CN114239908A - Overseas purchase order optimization method considering carbon emission constraint in transportation process - Google Patents

Overseas purchase order optimization method considering carbon emission constraint in transportation process Download PDF

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CN114239908A
CN114239908A CN202111338345.4A CN202111338345A CN114239908A CN 114239908 A CN114239908 A CN 114239908A CN 202111338345 A CN202111338345 A CN 202111338345A CN 114239908 A CN114239908 A CN 114239908A
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cost
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王国强
蒋媛媛
陈盈盈
罗贺
程八一
陆效农
余本功
吴萍
石鑫焱
田亚静
缪运运
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Hefei University of Technology
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Abstract

The invention provides an overseas purchase order optimization method, system, storage medium and electronic equipment considering carbon emission constraints in a transportation process, and relates to the technical field of material purchase. The method comprises the steps of constructing an overseas purchase order optimization model considering economic and environmental targets according to enterprise production information and carbon emission constraint conditions in the transportation process on the premise of meeting the requirement of a tax discount policy; according to the overseas purchase order optimization model, determining the amount of materials respectively purchased to the inland or overseas for the overseas production base of the manufacturing enterprise by adopting a multi-objective genetic algorithm, namely determining the optimized overseas purchase order. An optimal balance point is searched between an economic target and an environmental target, and an optimal solution is obtained under the condition that the cost is only slightly increased within a carbon emission range suitable for the environment; the optimized production plan can pursue the optimal value of carbon emission under the condition of higher economic cost, thereby achieving the optimal overall procurement plan.

Description

Overseas purchase order optimization method considering carbon emission constraint in transportation process
Technical Field
The invention relates to the technical field of material purchasing, in particular to an overseas purchase order optimization method and system considering carbon emission constraints in a transportation process, a storage medium and electronic equipment.
Background
With the influence of globalization trend, manufacturing enterprises gradually begin to transform and develop overseas markets, and overseas investment and factory building becomes one of the important ways for internationalization of enterprises. Considering that the biggest feature of its supply chain is that an enterprise is usually off-shore, the production planning and material procurement planning of the enterprise are greatly influenced by the transportation planning and cannot be considered as independent processes.
At present, activities such as raw material purchasing, production planning and inventory management in production chain management are often handled independently in practical situations. Production planning and raw material procurement decisions are usually made at different times, most of which are made after production planning is generated by a production planning system, and procurement and transportation decisions are made separately, however, increasing cost pressures and customer expectations and the changing business environment force the procurement planning to be continually optimized, increasing efficiency, while maintaining sufficient flexibility to cope with global market changes.
In addition, transportation as a non-negligible part of the purchasing process is also considered to be the largest source of environmental hazards in logistics systems. Nowadays, large-scale emission of greenhouse gases is an important environmental problem, so that enterprises gradually bring greenhouse gas emission reduction activities into enterprise supply chain management, and the enterprises enhance public relations and generate new income sources while reducing emission.
Carbon emissions are an important environmental issue, and enterprises are under increasing pressure from consumers and governments, however, generally speaking, as the total amount of carbon emissions is reduced, the total cost of procurement increases, and the pursuit of environmental goals alone will result in economic losses for the enterprises. In view of the above, it is desirable to provide a joint optimization plan for both production-procurement supply chain links that takes into account economic and environmental objectives.
Disclosure of Invention
Technical problem to be solved
Aiming at the defects of the prior art, the invention provides an overseas purchase order optimization method, a system, a storage medium and electronic equipment considering carbon emission constraint in the transportation process, and solves the technical problems that most of production plans are generated by a production planning system and then purchase and transportation decisions are made respectively, and economic targets and environmental targets are not considered.
(II) technical scheme
In order to achieve the purpose, the invention is realized by the following technical scheme:
a method for overseas purchase order optimization taking into account carbon emission constraints during transportation, comprising:
s1, acquiring enterprise production information;
s2, presetting carbon emission constraint conditions in the transportation process corresponding to the enterprise procurement plan;
s3, on the premise of meeting the requirement of the tax discount policy, constructing an overseas purchase order optimization model considering both economic and environmental targets according to the enterprise production information and the carbon emission constraint conditions in the transportation process;
s4, determining the amount of materials purchased respectively to the inside or the outside for the manufacturing enterprise outside production base by adopting a multi-objective genetic algorithm according to the optimized model of the outside purchase order built in the previous step, namely determining the optimized outside purchase order.
