CN111738542A - Reliability analysis method for social life cycle evaluation of complex product - Google Patents
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Abstract
The invention provides a reliability analysis method for social life cycle evaluation of a complex product, which relates to the field of reliability analysis methods and is characterized in that quantitative and qualitative data are represented under a unified frame by applying an effective uncertainty evaluation method, a unified data representation form represented by confidence distribution is used for solving the actual decision problem of the social life cycle evaluation reliability analysis of the complex product, and the confidence distribution evaluation differences among different indexes and the internal uncertainty evaluated on each index are considered at the same time, so that a method for analyzing the reliability of the evaluation result is provided, and the reliability of the result is analyzed from two aspects; the invention can express quantitative and qualitative data under a unified frame, and analyze the reliability of the fusion result from the source aiming at the question of a decision maker, thereby realizing the analysis of reliability measurement values of different data forms under the unified frame.
Description
Technical Field
The invention relates to the technical field of social life cycle evaluation methods, in particular to a reliability analysis method for social life cycle evaluation of a complex product.
Background
The complex product refers to a large-scale industrial product or system which is produced by a single piece or small batch of customization, such as an aviation aircraft system, a high-end numerical control device, a rail transit device, a complex electromechanical product and the like, and has the advantages of complex structure, high research and development cost, complex manufacturing process, high knowledge and technology content. Social Life Cycle Assessment (Social Life Cycle Assessment/S-LCA) is a technique for assessing Social effects of a product in a whole Life Cycle from the exploitation and processing of raw materials to the production, sale, use, maintenance, recycling, remanufacturing and final disposal of the product. The method comprises four steps of target and range definition, life cycle list analysis, life cycle influence evaluation and interpretation. As the industry related to the complex products is an important support for national economy and national defense safety, and the social life cycle evaluation of the complex products has important influence on the design, production and use of the complex products, the research on the reliability of the social life cycle evaluation of the complex products has great significance.
The data of the social life cycle evaluation of the complex product comes from all stakeholders, and not only contains a large amount of quantitative data of product equipment operation and the like, but also contains a large amount of qualitative data of subjective evaluation and the like. The existing research is analyzed from the perspective of a single frame of qualitative data or quantitative data and the like, most of researches on the reliability of evaluation results are realized by establishing a reliability evaluation index system based on a mathematical statistics method on the basis of an evaluation index represented by an accurate number, and the social life cycle evaluation results are analyzed by directly converting the qualitative data into the quantitative data.
The existing research on the reliability of the evaluation result is realized by establishing a reliability evaluation index system based on a mathematical statistics method on the basis of an evaluation index represented by an accurate number. In the conventional analysis of the reliability of decision results, the result of evaluation data is mostly an accurate number, the reliability of the result is generally analyzed by designing a reliability index by a mathematical statistics method, and the question of a decision maker about the reliability of a fusion result is not analyzed from the source. Most of researches only analyze from the perspective of a single frame such as qualitative data or quantitative data, while in the social life cycle evaluation method, not only a large amount of objective quantitative data but also more subjective qualitative data are involved, and if the qualitative data are directly converted into the quantitative data, information loss is caused, while in the existing researches, the qualitative data are represented in a form of confidence distribution, but few researches simultaneously represent the qualitative data and the quantitative data on a unified frame, and for the schemes with similar evaluation results, it is difficult to select the evaluation scheme with higher reliability from the perspective of the reliability of the results.
Disclosure of Invention
Technical problem to be solved
Aiming at the defects of the prior art, the invention provides a reliability analysis method for social life cycle evaluation of a complex product, and solves the problem that the existing analysis method is difficult to apply an effective uncertainty evaluation method to express quantitative and qualitative data under a unified framework.
