterprises by setting a price for carbon emissions and increasing the costs of inefficient enterprises. In the long run, the carbon emission trading system will affect the future investment direction, making long-term investment more inclined to clean and low-carbon, and ultimately help achieve the goal of carbon neutrality.

[0003] The current carbon emission trading system has three stages in its emission allocation process. In the first stage, the primary management unit allocates CO2 emission quotas to the secondary management unit. In the second stage, the secondary management unit allocates its own CO2 emission quotas to the corresponding industries. In the third stage, the industries allocate to the corresponding terminal emission enterprises. Since the third stage of CO2 emission quota allocation is a terminal process, it can directly affect the production and operation behavior of enterprises.

[0004] The allocation of carbon emission quotas in the shipping industry will have many impacts. The allocation method of quotas will directly and significantly affect the company's operations and production, and different companies have different enthusiasm for emission reduction in specific allocation methods. For the carbon quota allocation method of a single indicator, while meeting the performance of the indicator, most of them will have other defects. For example, although the grandfather method has good feasibility, there will be problems with fairness; and the baseline method of carbon quota allocation only reflects the efficiency principle. Therefore, when allocating carbon quotas to enterprises, fairness and efficiency should be fully considered. Summary of the invention

[0005] The purpose of the present invention is to provide a method, system, electronic equipment and medium for allocating carbon quotas in the shipping industry, which can improve the efficiency and rationality of carbon quota allocation for shipping enterprises.

[0006] To achieve the above object, the present invention provides the following solutions:

[0007] A method for allocating carbon quotas for the shipping industry, comprising:

[0008] Obtaining historical operating data of each shipping company in the target area; the historical operating data includes freight rates per unit turnover, operating costs, emission factors and carbon prices;

[0009] Establishing a first objective function based on the historical operating data of each shipping enterprise in the target area; the goal of the first objective function is to maximize the total profit of the shipping enterprises in the target area;

[0010] Obtain the historical carbon emission data of the shipping industry in the target area of ​​the current cycle, as well as the historical carbon emission data of each shipping enterprise in the target area; the historical carbon emission data of the shipping industry includes the historical total output value of the shipping industry, the historical total carbon emissions of the shipping industry and the historical average carbon emission intensity value of the shipping industry; the historical carbon emission data of the shipping enterprises include the historical output value of the shipping enterprises, the historical carbon emissions of the shipping enterprises and the historical carbon emission intensity value of the shipping enterprises;

[0011] Calculate the emission reduction index of each shipping company in the target area based on the historical carbon emission data of the shipping industry in the target area of ​​the current cycle and the historical carbon emission data of each shipping company, and establish constraint conditions based on the emission reduction index and emission factor of each shipping company;

[0012] A second objective function is established based on the emission factors of each shipping enterprise; the goal of the second objective function is to minimize the total carbon emission intensity value of shipping enterprises in the target area;

[0013] Based on the first objective function, the second objective function and the constraints, a multi-objective optimization model is established, and the free carbon quota and turnover volume of each shipping company in the target area of ​​the current cycle are obtained.

[0014] Optionally, the first objective function is:

[0015]

[0016] Where n is the number of shipping companies in the target area, P i is the freight rate per unit turnover of shipping company i, T i is the turnover of shipping company i in the current cycle, OC i is the operating cost of shipping company i, P c is the carbon price, FE i is the emission factor of shipping company i, representing the carbon emissions per unit turnover, CA i is the free carbon quota of shipping company i in the current cycle, T i and CA i are all decision variables.

[0017] Optionally, the emission reduction index of shipping company i is calculated using the following formula:

[0018]

[0019] in, is the emission reduction index of shipping enterprise i, G is the historical total output value of the shipping industry, G i is the historical output value of shipping enterprise i, H is the historical total carbon emissions of the shipping industry, and H i is the historical carbon emissions of shipping company i, I is the average carbon emission intensity value of the shipping industry, and I i is the historical carbon emission intensity value of shipping company i, w1 is the output value proportion, w2 is the carbon emission proportion, w3 is the carbon emission intensity proportion, and w1+w2+w3=1.