Preferably, the overseas purchase order optimization model in S3 includes,
an objective function that considers both economic objectives with minimal procurement costs and environmental objectives with minimal transportation environmental impact:
Figure BDA0003351369340000031
Figure BDA0003351369340000032
Figure BDA0003351369340000033
Figure BDA0003351369340000034
wherein E islRepresents the jth cost; l represents the number of cost categories; FTE represents carbon emission cost; TE represents the actual carbon emission; c. Cco2Is a standard discharge unit price, cexDischarge price for the over-standard part, qsThe maximum allowable discharge amount;
Figure BDA0003351369340000035
represents the fixed environmental impact of the shipment of a part j from a domestic base n to a overseas base k in a shipment manner g at a time t;
Figure BDA0003351369340000036
indicating that the piece j is in transit g from home at time tUnit variable environmental impact of base n transporting to overseas base k;
Figure BDA0003351369340000037
representing a binary variable, if the part j is transported from the domestic base n to the overseas base k in the transport mode g in the time t period, the value is 1, otherwise, the value is 0; xjnkgtRepresenting the number of corresponding transported parts j;
Figure BDA0003351369340000038
represents the maximum cost of the shipment of the parts j from the domestic base n to the overseas base k over time t in the manner of transportation g.
Preferably, the number of the cost categories is 2, and specifically includes:
raw material cost:
Figure BDA0003351369340000039
wherein the content of the first and second substances,
Figure BDA00033513693400000310
represents the fixed cost of importing raw material i from domestic base n at time t;
Figure BDA00033513693400000311
representing a binary variable, if the raw material i is imported from a domestic base n in the period t, the value is 1, otherwise, the value is 0;
Figure BDA0003351369340000041
represents the cost of raw material i imported from domestic base n during time t;
Figure BDA0003351369340000042
represents the quantity of raw material i imported from the domestic base n at the time t;
Figure BDA0003351369340000043
is shown inThe fixed cost of the parts j is imported from a domestic base n in the period t;
Figure BDA0003351369340000044
representing a binary variable, which is 1 if the part j is imported from the domestic base n in the period t, or 0 if not;
Figure BDA0003351369340000045
represents the cost of the change of import of parts j from domestic base n at time t;
Figure BDA0003351369340000046
representing the number of imported parts j from domestic base n during time t;
Figure BDA0003351369340000047
represents the fixed cost of purchasing parts j from overseas base k at time t;
Figure BDA0003351369340000048
represents a binary variable, which is 1 if part j is purchased from overseas base k at time t, and 0 otherwise;
Figure BDA0003351369340000049
represents the varying cost of purchasing parts j from overseas base k at time t,
Figure BDA00033513693400000410
representing the number of purchased parts j from overseas base k at time t;
transportation cost:
Figure BDA00033513693400000411
wherein the content of the first and second substances,
Figure BDA00033513693400000412
indicating the departure of a part j from the countryFixed cost for the internal base n to transport to the overseas base k in the time t period in the transport mode g; x is the number ofjnkgtRepresents the fluctuating cost of transporting a piece j from a domestic base n to an overseas base k over a period of time t in a transport mode g.
Preferably, the tax coupon policy requirement in S3 includes:
Figure BDA00033513693400000413
wherein, yiRepresenting the local localization purchase amount of the raw material i from overseas; qiRepresents the total demand of the enterprise for raw material i, and Qi＝xi+yi，xiRepresenting the purchase amount of the raw material i from a domestic base; miThe requirement of the tax policy on the minimum amount of the raw material i in the local procurement is expressed.
Preferably, in S4, the overseas purchase order optimization model is solved by using an NSGA-II algorithm.
A overseas purchase order optimization system that considers carbon emission constraints during transit, comprising:
the information acquisition module is used for acquiring enterprise production information;
the condition presetting module is used for presetting carbon emission constraint conditions in the transportation process corresponding to the enterprise purchasing plan;
the model construction module is used for constructing an overseas purchase order optimization model considering both economic and environmental targets according to the enterprise production information and the carbon emission constraint conditions in the transportation process on the premise of meeting the tax discount policy requirements;
and the order optimization module is used for determining the amounts of the materials purchased respectively to the inside or the outside for the manufacturing enterprise overseas production base by adopting a multi-objective genetic algorithm according to the overseas purchase order optimization model constructed by the previous module, namely determining the optimized overseas purchase order.