(II) technical scheme
In order to achieve the purpose, the invention is realized by the following technical scheme:
a reliability analysis method for social life cycle evaluation of a complex product is characterized by comprising the following steps:
s1: acquiring a scheme of a multi-attribute decision-making MADM problem, and acquiring a primary evaluation index and an evaluation grade parameter of the multi-attribute decision-making MADM problem;
s2: dividing the preliminary evaluation index into a qualitative index and a quantitative index, wherein the qualitative index and the quantitative index are respectively expressed as evaluation indexes in a confidence distribution form;
s3: constructing a confidence distribution decision matrix under the evaluation level of the MADM problem based on the scheme, the evaluation index and the evaluation level parameter of the MADM problem;
s4: calculating the average confidence distribution difference of the scheme of the MADM problem under all evaluation indexes and the average uncertainty of the confidence distribution of the scheme of the MADM problem on all evaluation indexes based on a confidence distribution decision matrix;
s5: the confidence degrees of all indexes under the scheme of each MADM problem are aggregated through an evidence reasoning method, so that a total confidence distribution evaluation value of the scheme of each MADM problem is obtained;
s6: determining an evaluation result by combining the difference degree and the average uncertainty of the average confidence distribution on all the evaluation indexes, wherein the evaluation result is the reliability of the total confidence distribution;
s7: and comparing the reliability of the total confidence distribution, and selecting a social life cycle evaluation scheme of the complex product with high reliability and large evaluation value of the total confidence distribution.
Preferably, the scheme for acquiring the MADM problem in step S1 includes: abstracting the social life cycle evaluation problem of the complex product into an MADM problem, and setting a scheme of the MADM problem.
Preferably, the step S1 of acquiring the preliminary evaluation index and the evaluation level parameter includes:
s101: determining the purpose, range, stakeholders and subcategories of social life cycle evaluation of the complex product;
s102: and determining a preliminary evaluation index and an evaluation grade parameter according to the stakeholders and the subcategories.
Preferably, the evaluation indexes, in which the qualitative index and the quantitative index are respectively expressed in the form of confidence distribution in step S2, include: the grading mode of the qualitative index is to design an expert grading table and utilize the internet big data to carry out sentiment classification, and the evaluation confidence coefficient distribution data on the formed grade is the evaluation index of the confidence distribution form; the evaluation data formed by the quantitative indexes is from traditional channels such as enterprise research, existing databases, social statistics and the like, and the confidence coefficient distribution data formed on the unified recognition framework through conversion is the evaluation indexes in the confidence distribution form.
Preferably, the step S3 of obtaining the confidence distribution decision matrix under the evaluation level of the MADM problem includes:
s301: expressing the evaluation indexes in the form of the evaluation grade and the confidence distribution by the following modes: the social life cycle evaluation problem of the complex product comprises S schemes expressed as: a ═ a1，a2，...，al，...，aS}; there are L evaluation indices, expressed as: e ═ E1，e2，...，ei，...，eL}; evaluated on N evaluation scales, expressed as: h ═ H1，H2，...，Hn，...，HNIn which H isn+1＞Hn；
S302: evaluation of confidence distribution data S (e) at each evaluation level for different solutions in the MADM problemi(al))＝{(Hn，βn，i(al))，n＝1，2，…，N；(H，βH，i(al) in which is beta is used)n，i(al) For scheme alIn the evaluation index eiIs evaluated to Hnconfidence of grade, βH，i(al) Representation scheme alIn the evaluation index eiAnd constructing a confidence distribution decision matrix [ S (e) ]i(al))]S×L；
S303: and performing matrixing representation on the obtained decision matrix:
wherein each column represents a confidence distribution evaluation vector of a different scheme on a particular evaluation index, using S (e)i(A) (i ═ 1, 2.. times, L), each row representing the confidence distribution evaluation vector for a particular protocol under different evaluation criteria, using S (E (a)l) And (l ═ 1, 2,, S) represents.