[0020] Optionally, the constraint condition is:

[0021]

[0022]

[0023]

[0024]

[0025] CA i ≥0;

[0026] T i ≥0;

[0027] Among them, CA i Free carbon quota for shipping company i in the current cycle, is the carbon quota lower limit of shipping company i, T i is the turnover of shipping company i in the current period, is the lower limit of the turnover of shipping company i, is the upper limit of the turnover of shipping company i, is the emission reduction index of shipping company i, TCE is the carbon quota of shipping companies in the target area, FE i is the emission factor of shipping company i, representing the carbon emissions per unit turnover, and n is the number of shipping companies in the target area.

[0028] Optionally, the second objective function is:

[0029]

[0030] in, is the total carbon emission intensity value of all shipping companies in the target area, n is the number of shipping companies in the target area, T i is the turnover of shipping company i in the current cycle, FEi is the emission factor of shipping company i, representing the carbon emissions per unit turnover.

[0031] Optionally, a genetic algorithm is used to solve the multi-objective optimization model.

[0032] To achieve the above object, the present invention also provides the following solution:

[0033] A carbon quota allocation system for the shipping industry, comprising:

[0034] An operation data acquisition unit, used to acquire historical operation data of each shipping enterprise in the target area; the historical operation data includes turnover, freight rate per unit turnover, operation cost, emission factor and carbon price;

[0035] A first objective establishing unit, connected to the operation data acquiring unit, is used to establish a first objective function according to the historical operation data of each shipping enterprise in the target area; the goal of the first objective function is to maximize the total profit of the shipping enterprises in the target area;

[0036] A carbon emission data acquisition unit, used to acquire the historical carbon emission data of the shipping industry in the target area of ​​the current cycle and the historical carbon emission data of each shipping enterprise in the target area; the historical carbon emission data of the shipping industry includes the historical total output value of the shipping industry, the historical total carbon emissions of the shipping industry and the average carbon emission intensity value of the shipping industry; the historical carbon emission data of the shipping enterprises includes the historical output value of the shipping enterprises, the historical carbon emissions of the shipping enterprises and the historical carbon emission intensity value of the shipping enterprises;

[0037] A constraint establishing unit, connected to the carbon emission data acquiring unit, is used to calculate the emission reduction index of each shipping enterprise in the target area according to the historical carbon emission data of the shipping industry in the target area of ​​the current cycle and the historical carbon emission data of each shipping enterprise, and establish constraint conditions based on the emission reduction index and emission factor of each shipping enterprise;

[0038] A second target establishing unit, connected to the operation data acquiring unit, is used to establish a second target function according to the emission factors of each shipping enterprise; the target of the second target function is to minimize the total carbon emission intensity value of the shipping enterprises in the target area;

[0039] The carbon quota allocation unit is connected to the constraint establishment unit, the first target establishment unit and the second target establishment unit respectively, and is used to establish a multi-objective optimization model based on the first objective function, the second objective function and the constraint conditions, and to solve and obtain the free carbon quota and turnover of each shipping company in the target area of ​​the current cycle.

[0040] To achieve the above object, the present invention also provides the following solution:

[0041] An electronic device comprises a memory and a processor, wherein the memory is used to store a computer program, and the processor runs the computer program to enable the electronic device to execute the above-mentioned shipping industry carbon quota allocation method.

[0042] To achieve the above object, the present invention also provides the following solution:

[0043] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the above-mentioned method for allocating carbon quotas for the shipping industry.