Preferably, the overseas purchase order optimization model includes,
an objective function that considers both economic objectives with minimal procurement costs and environmental objectives with minimal transportation environmental impact:
an objective function that considers both economic objectives with minimal procurement costs and environmental objectives with minimal transportation environmental impact:
Figure BDA0003351369340000051
Figure BDA0003351369340000052
Figure BDA0003351369340000053
Figure BDA0003351369340000054
wherein E islRepresents the jth cost; l represents the number of cost categories; FTE represents carbon emission cost; TE represents the actual carbon emission; c. Cco2Is a standard discharge unit price, cexDischarge price for the over-standard part, qsThe maximum allowable discharge amount;
Figure BDA0003351369340000055
represents the fixed environmental impact of the shipment of a part j from a domestic base n to a overseas base k in a shipment manner g at a time t;
Figure BDA0003351369340000061
represents the unit variable environmental impact of the shipment of a part j from a domestic base n to a overseas base k in a shipment manner g at a time t;
Figure BDA0003351369340000062
representing a binary variable, if the part j is transported from the domestic base n to the overseas base k in the transport mode g in the time t period, the value is 1, otherwise, the value is 0; xjnkgtRepresenting the number of corresponding transported parts j;
Figure BDA0003351369340000063
represents the maximum cost of the parts j to be transported from the domestic base n to the overseas base k in the transport mode g during the time t;
the cost category number is 2, and specifically includes:
raw material cost:
Figure BDA0003351369340000064
wherein the content of the first and second substances,
Figure BDA0003351369340000065
represents the fixed cost of importing raw material i from domestic base n at time t;
Figure BDA0003351369340000066
representing a binary variable, if the raw material i is imported from a domestic base n in the period t, the value is 1, otherwise, the value is 0;
Figure BDA0003351369340000067
represents the cost of raw material i imported from domestic base n during time t;
Figure BDA0003351369340000068
represents the quantity of raw material i imported from the domestic base n at the time t;
Figure BDA0003351369340000069
represents the fixed cost of importing a part j from a domestic base n at time t;
Figure BDA00033513693400000610
representing a binary variable, which is 1 if the part j is imported from the domestic base n in the period t, or 0 if not;
Figure BDA00033513693400000611
represents the cost of the change of import of parts j from domestic base n at time t;
Figure BDA00033513693400000612
representing the number of imported parts j from domestic base n during time t;
Figure BDA00033513693400000613
represents the fixed cost of purchasing parts j from overseas base k at time t;
Figure BDA00033513693400000614
represents a binary variable, which is 1 if part j is purchased from overseas base k at time t, and 0 otherwise;
Figure BDA00033513693400000615
represents the varying cost of purchasing parts j from overseas base k at time t,
Figure BDA00033513693400000616
representing the number of purchased parts j from overseas base k at time t;
transportation cost:
Figure BDA0003351369340000071
wherein the content of the first and second substances,
Figure BDA0003351369340000072
represents a fixed cost of transporting a piece j from a domestic base n to an overseas base k in a transport manner g over a period of time t; x is the number ofjnkgtRepresents the fluctuating cost of transporting a piece j from a domestic base n to an overseas base k over a period of time t in a transport mode g.
Preferably, the tax coupon policy requirements include
Figure BDA0003351369340000073
Wherein, yiRepresenting the local localization purchase amount of the raw material i from overseas; qiRepresents the total demand of the enterprise for raw material i, and Qi＝xi+yi，xiRepresenting the purchase amount of the raw material i from a domestic base; miThe requirement of the tax policy on the minimum amount of the raw material i in the local procurement is expressed.
A storage medium storing a computer program for overseas purchase order optimization taking into account carbon emission constraints during transit, wherein the computer program causes a computer to perform the overseas purchase order optimization method as described above.
An electronic device, comprising:
one or more processors;
a memory; and
one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the programs comprising instructions for performing the overseas purchase order optimization method as described above.
(III) advantageous effects
The invention provides an overseas purchase order optimization method, an overseas purchase order optimization system, a storage medium and electronic equipment, wherein carbon emission constraints are considered in the transportation process. Compared with the prior art, the method has the following beneficial effects:
the method comprises the steps of obtaining enterprise production information; presetting carbon emission constraint conditions in a transportation process corresponding to the enterprise purchasing plan; on the premise of meeting the requirement of the tax discount policy, constructing an overseas purchase order optimization model considering both economic and environmental targets according to the enterprise production information and the carbon emission constraint conditions in the transportation process; according to the overseas purchase order optimization model, determining the amount of materials respectively purchased to the inland or overseas local for the overseas production base of the manufacturing enterprise by adopting a multi-objective genetic algorithm, namely determining the optimized overseas purchase order. An optimal balance point is searched between an economic target and an environmental target, and an optimal solution is obtained under the condition that the cost is only slightly increased within a carbon emission range suitable for the environment; the optimized production plan can pursue the optimal value of carbon emission under the condition of higher economic cost, so that the optimal overall procurement plan is achieved; the solution optimized by the intelligent algorithm is more intelligent and scientific, and can provide guarantee for the purchasing plan.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a schematic flow chart of a method for optimizing an overseas purchase order in consideration of carbon emission constraints during transportation according to an embodiment of the present invention;
FIG. 2 is a schematic flow chart of a multi-objective genetic algorithm according to an embodiment of the present invention;
fig. 3 is a block diagram of an overseas purchase order optimization system considering carbon emission constraints during transportation according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention are clearly and completely described, and it is obvious that the described embodiments are a part of the embodiments of the present invention, but not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The embodiment of the application provides the overseas purchase order optimization method, the overseas purchase order optimization system, the storage medium and the electronic equipment considering the carbon emission constraint in the transportation process, and solves the technical problems that most of the overseas purchase orders are respectively made with purchase and transportation decisions after a production plan is generated by a production planning system, and the economic objective and the environmental objective are not considered.