Preferably, the calculating of the average confidence distribution differences of different evaluation indexes in the scheme of the MADM problem in step S4 includes calculating the average confidence distribution differences based on the confidence distribution differences of different evaluation indexes, and calculating the confidence distribution differences among different evaluation indexes includes:
s401: according to the scheme alLower eiAnd ej(i ≠ j) the Hamming distance of the confidence degrees of the indexes on different levels is multiplied by the Hamming distance of the utility on the corresponding level, the results are accumulated and summed and then multiplied by the utility difference factor, and therefore the scheme a is calculatedlLower eiAnd ejConfidence distribution difference value D (e) between indexesij(al) Equation) is as follows:
wherein, betan，|i-j|(al)＝|βn，i(al)-βn，j(al)|；u(H|s-n|)＝|u(Hs)-u(Hn)|；
Is a utility difference factor to ensure D (e)ij(al) ) has a maximum value of 1 and a minimum value of 0;
s402: and (3) performing matrixing representation on the difference values:
preferably, the calculating the mean confidence distribution difference of the solution of the MADM problem under all the evaluation indexes in step S4 includes:
scheme alMean confidence distribution difference D (a) over L evaluation indicesl) The formula is as follows:
wherein the content of the first and second substances,
for performing on the difference valueAveraging to obtain a scheme alThe difference value of the mean confidence distribution of pairwise comparison between different evaluation indexes.
Preferably, the method for calculating the mean uncertainty of the confidence distribution of the solution of the MADM problem in all the evaluation indexes in step S4 includes: calculating the uncertainty of the confidence distribution, and calculating the average uncertainty of the confidence distribution on the evaluation index based on the uncertainty of the confidence distribution, wherein the uncertainty calculation method of the confidence distribution comprises the following steps: according to the scheme alIn the evaluation index eiAnd calculating the uncertainty of the confidence distribution by multiplying the cumulative sum of the products of the confidence degrees on the different evaluation levels and the utility difference on the corresponding level by a utility difference factor, wherein the formula is as follows:
preferably, the method for calculating the mean uncertainty of the confidence distribution in step S4 includes: carrying out averaging processing on the uncertainty of the confidence distribution evaluation on all the evaluation indexes to obtain a scheme alThe average uncertainty under L evaluation indices is given by the following formula:
preferably, the reliability of the evaluation result, i.e. the total confidence distribution, determined in step S6 is calculated by: the decision maker gives the average confidence distribution difference value and the weight W of the average uncertainty result according to the preference of subjective uncertainty and objective difference1、W2Wherein W is1+W21 is ═ 1; calculating the total reliability measure of the evaluation result, wherein the formula is as follows:
Cre(al)＝1-(W1*Un(al)+W2*D(al))
Cre(al) Represents a pair of schemes alThe evaluated reliability metric of (2). Cre (a)l) The larger the value of (A), the scheme alThe greater the reliability of the evaluation of (a) and vice versa.
(III) advantageous effects
The invention provides a reliability analysis method for social life cycle evaluation of a complex product. Compared with the prior art, the method has the following beneficial effects:
1. the invention applies an effective uncertainty evaluation method to represent quantitative and qualitative data in a unified frame, uses a unified data representation form represented by confidence distribution aiming at the practical decision problem of the evaluation reliability analysis of the social life cycle of a complex product, and simultaneously considers the confidence distribution evaluation difference among different indexes and the internal uncertainty evaluated on each index, thereby providing a method for analyzing the reliability of the evaluation result, and analyzing the reliability of the result from two aspects: the uncertainty caused by the objective difference of the scheme is determined by the distance of original confidence distribution data among the indexes and the utility difference of each grade; the uncertainty caused by the confidence distribution of the data is evaluated inside the specific index. Finally, the overall reliability of the evaluation is determined based on these two factors. Therefore, the invention can express quantitative and qualitative data under a unified frame, and analyze the reliability of the fusion result from the source aiming at the question of a decision maker, thereby realizing the analysis of reliability measurement values of different data forms under the unified frame.
