CN109165824A - A kind of appraisal procedure and system for critical workflow - Google Patents
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Abstract
This application involves a kind of appraisal procedure and system for critical workflow, the method is applied in the critical workflow of power distribution network, which comprises establishes hierarchy Model, and forms the judgment matrix compared two-by-two；The corresponding Maximum characteristic root of the judgment matrix and the corresponding feature vector of the Maximum characteristic root are solved, and consistency desired result is carried out to the Maximum characteristic root and described eigenvector, and weight vector is set according to check results；According to the weight vector of setting, right vector is calculated, and is combined consistency check；It determines the judge collection of each object, and the judge is collected respectively according to the right vector and carries out single factor test fuzzy evaluation and fuzzy comprehensive evoluation, to obtain the comprehensive descision vector of each object；Based on the comprehensive descision vector and opinion scale, the judge total value of each object is generated, and evaluation result is determined based on maximum membership grade principle.Technical solution provided by the present application can be improved the accuracy of assessment result.
Description
Technical field
This application involves technical field of data processing, in particular to a kind of appraisal procedure and system for critical workflow.
Background technique
In recent years, with the development of power distribution network power supply capacity and operation level appraisal, the problem of evaluation result is presented
Increasingly it reduces, but status distribution physical fault still continuously emerges with operational management problem.At the same time, living standards of the people are continuous
It improves, requirement of the user to power supply reliability and power quality is also higher and higher, and distribution network failure problem will directly affect use
Satisfaction of the family to electric service.
Currently, Appreciation gist is according to each pass to the evaluation of critical workflow primarily directed to the evaluation of process duration efficiency
The duration evaluation method of key process lacks the overall merit to entire critical workflow.Therefore, how online to entire critical workflow
Which monitoring and on-line evaluation, influence factor have, and is both needed to just can solve by the demonstration of science using which kind of algorithm etc..Meanwhile
In order to improve the universality of integrated evaluating method, it is necessary to proved repeatedly evaluation method, so as to by evaluation method
Other critical workflows are extended to, realize the scientific and reasonable evaluation of critical workflow business
Summary of the invention
The application's is designed to provide a kind of appraisal procedure and system for critical workflow, can be improved assessment result
Accuracy.
To achieve the above object, the application provides a kind of appraisal procedure for critical workflow, and the method is applied to match
In the critical workflow of power grid, which comprises
Hierarchy Model is established, and forms the judgment matrix compared two-by-two；
The corresponding Maximum characteristic root of the judgment matrix and the corresponding feature vector of the Maximum characteristic root are solved, and to institute
It states Maximum characteristic root and described eigenvector carries out consistency desired result, and weight vector is set according to check results；
According to the weight vector of setting, right vector is calculated, and is combined consistency check；
It determines the judge collection of each object, and the judge is collected respectively according to the right vector and carries out single factor test mould
Paste evaluation and fuzzy comprehensive evoluation, to obtain the comprehensive descision vector of each object；
Based on the comprehensive descision vector and opinion scale, the judge total value of each object is generated, and based on most
Big degree of membership principle determines evaluation result.
Further, the judgment matrix compared two-by-two is indicated by following formula:
A=(aij)n×n(i, j=1,2 ..., n)
In formula, aij=1/aji, n is constant, and A is the judgment matrix；
The judgment matrix is formed in the following way:
Since the 2nd layer of the hierarchy Model, for being subordinated to or influencing the same layer of upper one layer of each factor
In each factor, with Paired Comparisons and 1-9 scale Judgement Matricies, until lowest level.
Further, solve the corresponding Maximum characteristic root of the judgment matrix and the corresponding feature of the Maximum characteristic root to
Amount includes:
Each column of judgment matrix A are made into normalized, obtain normalization result
Seek the sum of each row element of judgment matrix A
It is rightIt is normalized to obtain wi:
According to Aw=λmaxW finds out Maximum characteristic root and its feature vector, wherein w wiThe vector of composition.
Further, it is determined that the judge collection of each object includes:
For given set of factors U, it is divided into n subset U1, U2..., Un, wherein the n son collection meets:
Then obtain the second level sets of factors (U1,U2,…,Un), whereinIndicate intersection element.
Further, progress single factor test fuzzy evaluation is collected to the judge and fuzzy comprehensive evoluation includes:
By U1It is split as Multiple factors: U1=U11,U12,,……U1K, wherein U1Each factor weight allocation vector P1By
Analytic hierarchy process (AHP) calculated result determines；
U1Comment gathers be combined into V1=(v1,v2,……,vv), wherein subscript v indicates comment set element number；
Determine the opinion scale set E=(e of each element in comment set1,e2,……,ev), and utilize the evaluation
Scale set is to U1Each element carry out single factor evaluation, obtain evaluations matrix Rj=(rj1,rj2,……,rjv), wherein rji
(i=1,2 ... ..., v) indicates that j-th of evaluation index gives viDegree of membership；
To U1As Comprehensive Evaluation, comprehensive evaluation matrix B can be obtained1:
B1=P1R=P1(R1,R2,……,Rk)T, wherein k indicates set of factors U1Middle evaluation index number.