[0044] According to the specific embodiments provided by the present invention, the present invention discloses the following technical effects: the present invention uses the profit maximization of shipping companies to reflect the index of allocation efficiency, establishes a first objective function, incorporates variables such as the shipping company's ability (output value), responsibility (historical carbon emissions) and potential (carbon emission intensity) to reduce carbon emissions to reflect the index of allocation rationality, establishes a second objective function, considers both the rationality and efficiency of carbon quota allocation, and constructs a multi-objective optimization model, so that the results of carbon quota allocation are reasonable and the efficiency of carbon quota allocation is improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0046] Figure 1 A flow chart of the method for allocating carbon quotas to the shipping industry according to the present invention;

[0047] Figure 2 It is a module schematic diagram of the carbon quota allocation system for the shipping industry of the present invention.

[0048] Explanation of symbols:

[0049] Operation data acquisition unit-1, first target establishment unit-2, carbon emission data acquisition unit-3, constraint establishment unit-4, second target establishment unit-5, carbon quota allocation unit-6. DETAILED DESCRIPTION

[0050] 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.

[0051] The purpose of the present invention is to provide a method, system, electronic device and medium for allocating carbon quotas in the shipping industry, which takes into account the fairness and efficiency of carbon quota allocation based on models such as multi-objective optimization and genetic algorithms.

[0052] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0053] Embodiment 1

[0054] like Figure 1 As shown, this embodiment provides a method for allocating carbon quotas in the shipping industry, including:

[0055] S1: Obtain historical operating data of each shipping company in the target area. The historical operating data includes turnover, freight rate per unit turnover, operating cost, carbon emission factor and carbon price.

[0056] S2: Establishing a first objective function based on the historical operating data of each shipping enterprise in the target area. The goal of the first objective function is to maximize the total profit of the shipping enterprises in the target area.

[0057] Specifically, steps S1 and S2 determine an index that can reflect the efficiency of carbon emission quota allocation in the shipping industry. In this embodiment, the profit maximization of the shipping enterprise is used as an index to reflect the allocation efficiency. The profit calculation formula of the shipping enterprise i is: i =P i T i -OC i T i -(T i *FE i -CA i ). Then the first objective function is:

[0058]

[0059] Where n is the number of shipping companies in the target area, F i is the profit of shipping company i, P i is the freight rate per unit turnover of shipping company i, T i is the turnover of shipping company i in the current cycle, OC i is the operating cost of shipping company i, P c is the carbon price, FE i is the emission factor of shipping company i, representing the carbon emissions per unit turnover, CA i The free carbon quota for shipping company i, T i and CA i are all decision variables.

[0060] S3: Obtain the historical carbon emission data of the shipping industry in the target area of ​​the current cycle, as well as the historical carbon emission data of each shipping enterprise in the target area. The historical carbon emission data of the shipping industry includes the historical total output value of the shipping industry, the historical total carbon emissions of the shipping industry, and the historical average carbon emission intensity value of the shipping industry; the historical carbon emission data of the shipping enterprises include the historical output value of the shipping enterprises, the historical carbon emissions of the shipping enterprises, and the historical carbon emission intensity value of the shipping enterprises.

[0061] S4: Calculate the emission reduction index of each shipping company in the target area based on the historical carbon emission data of the shipping industry in the target area in the current cycle and the historical carbon emission data of each shipping company, and establish constraints based on the emission reduction index and emission factor of each shipping company.

[0062] S5: Establish a second objective function based on the emission factors of each shipping company. The goal of the second objective function is to minimize the total carbon emission intensity value of the shipping companies in the target area.

[0063] Specifically, steps S3 and S4 determine an indicator (emission reduction indicator) that can reflect the fairness of carbon emission quota allocation in the shipping industry. The present invention incorporates variables such as the shipping company's ability (output value), responsibility (historical carbon emissions) and potential (carbon emission intensity) to reduce carbon emissions to reflect this indicator.