2. Aiming at the defects of the traditional method, the invention provides a method for measuring the difference value of confidence distribution among indexes, and the difference value is used as an objective factor influencing the reliability of an evaluation result; by considering the internal uncertainty of the confidence distribution evaluation of the utility difference factor, the average uncertainty of the confidence evaluation of the scheme on all indexes is calculated, and the average uncertainty is used as a subjective factor influencing the reliability of the decision result, so that the social life cycle evaluation method of the complex product is perfected.
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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 flowchart of a reliability analysis method for social life cycle evaluation of a complex product 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 solves the problem that an effective uncertainty evaluation method is difficult to express quantitative and qualitative data in a unified frame by providing a reliability analysis method for social life cycle evaluation of complex products, realizes the expression of the quantitative and qualitative data in the unified frame, and analyzes the reliability of a fusion result from a source according to the question of a decision maker on the reliability of the fusion result.
In order to solve the technical problems, the general idea of the embodiment of the application is as follows:
the embodiment of the invention provides a method for analyzing and evaluating the reliability of the result by representing quantitative and qualitative data under a unified frame, using a unified data representation form represented by confidence distribution and considering the confidence distribution evaluation difference among different indexes and the internal uncertainty evaluated on each index aiming at the actual decision problem of the social life cycle evaluation reliability analysis of complex products. Therefore, quantitative and qualitative data are represented in a unified framework, and the reliability of the fusion result is analyzed from the source according to the question of a decision maker.
For better understanding of the above technical solutions, the following detailed descriptions will be provided in conjunction with the drawings and the detailed description of the embodiments.
A reliability analysis method for social life cycle evaluation of a complex product is characterized by comprising the following steps:
s1: acquiring a scheme of a multi-attribute decision-making MADM problem, and acquiring a primary evaluation index and an evaluation grade parameter of the multi-attribute decision-making MADM problem;
s2: dividing the preliminary evaluation index into a qualitative index and a quantitative index, wherein the qualitative index and the quantitative index are respectively expressed as evaluation indexes in a confidence distribution form;
s3: constructing a confidence distribution decision matrix under the evaluation level of the MADM problem based on the scheme, the evaluation index and the evaluation level parameter of the MADM problem;
s4: calculating the average confidence distribution difference of the scheme of the MADM problem under all evaluation indexes and the average uncertainty of the confidence distribution of the scheme of the MADM problem on all evaluation indexes based on a confidence distribution decision matrix;
s5: the confidence degrees of all indexes under each scheme in the MADM problem are aggregated through an evidence reasoning method, so that a total confidence distribution evaluation value of each scheme in the MADM problem is obtained;
s6: determining an evaluation result by combining the difference degree and the average uncertainty of the average confidence distribution on all the evaluation indexes, wherein the evaluation result is the reliability of the total confidence distribution;
s7: and comparing the reliability of the total confidence distribution, and selecting a social life cycle evaluation scheme of the complex product with high reliability and large evaluation value of the total confidence distribution.
The invention applies an effective uncertainty evaluation method to represent quantitative and qualitative data in a unified frame, uses a unified data representation form represented by confidence distribution aiming at the practical decision problem of the evaluation reliability analysis of the social life cycle of a complex product, and simultaneously considers the confidence distribution evaluation difference among different indexes and the internal uncertainty evaluated on each index, thereby providing a method for analyzing the reliability of the evaluation result, and analyzing the reliability of the result from two aspects: the uncertainty caused by the objective difference of the scheme is determined by the distance of original confidence distribution data among the indexes and the utility difference of each grade; the uncertainty caused by the confidence distribution of the data is evaluated inside the specific index. Finally, the overall reliability of the evaluation is determined based on these two factors. Therefore, the invention can express quantitative and qualitative data under a unified frame, and analyze the reliability of the fusion result from the source aiming at the question of a decision maker, thereby realizing the analysis of reliability measurement values of different data forms under the unified frame.