In order to solve the technical problems, the general idea of the embodiment of the application is as follows:
the embodiment of the invention comprises the steps of obtaining enterprise production information; presetting carbon emission constraint conditions in a transportation process corresponding to the enterprise purchasing plan; on the premise of meeting the requirement of the tax discount policy, constructing an overseas purchase order optimization model considering both economic and environmental targets according to the enterprise production information and the carbon emission constraint conditions in the transportation process; and according to the overseas purchase order optimization model constructed in the last step, determining the amount of materials respectively purchased to the inland or overseas for the overseas production base of the manufacturing enterprise by adopting a multi-objective genetic algorithm, namely determining the optimized overseas purchase order. An optimal balance point is searched between an economic target and an environmental target, and an optimal solution is obtained under the condition that the cost is only slightly increased within a carbon emission range suitable for the environment; the optimized production plan can pursue the optimal value of carbon emission under the condition of higher economic cost, so that the optimal overall procurement plan is achieved; the solution optimized by the intelligent algorithm is more intelligent and scientific, and can provide guarantee for the purchasing plan.
In order to better understand the technical solution, the technical solution will be described in detail with reference to the drawings and the specific embodiments.
Example (b):
in a first aspect, as shown in fig. 1, an embodiment of the present invention provides a method for optimizing an overseas purchase order in consideration of carbon emission constraints during transportation, including:
s1, acquiring enterprise production information;
s2, presetting carbon emission constraint conditions in the transportation process corresponding to the enterprise procurement plan;
s3, on the premise of meeting the requirement of the tax discount policy, constructing an overseas purchase order optimization model considering both economic and environmental targets according to the enterprise production information and the carbon emission constraint conditions in the transportation process;
s4, determining the amount of materials purchased respectively to the inside or the outside for the manufacturing enterprise outside production base by adopting a multi-objective genetic algorithm according to the optimized model of the outside purchase order built in the previous step, namely determining the optimized outside purchase order.
In the embodiment of the invention, an optimal balance point is searched between an economic target and an environmental target, and an optimized solution is obtained under the condition that the cost is only slightly increased within a carbon emission range suitable for the environment; the optimized production plan can pursue the optimal value of carbon emission under the condition of higher economic cost, so that the optimal overall procurement plan is achieved; the solution optimized by the intelligent algorithm is more intelligent and scientific, and can provide guarantee for the purchasing plan.
The overseas purchase order optimization model in S3 includes,
an objective function that considers both economic objectives with minimal procurement costs and environmental objectives with minimal transportation environmental impact:
Figure BDA0003351369340000111
Figure BDA0003351369340000112
Figure BDA0003351369340000113
Figure BDA0003351369340000114
wherein E islRepresents the jth cost; l represents the number of cost categories; FTE represents carbon emission cost; TE represents the actual carbon emission; c. Cco2Is a standard discharge unit price, cexDischarge price for the over-standard part, qsThe maximum allowable discharge amount;
Figure BDA0003351369340000115
represents the fixed environmental impact of the shipment of a part j from a domestic base n to a overseas base k in a shipment manner g at a time t;
Figure BDA0003351369340000116
represents the unit variable environmental impact of the shipment of a part j from a domestic base n to a overseas base k in a shipment manner g at a time t;
Figure BDA0003351369340000117
representing a binary variable, if the part j is transported from the domestic base n to the overseas base k in the transport mode g in the time t period, the value is 1, otherwise, the value is 0; xjnkgtRepresenting the number of corresponding transported parts j;
Figure BDA0003351369340000118
represents the maximum cost of the shipment of the parts j from the domestic base n to the overseas base k over time t in the manner of transportation g.