Further, it is based on the comprehensive descision vector and opinion scale, generates the judge total value of each object,
And determine that evaluation result includes: based on maximum membership grade principle
To all schemes for participating in evaluation or evaluation object, according to Comprehensive Evaluation vector Uy=(u1,u2,……,uv) and comment
Valence scale E=(e1,e2,……,ev), the total score for calculating the fuzzy comprehensive estimation of each scheme is Sy=u1e1+u2e2+…+
uvev, then it is ranked up according to the height of total score, highest scoring person is optimal case or best evaluation object.
To achieve the above object, the application also provides a kind of assessment system for critical workflow, and the system is applied to
In the critical workflow of power distribution network, the system comprises:
Judgment matrix forms unit, for establishing hierarchy Model, and forms the judgment matrix compared two-by-two；
Weight vector setting unit, for solving the corresponding Maximum characteristic root of the judgment matrix and the Maximum characteristic root pair
The feature vector answered, and consistency desired result is carried out to the Maximum characteristic root and described eigenvector, and according to check results
Weight vector is set；
Consistency desired result unit calculates right vector for the weight vector according to setting, and is combined consistency inspection
It tests；
Comprehensive descision vector generation unit, for determining the judge collection of each object, and according to the right vector point
It is other that progress single factor test fuzzy evaluation and fuzzy comprehensive evoluation are collected to the judge, to obtain the comprehensive descision vector of each object；
Evaluation result determination unit, for being based on the comprehensive descision vector and opinion scale, it is described each right to generate
The judge total value of elephant, and evaluation result is determined based on maximum membership grade principle.
Further, the judgment matrix compared two-by-two is indicated by following formula:
A=(aij)n×n(i, j=1,2 ..., n)
In formula, aij=1/aji, n is constant, and A is the judgment matrix；
The judgment matrix forms unit and forms the judgment matrix in the following way:
Since the 2nd layer of the hierarchy Model, for being subordinated to or influencing the same layer of upper one layer of each factor
In each factor, with Paired Comparisons and 1-9 scale Judgement Matricies, until lowest level.
Further, the weight vector setting unit solves the corresponding maximum feature of the judgment matrix according to following formula
Root and the corresponding feature vector of the Maximum characteristic root:
Each column of judgment matrix A are made into normalized, obtain normalization result
Seek the sum of each row element of judgment matrix A
It is rightIt is normalized to obtain wi:
According to Aw=λmaxW finds out Maximum characteristic root and its feature vector, wherein w wiThe vector of composition.
Further, comprehensive descision vector generation unit determines the judge collection of each object according to following formula:
For given set of factors U, it is divided into n subset U1, U2..., Un, wherein the n son collection meets:
Then obtain the second level sets of factors (U1,U2,…,Un), whereinIndicate intersection element.
The present invention determines that each index weights are answered with combining for fuzzy evaluation Calculation Estimation matrix using analytic hierarchy process (AHP) (AHP)
Overall merit is carried out with the critical workflow in repairing distribution, so as to General Promotion distribution network construction and management level, is mentioned
Service satisfaction of the high user to power supply company.
Detailed description of the invention
Fig. 1 is the appraisal procedure flow chart that critical workflow is directed in the application；
Fig. 2 is the flow chart in the application in concrete application scene.
Specific embodiment
In order to make those skilled in the art better understand the technical solutions in the application, below in conjunction with the application reality
The attached drawing in mode is applied, the technical solution in the application embodiment is clearly and completely described, it is clear that described
Embodiment is only a part of embodiment of the application, rather than whole embodiments.Based on the embodiment party in the application
Formula, all other embodiment obtained by those of ordinary skill in the art without making creative efforts, is all answered
When the range for belonging to the application protection.