[0064] In practical application, the following formula is used to calculate the emission reduction index of shipping company i:

[0065]

[0066] in, is the emission reduction index of shipping enterprise i, G is the historical total output value of the shipping industry, G i is the historical output value of shipping enterprise i, H is the historical total carbon emissions of the shipping industry, and H i is the historical carbon emissions of shipping company i, I is the average carbon emission intensity value of the shipping industry, and I i is the historical carbon emission intensity value of shipping company i, w1 is the output value ratio, w2 is the carbon emission ratio, and w3 is the carbon emission intensity ratio. And w1+w2+w3=1.

[0067] The following constraints are established based on the emission reduction coefficient:

[0068]

[0069] Among them, T i represents the turnover of shipping company i in the current period, The upper limit of turnover is calculated based on historical turnover and can be set to 120% of the highest value in the past three years. The emission reduction coefficient of shipping company i After adjustment, the turnover limit that can be increased, TCE represents the carbon quota of shipping companies in the target area, FE i is the emission factor of shipping company i, representing the carbon emissions per unit turnover.

[0070] According to the principle of fairness, after obtaining the carbon quota allocated based on fairness, the carbon quota is further divided by the turnover to obtain the carbon emission intensity under this principle, and then the minimum value of the carbon emission intensity is obtained. The second objective function is:

[0071]

[0072] in, is the total carbon emission intensity value of all shipping companies in the target area, T i is the turnover of shipping company i in the current cycle, FE i is the emission factor of shipping company i, representing the carbon emissions per unit turnover.

[0073] S6: Based on the first objective function, the second objective function and the constraint conditions, a multi-objective optimization model is established, and the free carbon quota and turnover of each shipping enterprise in the target area of ​​the current cycle are obtained. In this embodiment, a genetic algorithm is used to solve the multi-objective optimization model. The decision variable is the turnover T of shipping enterprise i in the current cycle t. i And free carbon quotas for shipping companies i .

[0074] Furthermore, the constraints of the multi-objective optimization model also include:

[0075]

[0076]

[0077]

[0078]

[0079] CA i ≥0 (5)

[0080] T i ≥0 (6)

[0081] Among them, constraint (1) means that the free carbon quota of shipping company i must be greater than or equal to its carbon quota lower limit The carbon quota limit It can be set based on the historical carbon quota of shipping company i, which is generally 85% of the average value of shipping company i in the past three years. Constraint (2) means that the turnover of shipping company i must be greater than or equal to the lower limit of the turnover of shipping company i It is calculated based on the historical turnover and can generally be set to 120% of the highest value of shipping company i in the past three years. Constraint (3) indicates that the turnover of shipping company i must be less than or equal to the turnover upper limit of shipping company i The turnover limit is calculated based on historical turnover and can be set to 120% of the highest value in the past three years. The emission reduction coefficient of shipping company i After adjustment, the upper limit of turnover volume can be increased.

[0082] The present invention takes into account both fairness and efficiency of carbon quota allocation, constructs a multi-objective optimization model, and uses a genetic algorithm to solve it, so that the results of carbon emission quota allocation are more effective and acceptable, and can provide policy support for carbon emission reduction in the shipping industry based on market means.

[0083] Embodiment 2

[0084] In order to execute the method corresponding to the above-mentioned embodiment 1 to achieve the corresponding functions and technical effects, a carbon quota allocation system for the shipping industry is provided below.

[0085] like Figure 2 As shown, the shipping industry carbon quota allocation system provided by this embodiment includes: an operation data acquisition unit 1, a first target establishment unit 2, a carbon emission data acquisition unit 3, a constraint establishment unit 4, a second target establishment unit 5 and a carbon quota allocation unit 6.

[0086] The operation data acquisition unit 1 is used to acquire the historical operation data of each shipping enterprise in the target area, including turnover, freight rate per unit turnover, operation cost, emission factor and carbon price.

[0087] The first target establishment unit 2 is connected to the operation data acquisition unit 1, and is used to establish a first target function according to the historical operation data of each shipping enterprise in the target area. The target of the first target function is to maximize the total profit of the shipping enterprises in the target area.