The cost category number is 2, and specifically includes:
raw material cost:
Figure BDA0003351369340000119
wherein the content of the first and second substances,
Figure BDA00033513693400001110
represents the fixed cost of importing raw material i from domestic base n at time t;
Figure BDA00033513693400001111
representing a binary variable, if the raw material i is imported from a domestic base n in the period t, the value is 1, otherwise, the value is 0;
Figure BDA00033513693400001112
represents the cost of raw material i imported from domestic base n during time t;
Figure BDA00033513693400001113
represents the quantity of raw material i imported from the domestic base n at the time t;
Figure BDA0003351369340000121
represents the fixed cost of importing a part j from a domestic base n at time t;
Figure BDA0003351369340000122
representing a binary variable, which is 1 if the part j is imported from the domestic base n in the period t, or 0 if not;
Figure BDA0003351369340000123
represents the cost of the change of import of parts j from domestic base n at time t;
Figure BDA0003351369340000124
representing the number of imported parts j from domestic base n during time t;
Figure BDA0003351369340000125
represents the fixed cost of purchasing parts j from overseas base k at time t;
Figure BDA0003351369340000126
represents a binary variable, which is 1 if part j is purchased from overseas base k at time t, and 0 otherwise;
Figure BDA0003351369340000127
represents the varying cost of purchasing parts j from overseas base k at time t,
Figure BDA0003351369340000128
representing the number of purchased parts j from overseas base k at time t;
transportation cost:
Figure BDA0003351369340000129
wherein the content of the first and second substances,
Figure BDA00033513693400001210
represents a fixed cost of transporting a piece j from a domestic base n to an overseas base k in a transport manner g over a period of time t; x is the number ofjnkgtRepresents the fluctuating cost of transporting a piece j from a domestic base n to an overseas base k over a period of time t in a transport mode g.
The step of incorporating the tax benefit policy requirement in S3 includes:
Figure BDA00033513693400001211
wherein, yiRepresenting the local localization purchase amount of the raw material i from overseas; qiRepresents the total demand of the enterprise for raw material i, and Qi＝xi+yi，xiRepresenting the purchase amount of the raw material i from a domestic base; miThe local procurement requirement of the raw material i in the local procurement in the tax policy is expressed, and specifically, the local procurement proportion of the local procurement in the local overseas production base in the overseas of the manufacturing enterprise is not less than the minimum proportion specified in the local government tax coupon policy.
As shown in fig. 2, in S4, the overseas purchase order optimization model is specifically solved by using an NSGA-II algorithm, where the NSGA-II algorithm is a fast non-dominated multi-objective optimization algorithm with an elite retention policy, and is a multi-objective optimization algorithm based on a Pareto optimal solution, which is the prior art, and is not described herein again in the embodiments of the present invention.
From the above description, it can be seen that the embodiment of the invention provides a dual-objective robust optimization model considering incorporating tax policy into cost optimization problem, with the purchase plan optimization problem faced by the multinational manufacturing enterprise as a background. The first objective is to minimize the total cost of procurement, including raw material costs, transportation costs; the second goal is to minimize the impact on the environment during procurement (i.e. carbon dioxide emissions): firstly, mathematical modeling is carried out according to the actual situation in the purchasing process, and simultaneously, in consideration of the preferential effect brought by the tax policy, the solution optimization is carried out by using a multi-objective genetic algorithm, namely an NSGA-II algorithm, so as to obtain the purchasing optimization method.
In a second aspect, an embodiment of the present invention provides an overseas purchase order optimization system considering carbon emission constraints during transportation, including:
the information acquisition module is used for acquiring enterprise production information;
the condition presetting module is used for presetting carbon emission constraint conditions in the transportation process corresponding to the enterprise purchasing plan;
the model construction module is used for constructing an overseas purchase order optimization model considering both economic and environmental targets according to the enterprise production information and the carbon emission constraint conditions in the transportation process on the premise of meeting the tax discount policy requirements;
and the order optimization module is used for determining the amounts of the materials purchased respectively to the inside or the outside for the manufacturing enterprise overseas production base by adopting a multi-objective genetic algorithm according to the overseas purchase order optimization model constructed in the last step, namely determining the optimized overseas purchase order.
The overseas purchase order optimization model includes,
an objective function that considers both economic objectives with minimal procurement costs and environmental objectives with minimal transportation environmental impact:
Figure BDA0003351369340000141
Figure BDA0003351369340000142
Figure BDA0003351369340000143
Figure BDA0003351369340000144
wherein E islRepresents the jth cost; l represents the number of cost categories; FTE represents carbon emission cost; TE represents the actual carbon emission; c. Cco2Is a standard discharge unit price, cexDischarge price for the over-standard part, qsThe maximum allowable discharge amount;
Figure BDA0003351369340000145
represents the fixed environmental impact of the shipment of a part j from a domestic base n to a overseas base k in a shipment manner g at a time t;
Figure BDA0003351369340000146
represents the unit variable environmental impact of the shipment of a part j from a domestic base n to a overseas base k in a shipment manner g at a time t;
Figure BDA0003351369340000147
representing a binary variable, if the part j is transported from the domestic base n to the overseas base k in the transport mode g in the time t period, the value is 1, otherwise, the value is 0; xjnkgtRepresenting the number of corresponding transported parts j;
Figure BDA0003351369340000148
represents the maximum cost of the shipment of the parts j from the domestic base n to the overseas base k over time t in the manner of transportation g.
