CN113792913A - Freight service optimization method, system, apparatus, and medium considering carbon emission compensation - Google Patents
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Abstract
The invention discloses a freight service optimization method, a system, a device and a medium considering carbon emission compensation, wherein the method comprises the following steps: through a highway toll system, carrying out parameter recording on annual traffic information of the goods transport vehicles registered on the case on the highway; annual inspection information of all cargo transport vehicles is obtained through a database; acquiring the emission reduction condition of a cargo transportation enterprise; constructing a fuzzy comprehensive evaluation model according to the recorded parameters, annual inspection information and emission reduction conditions, and dividing the green freight implementation condition of the freight transportation enterprise into a plurality of levels according to the fuzzy comprehensive evaluation model; awarding or penalizing different levels of freight forwarders. The method is based on multi-source data, completes the evaluation of green freight of enterprises by comprehensive quantitative analysis methods such as fuzzy comprehensive evaluation and the like, performs corresponding compensation or punishment measures on the highway toll and carbon emission after completing quantitative evaluation, and can be widely applied to the fields of transportation and environmental protection.
Description
Technical Field
The invention relates to the field of transportation and environmental protection, in particular to a freight service optimization method, a system, a device and a medium considering carbon emission compensation.
Background
In the energy consumption of the whole national economy, the consumption proportion of cargo transportation is large, and the proportion of the cargo transportation is gradually increased in recent years, while the proportion of the cargo transportation is the largest due to the advantages of flexibility and convenience of road transportation. The method actively promotes new energy vehicles and researches energy-saving and emission-reducing technologies, but is still in the starting stage at present. In addition, due to the insufficient knowledge of transportation energy conservation and emission reduction and the imperfect logistics information system, the energy conservation and emission reduction pressure under the goals of carbon peak reaching and carbon neutralization is still huge for freight enterprises.
Disclosure of Invention
To at least partially solve one of the technical problems in the prior art, an object of the present invention is to provide a freight service optimization method, system, device and medium considering carbon emission compensation.
The technical scheme adopted by the invention is as follows:
a freight service optimization method considering carbon emission compensation, comprising the steps of:
through a highway toll system, carrying out parameter recording on annual traffic information of the goods transport vehicles registered on the case on the highway;
annual inspection information of all cargo transport vehicles is obtained through a database;
acquiring the emission reduction condition of a cargo transportation enterprise;
constructing a fuzzy comprehensive evaluation model according to the recorded parameters, annual inspection information and emission reduction conditions, and dividing the green freight implementation condition of the freight transportation enterprise into a plurality of levels according to the fuzzy comprehensive evaluation model;
awarding or penalizing different levels of freight forwarders.
Further, the recorded parameters should include: the vehicle license plate number, the time when the vehicle enters the highway, the weight when the vehicle enters the highway, the time when the vehicle leaves the highway and the driving mileage of the vehicle;
the annual inspection information comprises the license plate number of the vehicle, the type of the vehicle, whether annual inspection is qualified or not, a freshness coefficient and the technical grade of the vehicle;
the emission reduction situation comprises: the method comprises the following steps of planning a special green freight, executing relevant green freight regulations, training drivers on energy conservation and emission reduction, applying energy conservation and emission reduction technologies and constructing and using a green freight informatization platform.
Further, the indices calculated from the highway toll system include: average vehicle speed vtAnd a vehicle load ratio wp：
Average vehicle speed vtCalculated by the following formula:
wherein s is the mileage of the vehicle on the highway, and toTime of exit of vehicle from expressway, tiThe time for the vehicle to drive into the highway;
the vehicle load ratio is calculated by:
wherein, wtIs the total mass of the vehicle, ws、wrThe dead weight of the vehicle and the vehicle verification load mass are respectively.