[0088] The carbon emission data acquisition unit 3 is used to acquire the historical carbon emission data of the shipping industry in the target area of ​​the current cycle and the historical carbon emission data of each shipping enterprise in the target area. The historical carbon emission data of the shipping industry includes the historical total output value of the shipping industry, the historical total carbon emissions of the shipping industry and the average carbon emission intensity value of the shipping industry. The historical carbon emission data of the shipping enterprises include the historical output value of the shipping enterprises, the historical carbon emissions of the shipping enterprises and the historical carbon emission intensity value of the shipping enterprises.

[0089] The constraint establishing unit 4 is connected to the carbon emission data acquiring unit 3, and the constraint establishing unit 4 is used to calculate the emission reduction index of each shipping company in the target area according to the historical carbon emission data of the shipping industry in the target area of ​​the current cycle and the historical carbon emission data of each shipping company, and establish constraint conditions based on the emission reduction index and emission factor of each shipping company.

[0090] The second target establishment unit 5 is connected to the operation data acquisition unit 1, and is used to establish a second target function according to the emission factors of each shipping enterprise. The target of the second target function is to minimize the total carbon emission intensity value of the shipping enterprises in the target area.

[0091] The carbon quota allocation unit 6 is connected to the constraint establishment unit 4, the first target establishment unit 3 and the second target establishment unit 4 respectively. The carbon quota allocation unit 5 is used to establish a multi-objective optimization model based on the first objective function, the second objective function and the constraint conditions, and to solve and obtain the free carbon quota and turnover volume of each shipping company in the target area of ​​the current cycle.

[0092] Compared with the prior art, the carbon quota allocation system for the shipping industry provided in this embodiment has the same beneficial effects as the carbon quota allocation method for the shipping industry provided in Example 1, which will not be described in detail here.

[0093] Embodiment 3

[0094] This embodiment provides an electronic device, including a memory and a processor, wherein the memory is used to store a computer program, and the processor runs the computer program to enable the electronic device to execute the shipping industry carbon quota allocation method of the first embodiment.

[0095] Optionally, the above-mentioned electronic device may be a server.

[0096] In addition, an embodiment of the present invention further provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the method for allocating carbon quotas for the shipping industry of embodiment 1.

[0097] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the various embodiments can be referenced to each other.

[0098] The principles and implementation methods of the present invention are described in this article using specific examples. The description of the above embodiments is only used to help understand the method and core idea of ​​the present invention. At the same time, for those skilled in the art, according to the idea of ​​the present invention, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting the present invention.

Claims

1. A method for allocating carbon quotas in the shipping industry, characterized in that: The shipping industry carbon quota allocation method includes: Obtaining historical operating data of each shipping company in the target area; the historical operating data includes freight rates per unit turnover, operating costs, emission factors and carbon prices; A first objective function is established based on the historical operating data of each shipping enterprise in the target area; the goal of the first objective function is to maximize the total profit of the shipping enterprises in the target area; the first objective function is: Where n is the number of shipping companies in the target area, P i is the freight rate per unit turnover of shipping company i, T i is the turnover of shipping company i in the current cycle, OC i is the operating cost of shipping company i, P c is the carbon price, FE i is the emission factor of shipping company i, representing the carbon emissions per unit turnover, CA i is the free carbon quota of shipping company i in the current cycle, T i and CA i All are decision variables; Obtain the historical carbon emission data of the shipping industry in the target area of ​​the current cycle, as well as the historical carbon emission data of each shipping enterprise in the target area; the historical carbon emission data of the shipping industry includes the historical total output value of the shipping industry, the historical total carbon emissions of the shipping industry and the historical average carbon emission intensity value of the shipping industry; the historical carbon emission data of the shipping enterprises include the historical output value of the shipping enterprises, the historical carbon emissions of the shipping enterprises and the historical carbon emission intensity value of the shipping enterprises; Calculate the emission reduction index of each shipping company in the target area based on the historical carbon emission data of the shipping industry in the target area of ​​the current cycle and the historical carbon emission data of each shipping company, and establish constraint conditions based on the emission reduction index and emission factor of each shipping company; The emission reduction index of shipping company i is calculated using the following formula: in, is the emission reduction index of shipping enterprise i, G is the historical total output value of the shipping industry, G i is the historical output value of shipping enterprise i, H is the historical total carbon emissions of the shipping industry, and H i is the historical carbon emissions of shipping company i, I is the average carbon emission intensity value of the shipping industry, and I i is the historical carbon emission intensity value of shipping company i, w1 is the output value ratio, w2 is the carbon emission ratio, w3 is the carbon emission intensity ratio, and w1+w2+w3=1; The constraints are: THAT i ≥0; T i ≥0； in, is the carbon quota lower limit of shipping company i, is the lower limit of the turnover of shipping company i, is the turnover limit of shipping company i, TCE is the carbon quota of shipping companies in the target area; A second objective function is established based on the emission factors of each shipping company; the goal of the second objective function is to minimize the total carbon emission intensity value of shipping companies in the target area; the second objective function is: in, is the total carbon emission intensity value of all shipping companies in the target area; Based on the first objective function, the second objective function and the constraints, a multi-objective optimization model is established, and the free carbon quota and turnover volume of each shipping company in the target area of ​​the current cycle are obtained.