The cost category number is 2, and specifically includes:
raw material cost:
Figure BDA0003351369340000149
wherein the content of the first and second substances,
Figure BDA00033513693400001410
represents the fixed cost of importing raw material i from domestic base n at time t;
Figure BDA00033513693400001411
representing a binary variable, if the raw material i is imported from a domestic base n in the period t, the value is 1, otherwise, the value is 0;
Figure BDA0003351369340000151
represents the cost of raw material i imported from domestic base n during time t;
Figure BDA0003351369340000152
represents the quantity of raw material i imported from the domestic base n at the time t;
Figure BDA0003351369340000153
represents the fixed cost of importing a part j from a domestic base n at time t;
Figure BDA0003351369340000154
representing a binary variable, which is 1 if the part j is imported from the domestic base n in the period t, or 0 if not;
Figure BDA0003351369340000155
represents the cost of the change of import of parts j from domestic base n at time t;
Figure BDA0003351369340000156
representing the number of imported parts j from domestic base n during time t;
Figure BDA0003351369340000157
represents the fixed cost of purchasing parts j from overseas base k at time t;
Figure BDA0003351369340000158
represents a binary variable, which is 1 if part j is purchased from overseas base k at time t, and 0 otherwise;
Figure BDA0003351369340000159
represents the varying cost of purchasing parts j from overseas base k at time t,
Figure BDA00033513693400001510
representing the number of purchased parts j from overseas base k at time t;
transportation cost:
Figure BDA00033513693400001511
wherein the content of the first and second substances,
Figure BDA00033513693400001512
represents a fixed cost of transporting a piece j from a domestic base n to an overseas base k in a transport manner g over a period of time t; x is the number ofjnkgtRepresents the fluctuating cost of transporting a piece j from a domestic base n to an overseas base k over a period of time t in a transport mode g.
The incorporating tax-benefit policy requirements includes the incorporating tax-benefit policy requirements in the S2 including:
Figure BDA00033513693400001513
wherein, yiRepresenting the local localization purchase amount of the raw material i from overseas; qiRepresents the total demand of the enterprise for raw material i, and Qi＝xi+yi，xiRepresenting the purchase amount of the raw material i from a domestic base; miThe requirement of the tax policy on the minimum amount of the raw material i in the local procurement is expressed.
In a third aspect, embodiments of the present invention provide a storage medium storing a computer program for overseas purchase order optimization that takes into account carbon emission constraints during transit, wherein the computer program causes a computer to perform a purchase plan optimization method as described above.
In a fourth aspect, an embodiment of the present invention provides an electronic device, including:
one or more processors;
a memory; and
one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the programs comprising instructions for performing the method for purchase plan optimization as described above.
It can be understood that, the overseas purchase order optimization system, the storage medium and the electronic device that consider the carbon emission constraint during transportation provided by the embodiment of the present invention correspond to the overseas purchase order optimization method that considers the carbon emission constraint during transportation provided by the embodiment of the present invention, and the explanation, the example, the beneficial effects and other parts of the relevant contents may refer to the corresponding parts in the overseas purchase order optimization method that consider the carbon emission constraint during transportation, and are not described herein again.
In summary, compared with the prior art, the method has the following beneficial effects:
the embodiment of the invention comprises the steps of obtaining enterprise production information; presetting carbon emission constraint conditions in a transportation process corresponding to the enterprise purchasing plan; on the premise of meeting the requirement of the tax discount policy, constructing an overseas purchase order optimization model considering both economic and environmental targets according to the enterprise production information and the carbon emission constraint conditions in the transportation process; and according to the overseas purchase order optimization model constructed in the last step, determining the amount of materials respectively purchased to the inland or overseas for the overseas production base of the manufacturing enterprise by adopting a multi-objective genetic algorithm, namely determining the optimized overseas purchase order. An optimal balance point is searched between an economic target and an environmental target, and an optimal solution is obtained under the condition that the cost is only slightly increased within a carbon emission range suitable for the environment; the optimized production plan can pursue the optimal value of carbon emission under the condition of higher economic cost, so that the optimal overall procurement plan is achieved; the solution optimized by the intelligent algorithm is more intelligent and scientific, and can provide guarantee for the purchasing plan.
It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
The above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.

Claims (10)

1. A method for optimizing an overseas purchase order taking into account carbon emission constraints during transportation, comprising:
s1, acquiring enterprise production information;
s2, presetting carbon emission constraint conditions in the transportation process corresponding to the enterprise procurement plan;
s3, on the premise of meeting the requirement of the tax discount policy, constructing an overseas purchase order optimization model considering both economic and environmental targets according to the enterprise production information and the carbon emission constraint conditions in the transportation process;
s4, determining the amount of materials purchased respectively to the inside or the outside for the manufacturing enterprise outside production base by adopting a multi-objective genetic algorithm according to the optimized model of the outside purchase order built in the previous step, namely determining the optimized outside purchase order.