Further, the establishing of the fuzzy comprehensive evaluation model according to the recorded parameters, annual inspection information and emission reduction conditions comprises the following steps:
1) determining evaluation factors and evaluation grades:
let U be { U ═ U1,u2,…,umM evaluation indexes of an evaluated object; v ═ V1,v2,…,vmN evaluation grades for each factor;
2) constructing a judgment matrix and determining weights:
judging the single factor in the factor set, and judging the factor uiChoice grade vj(j ═ 1,2, …, n) with a degree of membership rijI factor uiThe single factor evaluation set is as follows:
ri＝(ri1，ri2，…，rin，)
constructing a total evaluation matrix R by the evaluation sets of the m factors; fuzzy relation R from U to V for each evaluation object:
wherein r isijIs a factor uiIs rated as vjDegree of membership of, i.e. rijRepresents the ith factor uiFrequency distribution on the jth comment normalized to satisfy ∑ rij1 is ═ 1; each evaluation factor has different weight in the comprehensive evaluation, and a fuzzy subset A on U is introduced and is called as weight, wherein A is (a)1,a2,…,am) Wherein a isi> 0, and ∑ ai＝1；
3) Fuzzy synthesis and comprehensive evaluation are carried out:
different rows in the evaluation matrix R reflect the membership degree of an evaluated object to the fuzzy subsets at each level from different single factors, and the membership degree of the evaluated object to the fuzzy subsets at each level on the whole, namely a fuzzy comprehensive evaluation result vector, can be obtained by integrating the different rows by using the fuzzy vector A; introducing a fuzzy subset B on V, called fuzzy evaluation, i.e. B ═ B1,b2,…,bn) (ii) a Let B be a R, which is called fuzzy transformation.
Further, dividing the green freight implementation of the freight transportation enterprises into 4 levels, and giving rewards or punishments to the freight transportation enterprises of different levels comprises:
1) for enterprises with green freight evaluation level of the first level, giving the highway traffic fee x of the first year thereon1Proportional abatement and giving it an annual carbon emission quota y1A reward for a proportion;
2) for green freight, enterprise with second grade of evaluation gradeIndustry, giving the highway the first year of it a toll of x2Proportional abatement and giving it an annual carbon emission quota y2A reward for a proportion;
3) for enterprises with the green freight evaluation level of the third level, no exemption or punishment is given to the highway toll fee, and no exemption or punishment is given to the carbon emission quota;
4) for enterprises with green freight evaluation level of fourth level, giving highway traffic fee x for the enterprises in the first year3Punishment in proportion and giving annual carbon emission quota y on the punishment3And (4) punishment of proportion.
Further, for all freight transportation enterprises, the carbon emission trading market can be entered for carbon emission trading:
for the freight transportation enterprises with surplus carbon emission indexes, selling surplus carbon emission quotas of the enterprises on the market;
for the goods transportation enterprises with the shortage of carbon emission indexes, the carbon emission quotas of other enterprises are purchased in the market.
Further, the freight service optimization method considering carbon emission compensation further includes the steps of:
and acquiring a priority weight matrix of the importance of each index in the evaluation method and the scoring rules of each index by the experts through a Delphi method.
The other technical scheme adopted by the invention is as follows:
a freight service optimization system that accounts for carbon emissions compensation, comprising:
the driving data acquisition module is used for carrying out parameter recording on annual traffic information of the goods transport vehicles registered on the case on the expressway through the expressway toll collection system;
the annual inspection data acquisition module is used for acquiring annual inspection information of all the cargo transport vehicles through the database;
the enterprise data acquisition module is used for acquiring the emission reduction condition of the freight transportation enterprise;
the enterprise grade division module is used for constructing a fuzzy comprehensive evaluation model according to the recorded parameters, annual inspection information and emission reduction conditions, and dividing the green freight implementation condition of the freight transportation enterprise into a plurality of grades according to the fuzzy comprehensive evaluation model;
and the enterprise rewarding and punishing module is used for giving rewards or punishments to the cargo transportation enterprises of different levels.
The other technical scheme adopted by the invention is as follows:
a freight service optimization device considering carbon emission compensation, comprising:
at least one processor;
at least one memory for storing at least one program;
when executed by the at least one processor, cause the at least one processor to implement the method described above.
The other technical scheme adopted by the invention is as follows:
a storage medium having stored therein a processor-executable program for performing the method as described above when executed by a processor.
The invention has the beneficial effects that: the evaluation of green freight of enterprises is completed by comprehensive quantitative analysis methods such as fuzzy comprehensive evaluation and the like based on multi-source data, and qualitative or single quantitative methods in the traditional energy-saving emission-reduction evaluation method are abandoned; in addition, corresponding compensation or punishment measures are carried out on the highway toll and the carbon emission after the quantitative evaluation is finished, a powerful constraint effect can be formed on the freight transportation enterprises, and the method has actual popularization value.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following description is made on the drawings of the embodiments of the present invention or the related technical solutions in the prior art, and it should be understood that the drawings in the following description are only for convenience and clarity of describing some embodiments in the technical solutions of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to these drawings without creative efforts.