2. The method for allocating carbon quotas for the shipping industry according to claim 1, characterized in that: A genetic algorithm is used to solve the multi-objective optimization model.

3. A shipping industry carbon quota allocation system, applied to the shipping industry carbon quota allocation method according to any one of claims 1-2, characterized in that: The shipping industry carbon quota allocation system includes: An operation data acquisition unit, used to acquire historical operation data of each shipping enterprise in the target area; the historical operation data includes turnover, freight rate per unit turnover, operation cost, emission factor and carbon price; A first objective establishing unit, connected to the operation data acquiring unit, is used to establish a first objective function according to the historical operation data of each shipping enterprise in the target area; the goal of the first objective function is to maximize the total profit of the shipping enterprises in the target area; A carbon emission data acquisition unit, used to acquire the historical carbon emission data of the shipping industry in the target area of ​​the current cycle and the historical carbon emission data of each shipping enterprise in the target area; the historical carbon emission data of the shipping industry includes the historical total output value of the shipping industry, the historical total carbon emissions of the shipping industry and the average carbon emission intensity value of the shipping industry; the historical carbon emission data of the shipping enterprises includes the historical output value of the shipping enterprises, the historical carbon emissions of the shipping enterprises and the historical carbon emission intensity value of the shipping enterprises; A constraint establishing unit, connected to the carbon emission data acquiring unit, is used to calculate the emission reduction index of each shipping enterprise in the target area according to the historical carbon emission data of the shipping industry in the target area of ​​the current cycle and the historical carbon emission data of each shipping enterprise, and establish constraint conditions based on the emission reduction index and emission factor of each shipping enterprise; A second target establishing unit, connected to the operation data acquiring unit, is used to establish a second target function according to the emission factors of each shipping enterprise; the target of the second target function is to minimize the total carbon emission intensity value of the shipping enterprises in the target area; The carbon quota allocation unit is connected to the constraint establishment unit, the first target establishment unit and the second target establishment unit respectively, and is used to establish a multi-objective optimization model based on the first objective function, the second objective function and the constraint conditions, and to solve and obtain the free carbon quota and turnover of each shipping company in the target area of ​​the current cycle.

4. An electronic device, characterized in that: The electronic device comprises a memory and a processor, wherein the memory is used to store a computer program, and the processor runs the computer program to enable the electronic device to execute the shipping industry carbon quota allocation method according to any one of claims 1 to 2.

5. A computer-readable storage medium, characterized in that: The computer program is stored therein, and when the computer program is executed by a processor, the method for allocating carbon quotas for the shipping industry as claimed in any one of claims 1 to 2 is implemented.

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