2. The overseas purchase order optimization method of claim 1, wherein the overseas purchase order optimization model of S3 includes,
an objective function that considers both economic objectives with minimal procurement costs and environmental objectives with minimal transportation environmental impact:
Figure FDA0003351369330000011
Figure FDA0003351369330000012
Figure FDA0003351369330000013
Figure FDA0003351369330000014
wherein E islRepresents the jth cost; l represents the number of cost categories; FTE represents carbon emission cost; TE represents the actual carbon emission; c. Cco2Is a standard discharge unit price, cexDischarge price for the over-standard part, qsThe maximum allowable discharge amount;
Figure FDA0003351369330000015
represents the fixed environmental impact of the shipment of a part j from a domestic base n to a overseas base k in a shipment manner g at a time t;
Figure FDA0003351369330000021
represents the unit variable environmental impact of the shipment of a part j from a domestic base n to a overseas base k in a shipment manner g at a time t;
Figure FDA0003351369330000022
representing a binary variable, if the part j is transported from the domestic base n to the overseas base k in the transport mode g in the time t period, the value is 1, otherwise, the value is 0; xjnkgtRepresenting the number of corresponding transported parts j;
Figure FDA0003351369330000023
represents the maximum cost of the shipment of the parts j from the domestic base n to the overseas base k over time t in the manner of transportation g.
3. The overseas procurement order optimization method of claim 2, wherein the cost category number is 2, specifically comprising:
raw material cost:
Figure FDA0003351369330000024
wherein the content of the first and second substances,
Figure FDA0003351369330000025
represents the fixed cost of importing raw material i from domestic base n at time t;
Figure FDA0003351369330000026
representing a binary variable, if the raw material i is imported from a domestic base n in the period t, the value is 1, otherwise, the value is 0;
Figure FDA0003351369330000027
represents the cost of raw material i imported from domestic base n during time t;
Figure FDA0003351369330000028
represents the quantity of raw material i imported from the domestic base n at the time t;
Figure FDA0003351369330000029
represents the fixed cost of importing a part j from a domestic base n at time t;
Figure FDA00033513693300000210
representing a binary variable, which is 1 if the part j is imported from the domestic base n in the period t, or 0 if not;
Figure FDA00033513693300000211
represents the cost of the change of import of parts j from domestic base n at time t;
Figure FDA00033513693300000212
representing the number of imported parts j from domestic base n during time t;
Figure FDA00033513693300000213
represents the fixed cost of purchasing parts j from overseas base k at time t;
Figure FDA00033513693300000214
represents a binary variable, which is 1 if part j is purchased from overseas base k at time t, and 0 otherwise;
Figure FDA0003351369330000031
represents the varying cost of purchasing parts j from overseas base k at time t,
Figure FDA0003351369330000032
representing the number of purchased parts j from overseas base k at time t;
transportation cost:
Figure FDA0003351369330000033
wherein the content of the first and second substances,
Figure FDA0003351369330000034
represents a fixed cost of transporting a piece j from a domestic base n to an overseas base k in a transport manner g over a period of time t; x is the number ofjnkgtRepresents the fluctuating cost of transporting a piece j from a domestic base n to an overseas base k over a period of time t in a transport mode g.
4. The overseas purchase order optimization method of claim 3, wherein the tax coupon policy requirements in S3 include:
Figure FDA0003351369330000035
wherein, yiRepresenting the local localization purchase amount of the raw material i from overseas; qiRepresents the total demand of the enterprise for raw material i, and Qi＝xi+yi，xiRepresenting the purchase amount of the raw material i from a domestic base; miThe requirement of the tax policy on the minimum amount of the raw material i in the local procurement is expressed.
5. The overseas procurement order optimization method of any one of claims 1 to 4, wherein in S4, the overseas procurement order optimization model is solved by using an NSGA-II algorithm.
6. A system for overseas purchase order optimization taking into account carbon emission constraints during transportation, comprising:
the information acquisition module is used for acquiring enterprise production information;
the condition presetting module is used for presetting carbon emission constraint conditions in the transportation process corresponding to the enterprise purchasing plan;
the model construction module is used for constructing an overseas purchase order optimization model considering both economic and environmental targets according to the enterprise production information and the carbon emission constraint conditions in the transportation process on the premise of meeting the tax discount policy requirements;
and the order optimization module is used for determining the amounts of the materials purchased respectively to the inside or the outside for the manufacturing enterprise overseas production base by adopting a multi-objective genetic algorithm according to the overseas purchase order optimization model constructed by the previous module, namely determining the optimized overseas purchase order.