Aiming at the defects of the traditional method, the invention provides a method for measuring the difference value of confidence distribution among indexes, and the difference value is used as an objective factor influencing the reliability of an evaluation result; by considering the internal uncertainty of the confidence distribution evaluation of the utility difference factor, the average uncertainty of the confidence evaluation of the scheme on all indexes is calculated, and the average uncertainty is used as a subjective factor influencing the reliability of the decision result, so that the social life cycle evaluation method of the complex product is perfected.
The individual steps are described in detail below:
in step S1, acquiring the MADM question includes: abstracting the social life cycle evaluation problem of the complex product into an MADM problem, and setting a scheme of the MADM problem.
The acquisition of the preliminary evaluation index and the evaluation level parameter in step S1 includes:
s101: determining the purpose, range, stakeholders and subcategories of social life cycle evaluation of the complex product;
s102: and determining a preliminary evaluation index and an evaluation grade parameter according to the stakeholders and the subcategories.
TABLE 1 evaluation index system for social life cycle of complex products
The evaluation indexes in which the qualitative index and the quantitative index are respectively expressed in the form of confidence distribution in step S2 include: the grading mode of the qualitative index is to design an expert grading table and utilize the internet big data to carry out sentiment classification, and the evaluation confidence coefficient distribution data on the formed grade is the evaluation index of the confidence distribution form; and the evaluation data formed by the quantitative indexes is converted into confidence coefficient distribution data on a unified recognition framework, and the confidence coefficient distribution data is the evaluation indexes in a confidence distribution form.
The step S3 of obtaining the confidence distribution decision matrix under the evaluation level of the MADM problem includes:
s301: expressing the evaluation indexes in the form of the evaluation grade and the confidence distribution by the following modes: the social life cycle evaluation problem of the complex product comprises S schemes expressed as: a ═ a1，a2，...，ai，...，as}; there are L evaluation indices, expressed as: e ═ E1，e2，...，ei，...，eL}; evaluated on N evaluation scales, expressed as: h ═ H1，H2，...，Hn，...，HNIn which H isn+1＞Hn；
S302: evaluation of confidence distribution data S (e) at each evaluation level for different solutions in the MADM problemi(al))＝{(Hn，βn，i(al))，n＝1，2，…，N；(H，βH，i(al) in which is beta is used)n，i(al) For scheme alAt index eiIs evaluated to Hnconfidence of grade, βH，i(al) Representation scheme alAt index eiAnd constructing a confidence distribution decision matrix [ S (e) ]i(al))]s×L；
S303: and performing matrixing representation on the obtained decision matrix:
wherein each column represents a confidence distribution evaluation vector for a different solution on a particular target, using S (e)i(A) (i ═ 1, 2.., L) and each row represents the confidence score of a particular solution under different criteriaEvaluating the vector with S (E (a)l) And (l ═ 1, 2,, S) represents.
The difference measurement method between confidence distributions considering utility difference is mainly used for difference calculation between schemes or between experts, the difference between indexes is not involved, and the maximum value or the minimum value of the difference is influenced by the value of the utility value and is not necessarily 1 or 0. In addition, the traditional measure for the difference between the indexes is mainly used for analyzing the relative importance degree of the indexes, and the difference between the indexes is rarely considered to have an important influence on the reliability of the evaluation result. Therefore, aiming at the defects of the traditional method, the invention provides a method for measuring the difference value of confidence distribution among indexes, and the difference value is used as an objective factor influencing the reliability of an evaluation result.
In step S4, calculating the average confidence distribution differences of different evaluation indexes under the scheme of the MADM problem, and then calculating the average confidence distribution differences of different evaluation indexes, where calculating the confidence distribution differences among different evaluation indexes includes:
s401: according to the scheme alLower eiAnd ej(i ≠ j) the Hamming distance of the confidence degrees of the indexes on different levels is multiplied by the Hamming distance of the utility on the corresponding level, the results are accumulated and summed and then multiplied by the utility difference factor, and therefore the scheme a is calculatedlLower eiAnd ejConfidence distribution difference value D (e) between indexesij(al) Equation) is as follows:
wherein, betan，|i-j|(al)＝|βn，i(al)-βn，j(al)|；u(H|s-n|)＝|u(Hs)-u(Hn)|；
Is a utility difference factor to ensure D (e)ij(al) ) has a maximum value of 1 and a minimum value of 0.