FIG. 1 is a flow chart of the steps of a freight service optimization method in accordance with an embodiment of the present invention that takes into account carbon emissions compensation;
FIG. 2 is a flow chart illustrating a method for service optimization of green shipments with carbon emissions compensation in accordance with an embodiment of the present invention;
FIG. 3 is a schematic diagram of a fuzzy comprehensive evaluation model framework in an embodiment of the present invention.
Detailed Description
Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the accompanying drawings are illustrative only for the purpose of explaining the present invention, and are not to be construed as limiting the present invention. The step numbers in the following embodiments are provided only for convenience of illustration, the order between the steps is not limited at all, and the execution order of each step in the embodiments can be adapted according to the understanding of those skilled in the art.
In the description of the present invention, it should be understood that the orientation or positional relationship referred to in the description of the orientation, such as the upper, lower, front, rear, left, right, etc., is based on the orientation or positional relationship shown in the drawings, and is only for convenience of description and simplification of description, and does not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and thus, should not be construed as limiting the present invention.
In the description of the present invention, the meaning of a plurality of means is one or more, the meaning of a plurality of means is two or more, and larger, smaller, larger, etc. are understood as excluding the number, and larger, smaller, inner, etc. are understood as including the number. If the first and second are described for the purpose of distinguishing technical features, they are not to be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated or implicitly indicating the precedence of the technical features indicated.
In the description of the present invention, unless otherwise explicitly limited, terms such as arrangement, installation, connection and the like should be understood in a broad sense, and those skilled in the art can reasonably determine the specific meanings of the above terms in the present invention in combination with the specific contents of the technical solutions.
As shown in fig. 1 and 2, the present embodiment provides a freight service optimization method considering carbon emission compensation, including the steps of:
s1, acquiring a priority weighting matrix of the importance of each index in the assessment method by the expert through the Delphi method, and scoring detailed rules of each index.
According to the hierarchical structure of the system, a judgment matrix obtained by applying a Delphi method to solicit opinions is used for determining the priority weights between every two adjacent layers and reflecting the relative importance of each factor, and the consistency of the judgment matrix is checked. Meanwhile, a Delphi method is applied to obtain the scoring detailed rules of each index.
And S2, recording the annual traffic information of the goods transportation vehicles registered on the scheme through the highway toll system.
Recording the annual passing information of the goods transportation vehicles registered on the record on the expressway through an expressway toll system, wherein the recorded parameters comprise: the license plate number of the vehicle, the time when the vehicle enters the highway, the weight when the vehicle enters the highway, the time when the vehicle leaves the highway and the driving mileage of the vehicle.
For highway toll systems, the following assumptions are set up:
1) the highway toll collection system can accurately identify the passing information such as the license plate number of the vehicle, the time of the vehicle entering the highway, the weight of the vehicle entering the highway, the time of the vehicle leaving the highway, the driving mileage of the vehicle and the like.
2) The goods transportation enterprise vehicles are updated in the database in real time after being registered and put on record by the vehicle management system.
The indices calculated by the highway toll system include: average vehicle speed vtAnd a vehicle load ratio wp：
Average vehicle speed vtCan be calculated by the following formula:
where s is the distance traveled by the vehicle on the highway and toTime of exit of vehicle from expressway, tiThe above parameters can be directly obtained by the highway toll system for the time when the vehicle drives into the highway.
The vehicle load ratio can be calculated by:
wherein wtThe total mass of the vehicle can be directly obtained by a highway toll system, ws、wrThe vehicle dead weight and the vehicle verification and load determination mass are respectively obtained through a vehicle transportation and administration library.
Wherein the average running speed v of the vehicletAnd a vehicle load ratio wpThe method is used for comparing the average running speed and the vehicle carrying ratio of a certain vehicle with the values of the two parameters under the most energy-saving condition.
And S3, acquiring annual inspection information of all the cargo transportation vehicles through the database.
The annual inspection information of all the freight transportation vehicles is acquired through databases such as a transportation administration library and the like, and the annual inspection information comprises the following steps: license plate number of vehicle, vehicle type, whether annual inspection is qualified, novelty coefficient and vehicle technical grade.
And S4, acquiring the emission reduction condition of the goods transportation enterprise.
The method is characterized in that the visit investigation is carried out on goods transportation enterprises home by home, and the following aspects of the enterprises are mainly known: the method comprises the following steps of planning a special green freight, executing relevant green freight regulations, training drivers on energy conservation and emission reduction, applying energy conservation and emission reduction technologies and constructing and using a green freight informatization platform.