7. The overseas purchase order optimization system of claim 6, wherein the overseas purchase order optimization model comprises,
an objective function that considers both economic objectives with minimal procurement costs and environmental objectives with minimal transportation environmental impact:
an objective function that considers both economic objectives with minimal procurement costs and environmental objectives with minimal transportation environmental impact:
Figure FDA0003351369330000041
Figure FDA0003351369330000042
Figure FDA0003351369330000043
Figure FDA0003351369330000044
wherein E islRepresents the jth cost; l represents the number of cost categories; FTE represents carbon emission cost; TE represents the actual carbon emission; c. Cco2Is a standard discharge unit price, cexDischarge price for the over-standard part, qsThe maximum allowable discharge amount;
Figure FDA0003351369330000045
represents the fixed environmental impact of the shipment of a part j from a domestic base n to a overseas base k in a shipment manner g at a time t;
Figure FDA0003351369330000046
represents the unit variable environmental impact of the shipment of a part j from a domestic base n to a overseas base k in a shipment manner g at a time t;
Figure FDA0003351369330000047
representing a binary variable, if the part j is transported from the domestic base n to the overseas base k in the transport mode g in the time t period, the value is 1, otherwise, the value is 0; xjnkgtRepresenting the number of corresponding transported parts j;
Figure FDA0003351369330000051
represents the maximum cost of the parts j to be transported from the domestic base n to the overseas base k in the transport mode g during the time t;
the cost category number is 2, and specifically includes:
raw material cost:
Figure FDA0003351369330000052
wherein the content of the first and second substances,
Figure FDA0003351369330000053
represents the fixed cost of importing raw material i from domestic base n at time t;
Figure FDA0003351369330000054
representing a binary variable, if the raw material i is imported from a domestic base n in the period t, the value is 1, otherwise, the value is 0;
Figure FDA0003351369330000055
means that the raw material is imported from the domestic base n at the time tA cost of variation of i;
Figure FDA0003351369330000056
represents the quantity of raw material i imported from the domestic base n at the time t;
Figure FDA0003351369330000057
represents the fixed cost of importing a part j from a domestic base n at time t;
Figure FDA0003351369330000058
representing a binary variable, which is 1 if the part j is imported from the domestic base n in the period t, or 0 if not;
Figure FDA0003351369330000059
represents the cost of the change of import of parts j from domestic base n at time t;
Figure FDA00033513693300000510
representing the number of imported parts j from domestic base n during time t;
Figure FDA00033513693300000511
represents the fixed cost of purchasing parts j from overseas base k at time t;
Figure FDA00033513693300000512
represents a binary variable, which is 1 if part j is purchased from overseas base k at time t, and 0 otherwise;
Figure FDA00033513693300000513
represents the varying cost of purchasing parts j from overseas base k at time t,
Figure FDA00033513693300000514
representing the number of purchased parts j from overseas base k at time t;
transportation cost:
Figure FDA00033513693300000515
wherein the content of the first and second substances,
Figure FDA00033513693300000516
represents a fixed cost of transporting a piece j from a domestic base n to an overseas base k in a transport manner g over a period of time t; x is the number ofjnkgtRepresents the fluctuating cost of transporting a piece j from a domestic base n to an overseas base k over a period of time t in a transport mode g.
8. The overseas purchase order optimization system of claim 6, wherein the tax coupon policy requirements include:
Figure FDA0003351369330000061
wherein, yiRepresenting the local localization purchase amount of the raw material i from overseas; qiRepresents the total demand of the enterprise for raw material i, and Qi＝xi+yi，xiRepresenting the purchase amount of the raw material i from a domestic base; miThe requirement of the tax policy on the minimum amount of the raw material i in the local procurement is expressed.
9. A storage medium storing a computer program for overseas purchase order optimization taking into account carbon emission constraints during transportation, wherein the computer program causes a computer to perform the overseas purchase order optimization method according to any one of claims 1 to 5.
10. An electronic device, comprising:
one or more processors;
a memory; and
one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the programs comprising instructions for performing the overseas purchase order optimization method of any of claims 1-5.
CN202111338345.4A 2021-11-12 2021-11-12 Overseas purchase order optimization method considering carbon emission constraint in transportation process Pending CN114239908A (en)

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116049627A (en) * 2023-01-04 2023-05-02 暨南大学 Carbon emission estimation method and device for ocean transportation industry

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116049627A (en) * 2023-01-04 2023-05-02 暨南大学 Carbon emission estimation method and device for ocean transportation industry
CN116049627B (en) * 2023-01-04 2023-10-03 暨南大学 Carbon emission estimation method and device for ocean transportation industry

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