S402: and (3) performing matrixing representation on the difference values:
the calculation of the mean confidence distribution difference of the solution of the MADM problem under all indexes in step S4 is performed by:
scheme alMean confidence distribution variance value D (a) over L indicatorsl) The formula is as follows:
wherein the content of the first and second substances,
for averaging the difference values to obtain a scheme alThe mean confidence distribution difference values of pairwise comparisons between different indexes.
The invention provides an internal uncertainty measurement method for confidence distribution evaluation by considering utility difference factors, so that the average uncertainty of confidence evaluation of a scheme on all indexes is calculated and used as a subjective factor influencing the reliability of a decision result.
The method for calculating the mean uncertainty of the confidence distribution of the scheme of the MADM problem on all the evaluation indexes in step S4 includes: calculating the uncertainty of the confidence distribution, and calculating the average uncertainty of the confidence distribution on the evaluation index based on the uncertainty of the confidence distribution, wherein the uncertainty calculation method of the confidence distribution comprises the following steps: according to the scheme alAt index eiAnd calculating the uncertainty of the confidence distribution by multiplying the cumulative sum of the products of the confidence degrees on the different evaluation levels and the utility difference on the corresponding level by a utility difference factor, wherein the formula is as follows:
mean uncertainty of confidence distribution in step S4The calculation method comprises the following steps: carrying out averaging processing on the uncertainty of the confidence distribution evaluation on all indexes to obtain a scheme alThe average uncertainty under L indices is given by the following formula:
the reliability of the evaluation result, i.e., the overall confidence distribution, is determined in step S6 to be calculated by: the decision maker gives the average confidence distribution difference value and the weight W of the average uncertainty result according to the preference of subjective uncertainty and objective difference1、W2Wherein W is1+W21 is ═ 1; calculating the total reliability measure of the evaluation result, wherein the formula is as follows:
Cre(al)＝1-(W1*Un(al)+W2*D(al))
Cre(al) Represents a pair of schemes alThe evaluated reliability metric of (2). Cre (a)l) The larger the value of (A), the scheme alThe greater the reliability of the evaluation of (a) and vice versa.
In summary, compared with the prior art, the method has the following beneficial effects:
1. the invention applies an effective uncertainty evaluation method to represent quantitative and qualitative data in a unified frame, uses a unified data representation form represented by confidence distribution aiming at the practical decision problem of the evaluation reliability analysis of the social life cycle of a complex product, and simultaneously considers the confidence distribution evaluation difference among different indexes and the internal uncertainty evaluated on each index, thereby providing a method for analyzing the reliability of the evaluation result, and analyzing the reliability of the result from two aspects: the uncertainty caused by the objective difference of the scheme is determined by the distance of original confidence distribution data among the indexes and the utility difference of each grade; the uncertainty caused by the confidence distribution of the data is evaluated inside the specific index. Finally, the overall reliability of the evaluation is determined based on these two factors. Therefore, the invention can express quantitative and qualitative data under a unified frame, and analyze the reliability of the fusion result from the source aiming at the question of a decision maker, thereby realizing the analysis of reliability measurement values of different data forms under the unified frame.
2. By knowing the characteristics of the evaluation data, the invention can enhance the trust degree of a decision maker on the evaluation result on one hand, and can select a decision scheme with higher reliability as a final scheme on the other hand under the condition that the scheme priority cannot be distinguished. The reliability of the final fusion result of each index is analyzed from two angles of the difference of confidence distribution data among the indexes and the uncertainty inside the confidence distribution data, so that the decision-making efficiency is improved.