Collecting enterprise-related data through a visit survey:
for collecting enterprise-related data, the following assumptions are made:
1) the data of the enterprise visiting investigation is real and reliable, and no human factor interference exists.
2) The expert opinions are anonymous and true and reliable.
The visit survey needs to check whether enterprises can provide special green freight planning or not, whether green freight related systems can be provided or not, whether energy-saving and emission-reducing related technologies are applied or not, and whether green freight informatization platforms are built or added or not, and for related responsible persons and freight drivers, the mastering degree and the implementation degree of energy-saving and emission-reducing knowledge of the relevant responsible persons and the freight drivers can be investigated by adopting an examination method.
S5, constructing a fuzzy comprehensive evaluation model according to the recorded parameters, annual inspection information and emission reduction conditions, and dividing the green freight implementation condition of the freight transportation enterprise into a plurality of levels according to the fuzzy comprehensive evaluation model.
As shown in fig. 3, a fuzzy comprehensive evaluation model is constructed according to the recorded parameters, the annual survey information and the emission reduction situation, wherein in the process of constructing the fuzzy comprehensive evaluation model, the recorded parameters (i.e. B1 in the framework of fig. 3), the annual survey information (i.e. B2 in the framework of fig. 3) and the emission reduction situation (i.e. B3 in the framework of fig. 3) are subdivided into C1-C11 (eleven sub-factors) for modeling, and the specific steps are as follows:
1) and determining an evaluation factor and an evaluation grade. Let U be { U ═ U1,u2，…，umM evaluation indexes of an evaluated object; v ═ V1，v2，…，vmN evaluation grades for each factor. Here, m is the number of evaluation factors, i.e., the index number; n is the number of the comments and is generally divided into 3-5 grades, and the method is divided into 4 grades, namely good, general and poor.
2) Constructing a judgment matrix and determining weights. Firstly, single factor evaluation is carried out on single factors in a factor set, and the factor uiChoice grade vj(j ═ 1,2, …, n) with a degree of membership rijI factor uiThe single factor evaluation set is as follows:
ri＝(ri1，ri2，…，rin，)
the evaluation set of m factors constructs the overall evaluation matrix R. Fuzzy relation R from U to V for each evaluation object:
wherein r isijIs a factor uiIs rated as vjDegree of membership of, i.e. rijRepresents the ith factor uiFrequency distribution on the jth comment normalized to satisfy ∑ rij1. Therefore, the R matrix has no dimension and does not need to be subjected to dimensionless processing. Each evaluation factor has different weight in the comprehensive evaluation, and a fuzzy subset A on U is introduced and is called as weight, wherein A is (a)1,a2,…,am) Wherein a isi> 0, and ∑ ai＝1。
3) Fuzzy synthesis and comprehensive evaluation are carried out. Different rows in the R reflect the membership degree of a certain evaluated object to the fuzzy subsets of each level from different single factors, and the membership degree of the evaluated object to the fuzzy subsets of each level on the whole, namely the fuzzy comprehensive evaluation result vector, can be obtained by integrating the different rows by using the fuzzy vector A. Introducing a fuzzy subset B on V, called fuzzy evaluation or decision set, i.e. B ═ B1，b2，…，bn). Let B ═ a × R (×) be the operator symbol, called fuzzy transformation.
And S6, awarding rewards or punishments to the freight transportation enterprises with different levels.
Enterprises with good evaluation results and better grades can give a certain proportion of expense reduction based on the freight transportation expense of the highway in the last year, the carbon emission quota in the current year is increased in a certain proportion on the basis of the last year, and redundant quota can be used for the enterprises to trade in the carbon emission trading market; enterprises with poor evaluation results need to punish certain proportion on the basis of the freight transportation cost of the highway in the last year, and the carbon emission quota in the current year is reduced in a certain proportion on the basis of the last year.
Enterprises with different green freight evaluation levels are awarded with different levels of fees and carbon emission quotas or penalties as follows:
1) for the enterprises with green freight rating of 'good', giving the highway traffic fee x for the previous year1Proportional abatement and giving it an annual carbon emission quota y1A reward for the ratio.
2) For the enterprises with green freight rating of 'better', giving the highway traffic fee x for the previous year2Proportional abatement and giving it an annual carbon emission quota y2A reward for the ratio.
3) For enterprises with green freight rating "general", no exemption or penalty is given to highway tolls, nor to carbon emission quotas.
4) For the enterprises with green freight rating of 'poor', giving the highway traffic fee x for the first year3Punishment in proportion and giving annual carbon emission quota y on the punishment3And (4) punishment of proportion.
By the method, data acquisition and quantitative evaluation can be carried out on the green freight transportation implementation condition of the freight transportation enterprise from multiple dimensions, the implementation condition of the green freight transportation of the enterprise can be accurately mastered, corresponding carbon emission compensation and reward and punishment measures are proposed, better energy conservation and emission reduction of the freight transportation enterprise can be effectively promoted, and the freight transportation enterprise can be transferred to the green freight transportation direction.
The above method is explained in detail with reference to specific examples below.
As shown in fig. 2, the present embodiment provides a service optimization method for green freight with carbon emission compensation taken into account, and the data obtained in the present experimental example all satisfy: the highway toll collection system can accurately identify the passing information such as the license plate number of the vehicle, the time of the vehicle entering the highway, the weight of the vehicle entering the highway, the time of the vehicle leaving the highway, the driving mileage of the vehicle and the like; secondly, the goods transportation enterprise vehicles can be updated in real time in the database after being registered and recorded by the vehicle management system; the visiting survey data of the enterprise is real and reliable, and no interference of human factors exists; fourthly, the expert opinions are anonymous, real and reliable; and fifthly, the enterprises freely trade in the carbon emission market and accord with the trading rules.
Through a Delphi method, a priority weight matrix (shown in table 1) of the importance of each index in the evaluation method and a scoring rule (shown in table 2) of each index are obtained by experts:
TABLE 1 priority weightings of importance of individual indices
TABLE 2 detailed index points
Assuming the presence of cargo-moving vehicles 1-10, and units A, B, C, D, E and F, the vehicles 1-10 belong to the units A-F, respectively, and the highway toll records for the vehicles 1-10 in the last year are shown in Table 3:
TABLE 3 freight vehicle highway toll record
Annual inspection information of the vehicle operation administration library can be acquired as shown in table 4:
TABLE 4 annual inspection information of freight vehicle transportation administration warehouse
Based on the indexes and rules in step S1, the scores obtained by the respective enterprises are shown in table 5:
TABLE 5 index data or scores (examples) for each unit
| Scoring item | Unit A | Unit B | Unit C | Unit D | Unit E | Unit F |
| C1. Average running speed (km/h) of vehicle | 62.2 | 53.4 | 53.2 | 56.4 | 58.4 | 70 |
| C2. Vehicle load ratio (%) | 81 | 52 | 38 | 47 | 32 | 40 |
| C3. New energy vehicle proportion (%) | 50 | 50 | 0 | 66.67 | 100 | 0 |
| C4. Annual inspection qualification rate (%) | 100 | 100 | 100 | 100 | 100 | 100 |
| C5. Coefficient of vehicle newness | 0.78 | 0.84 | 0.98 | 0.57 | 0.85 | 0.58 |
| C6. Technical grade of vehicle | 100 | 100 | 100 | 66.67 | 100 | 100 |
| C7. Green freight special planning situation | 85 | 74 | 98 | 88 | 62 | 80 |
| C8. Green freight related system execution situation | 88 | 89 | 85 | 97 | 99 | 65 |
| C9. For the condition of energy-saving and emission-reducing training of drivers | 71 | 84 | 86 | 88 | 90 | 92 |
| C10. Application situation of energy-saving emission-reducing technology | 86 | 88 | 82 | 98 | 90 | 77 |
| C11. Green freight informatization platform use condition | 87 | 88 | 88 | 85 | 87 | 88 |
And (3) constructing a fuzzy comprehensive evaluation model by combining the information in the tables 1-5, wherein the specific construction steps are as follows:
1) and determining an evaluation factor and an evaluation grade. Let U be { U ═ U1，u2，…，umM evaluation indexes of an evaluated object; v ═ V1，V2,…，vmN evaluation grades for each factor. Here, m is the number of evaluation factors, i.e., the index number; n is the number of the comments and is generally divided into 3-5 grades, and the method is divided into 4 grades, namely good, general and poor.