3. Aiming at the defects of the traditional method, the invention provides a method for measuring the difference value of confidence distribution among indexes, and the difference value is used as an objective factor influencing the reliability of an evaluation result; by considering the internal uncertainty of the confidence distribution evaluation of the utility difference factor, the average uncertainty of the confidence evaluation of the scheme on all indexes is calculated, the average uncertainty is used as a subjective factor influencing the reliability of the decision result, and the social life cycle evaluation index system of the complex product is perfected.
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 reliability analysis method for social life cycle evaluation of a complex product is characterized by comprising the following steps:
s1: acquiring a scheme of a multi-attribute decision-making MADM problem, and acquiring a primary evaluation index and an evaluation grade parameter of the multi-attribute decision-making MADM problem;
s2: dividing the preliminary evaluation index into a qualitative index and a quantitative index, wherein the qualitative index and the quantitative index are respectively expressed as evaluation indexes in a confidence distribution form;
s3: constructing a confidence distribution decision matrix under the evaluation level of the MADM problem based on the scheme, the evaluation index and the evaluation level parameter of the MADM problem;
s4: calculating the average confidence distribution difference of the scheme of the MADM problem under all evaluation indexes and the average uncertainty of the confidence distribution of the scheme of the MADM problem on all evaluation indexes based on a confidence distribution decision matrix;
s5: the confidence degrees of all indexes under the scheme of each MADM problem are aggregated through an evidence reasoning method, so that a total confidence distribution evaluation value of the scheme of each MADM problem is obtained;
s6: determining an evaluation result by combining the difference degree and the average uncertainty of the average confidence distribution on all the evaluation indexes, wherein the evaluation result is the reliability of the total confidence distribution;
s7: and comparing the reliability of the total confidence distribution, and selecting a social life cycle evaluation scheme of the complex product with high reliability and large evaluation value of the total confidence distribution.
2. The method for reliability analysis of social life cycle assessment of complex products as claimed in claim 1, wherein the solution of obtaining the MADM problem in step S1 comprises: abstracting the social life cycle evaluation problem of the complex product into an MADM problem, and setting a scheme of the MADM problem.
3. The method for analyzing reliability of social life cycle evaluation of complex products according to claim 1, wherein the step S1 of obtaining the preliminary evaluation index and the evaluation level parameter comprises:
s101: determining the purpose, range, stakeholders and subcategories of social life cycle evaluation of the complex product;
s102: and determining a preliminary evaluation index and an evaluation grade parameter according to the stakeholders and the subcategories.
4. The method for analyzing reliability of social life cycle evaluation of complex products as claimed in claim 1, wherein the step S2, in which the qualitative index and the quantitative index are respectively expressed as evaluation indexes of confidence distribution form, comprises: the grading mode of the qualitative index is to design an expert grading table and utilize the internet big data to carry out sentiment classification, and the evaluation confidence coefficient distribution data on the formed grade is the evaluation index of the confidence distribution form; and the evaluation data formed by the quantitative indexes is converted into confidence coefficient distribution data on a unified recognition framework, and the confidence coefficient distribution data is the evaluation indexes in a confidence distribution form.
5. The method for analyzing reliability of social life cycle evaluation of complex products as claimed in claim 1, wherein the step S3 of obtaining the confidence distribution decision matrix under the evaluation level of the MADM problem comprises:
s301: expressing the evaluation indexes in the form of the evaluation grade and the confidence distribution by the following modes: the social life cycle evaluation problem of the complex product comprises S schemes expressed as: a ═ a1，a2，...，al，...，aS}; there are L evaluation indices, expressed as: e ═ E1，e2，...，ei，...，eL}; evaluated on N evaluation scales, expressed as: h ═ H1，H2，...，Hn，...，HNIn which H isn+1＞Hn；
S302: evaluation of confidence distribution data S (e) at each evaluation level for different solutions in the MADM problemi(al))＝{(Hn，βn，i(al))，n＝1，2，…，N；(H，βH，i(al) in which is beta is used)n，i(al) For scheme alIn the evaluation index eiIs evaluated to Hnconfidence of grade, βH，i(al) Representation scheme alIn the evaluation index eiAnd constructing a confidence distribution decision matrix [ S (e) ]i(al))]S×L；
S303: and performing matrixing representation on the obtained decision matrix:
wherein each column represents a confidence distribution evaluation vector of a different scheme on a particular evaluation index, using S (e)i(A) (i ═ 1, 2.. times, L), each row representing the confidence distribution evaluation vector for a particular protocol under different evaluation criteria, using S (E (a)l) And (l ═ 1, 2,, S) represents.