2) Constructing a judgment matrix and determining weights. Firstly, single factor evaluation is carried out on single factors in a factor set, and the factor uiChoice grade vj(j ═ 1,2, …, n) with a degree of membership rijI factor uiThe single factor evaluation set is as follows:
ri＝(ri1，ri2，…，rin，)
the evaluation set of m factors constructs the overall evaluation matrix R. Fuzzy relation R from U to V for each evaluation object:
wherein r isijIs a factor uiIs rated as vjDegree of membership of, i.e. rijRepresents the ith factor uiFrequency distribution on the jth comment normalized to satisfy ∑ rij1. Therefore, the R matrix has no dimension and does not need to be subjected to dimensionless processing. Each evaluation factor has different weight in the comprehensive evaluation, and a fuzzy subset A on U is introduced and is called as weight, wherein A is (a)1，a2，…，am) Wherein a isi> 0, and ∑ ai＝1。
3) Fuzzy synthesis and comprehensive evaluation are carried out. Different rows in the R reflect the membership degree of a certain evaluated object to the fuzzy subsets of each level from different single factors, and the membership degree of the evaluated object to the fuzzy subsets of each level as a whole can be obtained by integrating the different rows by using the fuzzy vector A, namely the fuzzy comprehensive evaluationAnd (6) a result vector. Introducing a fuzzy subset B on V, called fuzzy evaluation or decision set, i.e. B ═ B1,b2,…,bn). Let B ═ a × R (×) be the operator symbol, called fuzzy transformation.
Based on the fuzzy comprehensive evaluation model, the enterprise is rated, and the rating result is shown in table 6:
TABLE 6 fuzzy comprehensive evaluation result and reward and punishment of green freight unit (example)
In summary, the above is provided. The embodiment is based on a mode that various means such as automatic detection of a highway toll system, annual vehicle inspection and enterprise visit are combined, and green freight conditions of freight transportation enterprises are evaluated through methods such as fuzzy comprehensive evaluation, so that enterprises with carbon emission standards meeting requirements and strong energy-saving and emission-reduction awareness are exempted from freight transportation cost, carbon emission quotas of the next year are increased, penalties of the freight transportation cost are given to the freight transportation enterprises which do not meet the emission requirements, and the carbon emission quotas of the next year are reduced. Carbon emission quotas may be traded between enterprises. The invention can reduce the carbon emission of cargo transportation enterprises, improve the energy-saving and emission-reducing awareness of the enterprises and drivers, simultaneously assist the popularization of new energy vehicles, and has practical popularization value.
The present embodiment also provides a freight service optimization system considering carbon emission compensation, including:
the driving data acquisition module is used for carrying out parameter recording on annual traffic information of the goods transport vehicles registered on the case on the expressway through the expressway toll collection system;
the annual inspection data acquisition module is used for acquiring annual inspection information of all the cargo transport vehicles through the database;
the enterprise data acquisition module is used for acquiring the emission reduction condition of the freight transportation enterprise;
the enterprise grade division module is used for constructing a fuzzy comprehensive evaluation model according to the recorded parameters, annual inspection information and emission reduction conditions, and dividing the green freight implementation condition of the freight transportation enterprise into a plurality of grades according to the fuzzy comprehensive evaluation model;
and the enterprise rewarding and punishing module is used for giving rewards or punishments to the cargo transportation enterprises of different levels.
The freight service optimization system considering carbon emission compensation of the embodiment can execute the freight service optimization method considering carbon emission compensation provided by the method embodiment of the invention, can execute any combination of the implementation steps of the method embodiment, and has corresponding functions and beneficial effects of the method.
The present embodiment also provides a freight service optimization apparatus considering carbon emission compensation, including:
at least one processor;
at least one memory for storing at least one program;
when executed by the at least one processor, cause the at least one processor to implement the method shown in fig. 1.
The freight service optimization device considering carbon emission compensation of the embodiment can execute the freight service optimization method considering carbon emission compensation provided by the method embodiment of the invention, can execute any combination of the implementation steps of the method embodiment, and has corresponding functions and beneficial effects of the method.
The embodiment of the application also discloses a computer program product or a computer program, which comprises computer instructions, and the computer instructions are stored in a computer readable storage medium. The computer instructions may be read by a processor of a computer device from a computer-readable storage medium, and executed by the processor to cause the computer device to perform the method illustrated in fig. 1.
The present embodiment also provides a storage medium storing instructions or a program that can execute a freight service optimization method considering carbon emission compensation according to an embodiment of the method of the present invention, and when the instructions or the program are executed, the steps can be performed in any combination of the embodiments of the method, and the corresponding functions and advantages of the method can be achieved.
In alternative embodiments, the functions/acts noted in the block diagrams may occur out of the order noted in the operational illustrations. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality/acts involved. Furthermore, the embodiments presented and described in the flow charts of the present invention are provided by way of example in order to provide a more thorough understanding of the technology. The disclosed methods are not limited to the operations and logic flows presented herein. Alternative embodiments are contemplated in which the order of various operations is changed and in which sub-operations described as part of larger operations are performed independently.
Furthermore, although the present invention is described in the context of functional modules, it should be understood that, unless otherwise stated to the contrary, one or more of the described functions and/or features may be integrated in a single physical device and/or software module, or one or more functions and/or features may be implemented in a separate physical device or software module. It will also be appreciated that a detailed discussion of the actual implementation of each module is not necessary for an understanding of the present invention. Rather, the actual implementation of the various functional modules in the apparatus disclosed herein will be understood within the ordinary skill of an engineer, given the nature, function, and internal relationship of the modules. Accordingly, those skilled in the art can, using ordinary skill, practice the invention as set forth in the claims without undue experimentation. It is also to be understood that the specific concepts disclosed are merely illustrative of and not intended to limit the scope of the invention, which is defined by the appended claims and their full scope of equivalents.
The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
The logic and/or steps represented in the flowcharts or otherwise described herein, e.g., an ordered listing of executable instructions that can be considered to implement logical functions, can be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions. For the purposes of this description, a "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device.
More specific examples (a non-exhaustive list) of the computer-readable medium would include the following: an electrical connection (electronic device) having one or more wires, a portable computer diskette (magnetic device), a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium could even be paper or another suitable medium upon which the program is printed, as the program can be electronically captured, via for instance optical scanning of the paper or other medium, then compiled, interpreted or otherwise processed in a suitable manner if necessary, and then stored in a computer memory.
It should be understood that portions of the present invention may be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, the various steps or methods may be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, any one or combination of the following techniques, which are known in the art, may be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application specific integrated circuit having an appropriate combinational logic gate circuit, a Programmable Gate Array (PGA), a Field Programmable Gate Array (FPGA), or the like.
In the foregoing description of the specification, reference to the description of "one embodiment/example," "another embodiment/example," or "certain embodiments/examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
While embodiments of the present invention have been shown and described, it will be understood by those of ordinary skill in the art that: various changes, modifications, substitutions and alterations can be made to the embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the claims and their equivalents.
While the preferred embodiments of the present invention have been illustrated and described, it will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention as defined by the appended claims.
Claims (10)
1. A freight service optimization method taking into account carbon emission compensation, comprising the steps of:
through a highway toll system, carrying out parameter recording on annual traffic information of the goods transport vehicles registered on the case on the highway;
annual inspection information of all cargo transport vehicles is obtained through a database;
acquiring the emission reduction condition of a cargo transportation enterprise;
constructing a fuzzy comprehensive evaluation model according to the recorded parameters, annual inspection information and emission reduction conditions, and dividing the green freight implementation condition of the freight transportation enterprise into a plurality of levels according to the fuzzy comprehensive evaluation model;
awarding or penalizing different levels of freight forwarders.
2. A method for freight service optimization with carbon emissions compensation in mind according to claim 1, wherein the recorded parameters include: the vehicle license plate number, the time when the vehicle enters the highway, the weight when the vehicle enters the highway, the time when the vehicle leaves the highway and the driving mileage of the vehicle;
the annual inspection information comprises the license plate number of the vehicle, the type of the vehicle, whether annual inspection is qualified or not, a freshness coefficient and the technical grade of the vehicle;
the emission reduction situation comprises: the method comprises the following steps of planning a special green freight, executing relevant green freight regulations, training drivers on energy conservation and emission reduction, applying energy conservation and emission reduction technologies and constructing and using a green freight informatization platform.
3. A method for freight service optimization with carbon emissions compensation in mind according to claim 2, wherein the metrics calculated from the highway toll system include: average vehicle speed vtAnd a vehicle load ratio wp：
Average vehicle speed vtCalculated by the following formula:
wherein s is the mileage of the vehicle on the highway, and toTime of exit of vehicle from expressway, tiThe time for the vehicle to drive into the highway;
the vehicle load ratio is calculated by:
wherein, wtIs the total mass of the vehicle, ws、wrThe dead weight of the vehicle and the vehicle verification load mass are respectively.