6. The method for analyzing reliability of social life cycle evaluation of complex products as claimed in claim 1, wherein the step S4 is implemented by calculating the difference of the mean confidence distributions of different evaluation indexes under the solution of the MADM problem, and the calculating the difference of the mean confidence distributions based on the difference of the confidence distributions of different evaluation indexes comprises:
s401: according to the scheme alLower eiAnd ej(i ≠ j) the Hamming distance of the confidence degrees of the indexes on different levels is multiplied by the Hamming distance of the utility on the corresponding level, the results are accumulated and summed and then multiplied by the utility difference factor, and therefore the scheme a is calculatedlLower eiAnd ejConfidence distribution difference value D (e) between indexesij(al) Equation) is as follows:
wherein, betan，|i-j|(al)＝|βn，i(al)-βn，j(al)|；u(H|s-n|)＝|u(Hs)-u(Hn)|；
Is a utility difference factor to ensure D (e)ij(al) ) has a maximum value of 1 and a minimum value of 0;
s402: and (3) performing matrixing representation on the difference values:
7. the method for analyzing reliability of social life cycle evaluation of complex products as claimed in claim 6, wherein the step S4 of calculating the mean confidence distribution difference of the solution of the MADM problem under all evaluation indexes comprises:
scheme alMean confidence distribution difference D (a) over L evaluation indicesl) The formula is as follows:
wherein the content of the first and second substances,
for averaging the difference values to obtain a scheme alThe difference value of the mean confidence distribution of pairwise comparison between different evaluation indexes.
8. The complex product society of claim 1The reliability analysis method for life cycle evaluation is characterized in that the method for calculating the mean uncertainty of the confidence distribution of the scheme of the MADM problem on all the evaluation indexes in the step S4 comprises the following steps: calculating the uncertainty of the confidence distribution, and calculating the average uncertainty of the confidence distribution on the evaluation index based on the uncertainty of the confidence distribution, wherein the uncertainty calculation method of the confidence distribution comprises the following steps: according to the scheme alIn the evaluation index eiAnd calculating the uncertainty of the confidence distribution by multiplying the cumulative sum of the products of the confidence degrees on the different evaluation levels and the utility difference on the corresponding level by a utility difference factor, wherein the formula is as follows:
9. the method for analyzing reliability of social life cycle evaluation of complex products according to claim 8, wherein the method for calculating the mean uncertainty of the confidence distribution in step S4 comprises: carrying out averaging processing on the uncertainty of the confidence distribution evaluation on all the evaluation indexes to obtain a scheme alThe average uncertainty under L evaluation indices is given by the following formula:
10. the method for analyzing reliability of social life cycle assessment of complex products according to claim 1, wherein the reliability of the overall confidence distribution, which is the assessment result determined in step S6, is calculated by: the decision maker gives the average confidence distribution difference value and the weight W of the average uncertainty result according to the preference of subjective uncertainty and objective difference1、W2Wherein W is1+W21 is ═ 1; calculating the total reliability measure of the evaluation result, wherein the formula is as follows:
Cre(al)＝1-(W1*Un(al)+W2*D(al))
Cre(al) Represents a pair of schemes alThe reliability measure of the evaluation of (1), Cre (a)l) The larger the value of (A), the scheme alThe greater the reliability of the evaluation of (a) and vice versa.
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