4. The freight service optimization method considering carbon emission compensation according to claim 1, wherein the constructing of the fuzzy comprehensive evaluation model according to the recorded parameters, annual survey information and emission reduction conditions comprises:
1) determining evaluation factors and evaluation grades:
let U be { U ═ U1,u2,…,umM evaluation indexes of an evaluated object; v ═ V1,v2,…,vmN evaluation grades for each factor;
2) constructing a judgment matrix and determining weights:
judging the single factor in the factor set, and judging the factor uiChoice grade vj(j ═ 1,2, …, n) with a degree of membership rijI factor uiThe single factor evaluation set is as follows:
ri＝(ri1,ri2,…,rin,)
constructing a total evaluation matrix R by the evaluation sets of the m factors; fuzzy relation R from U to V for each evaluation object:
wherein r isijIs a factor uiIs rated as vjDegree of membership of, i.e. rijRepresents the ith factor uiFrequency distribution on the jth comment normalized to satisfy ∑ rij1 is ═ 1; each evaluation factor has different weight in the comprehensive evaluation, and a fuzzy subset A on U is introduced and is called as weight, wherein A is (a)1,a2,…,am) Wherein a isi> 0, and ∑ ai＝1；
3) Fuzzy synthesis and comprehensive evaluation are carried out:
different rows in the evaluation matrix R reflect the membership degree of an evaluated object to the fuzzy subsets at each level from different single factors, and the membership degree of the evaluated object to the fuzzy subsets at each level on the whole, namely a fuzzy comprehensive evaluation result vector, can be obtained by integrating the different rows by using the fuzzy vector A; introducing a fuzzy subset B on V, called fuzzy evaluation, i.e. B ═ B1,b2,…,bn)。
5. The method of claim 1, wherein the green freight transportation implementation of the freight transportation enterprises is divided into 4 levels, and the awarding or penalizing of the freight transportation enterprises of different levels comprises:
1) for enterprises with green freight evaluation level of the first level, giving the highway traffic fee x of the first year thereon1Proportional abatement and giving it an annual carbon emission quota y1A reward for a proportion;
2) for enterprises with green freight evaluation level of second level, giving highway traffic fee x for the enterprises in the first year2Proportional abatement and giving it an annual carbon emission quota y2A reward for a proportion;
3) for enterprises with the green freight evaluation level of the third level, no exemption or punishment is given to the highway toll fee, and no exemption or punishment is given to the carbon emission quota;
4) for enterprises with green freight evaluation level of fourth level, giving highway traffic fee x for the enterprises in the first year3Punishment of proportion and given to it for one yearCarbon emission quota y3And (4) punishment of proportion.
6. The method of claim 5, wherein for all freight transportation enterprises, the carbon emission trading market can be entered for carbon emission trading:
for the freight transportation enterprises with surplus carbon emission indexes, selling surplus carbon emission quotas of the enterprises on the market;
for the goods transportation enterprises with the shortage of carbon emission indexes, the carbon emission quotas of other enterprises are purchased in the market.
7. The carbon emission compensation-considered freight service optimization method according to claim 1, further comprising the steps of:
and acquiring a priority weight matrix of the importance of each index in the evaluation method and the scoring rules of each index by the experts through a Delphi method.
8. A freight service optimization system that accounts for carbon emissions compensation, comprising:
the driving data acquisition module is used for carrying out parameter recording on annual traffic information of the goods transport vehicles registered on the case on the expressway through the expressway toll collection system;
the annual inspection data acquisition module is used for acquiring annual inspection information of all the cargo transport vehicles through the database;
the enterprise data acquisition module is used for acquiring the emission reduction condition of the freight transportation enterprise;
the enterprise grade division module is used for constructing a fuzzy comprehensive evaluation model according to the recorded parameters, annual inspection information and emission reduction conditions, and dividing the green freight implementation condition of the freight transportation enterprise into a plurality of grades according to the fuzzy comprehensive evaluation model;
and the enterprise rewarding and punishing module is used for giving rewards or punishments to the cargo transportation enterprises of different levels.
9. A freight service optimization device considering carbon emission compensation, comprising:
at least one processor;
at least one memory for storing at least one program;
when executed by the at least one processor, cause the at least one processor to implement the method of any one of claims 1-7.
10. A storage medium having stored therein a program executable by a processor, wherein the program executable by the processor is adapted to perform the method of any one of claims 1-7 when executed by the processor.
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