Referring to Fig. 1, the application provides a kind of appraisal procedure for critical workflow, the method is applied to power distribution network
In critical workflow, which comprises
S1: hierarchy Model is established, and forms the judgment matrix compared two-by-two；
S2: solving the corresponding Maximum characteristic root of the judgment matrix and the corresponding feature vector of the Maximum characteristic root, and
Consistency desired result is carried out to the Maximum characteristic root and described eigenvector, and weight vector is set according to check results；
S3: according to the weight vector of setting, right vector is calculated, and is combined consistency check；
S4: it determines the judge collection of each object, and the judge is collected respectively according to the right vector and carries out Dan Yin
Plain fuzzy evaluation and fuzzy comprehensive evoluation, to obtain the comprehensive descision vector of each object；
S5: it is based on the comprehensive descision vector and opinion scale, generates the judge total value of each object, and be based on
Maximum membership grade principle determines evaluation result
Referring to Fig. 2, in practical applications, can realize technical scheme by multiple detailed steps:
1, AHP evaluations matrix is constructed, and calculates the weight of each index
(1) hierarchy Model is established.On the basis of analysing in depth practical problem, by related each factor according to not
Resolve into several levels from top to down with attribute, the factors of same layer are subordinated to one layer of factor or to upper layer because being known as
It influences, while dominating next layer of factor or the effect by lower layer factors again.Top layer is destination layer, usually only 1 because
Element, lowest level are usually scheme or object layer, and centre can have one or several levels, usually criterion or indicator layer.Work as standard
Sub- rule layer should further be decomposited by (being for example more than 9) when then excessive.According to scaling theory, multilevel iudge matrix two-by-two is constructed
A:
A=(aij)n×n(i, j=1,2 ..., n)
In formula, aij=1, aij=1/aji
(2) Paired comparison matrix is constructed.It is one layer upper for being subordinated to (or influence) since the 2nd layer of hierarchy Model
The same layer factors of each factor compare dimensional configurations Paired comparison matrix with Paired Comparisons and 1-9, until lowest level.It will
Each column of judgment matrix A make normalized:
Seek the sum of each row element of judgment matrix A
It is rightIt is normalized to obtain wi:
According to Aw=λmaxW finds out Maximum characteristic root and its feature vector
(3) it calculates weight vector and does consistency check.Maximum characteristic root and correspondence are calculated for each Paired comparison matrix
Feature vector does consistency check using coincident indicator, random index and consistency ratio.It is special if upchecking
Levying vector (after normalization) is weight vector: if not passing through, need to reconfigure in pairs relatively battle array.Consistency check:
1. calculating coincident indicator:
2. finding out corresponding Aver-age Random Consistency Index: R.I.
3. calculating consistency ration: C.R.=C.I./R.I..As C.R. < 0.1, it is subjected to consistency check, it is otherwise right
A amendment.
(4) it calculates right vector and does combination consistency check.Lowest level is calculated to the right vector of target, and root
Combination consistency check is done according to formula, if upchecking, the result that can be indicated according to right vector carries out decision, otherwise needs
It rethinks model or reconfigures the biggish Paired comparison matrix of those consistency ratios.
2, by fuzzy synthetic appraisement method parameter value
When carrying out overall merit to complication system, due to Consideration is more and each factor between point that has levels, because
This will be preferred using AHP- fuzzy overall evaluation (multi_levels fuzzy evaluation) method.The specific steps of which are as follows:
(1) evaluation sub-goal collection U is established:
U=(U1,U2,…,Us)
(2) sub-goal weight-distributed set A is established according to the result that above-mentioned analytic hierarchy process (AHP) calculates:
A=(A1,A2,…,AS), and meet condition
(3) each sub-goal UiBy each index ui1,ui2,…,uikInfluence, then index set uiAre as follows:
ui=(ui1,ui2,…,uik) (i=1,2 ..., s)
(4) according to the calculated result of analytic hierarchy process (AHP), each index u is determinediWeight-distributed set wi:
wi=(wi1,wi2,…,wik)(i=1,2 ..., s)
(5) according to system status, several evaluate collections is selected to form an evaluation set:
V=(V1,V2,…,Vm)
(6) it asks several experts to evaluate each index by ballot, obtains evaluations matrix Ri:
(7) the overall merit vector B of each sub-goal is acquiredi:
Bi=wi Ri(i=1,2 ..., s)
(8) sub-goal evaluations matrix: B=(B is formed1, B2,…,Bs)T
(9) general objective evaluation vector C:C=AB is sought
(10) maximum membership degree is taken, system evaluation grade is obtained.
3, AHP- fuzzy synthetic appraisement method
AHP- model of fuzzy synthetic evaluation is mainly made of two parts, first part, analytic hierarchy process (AHP)；Second part,
Fuzzy overall evaluation.Wherein, fuzzy overall evaluation is carried out on the basis of analytic hierarchy process (AHP), and the two complements each other, jointly
Improve the reliability and validity of evaluation.
When carrying out overall merit to complication system, due to Consideration is more and each factor between point that has levels, because
This will be preferred using AHP- fuzzy overall evaluation (multi_levels fuzzy evaluation) method.The specific steps of which are as follows:
(1) set of factors item is established.Given set of factors U, makees division P to U, it is divided into n subset U1, U2..., Un, full
Sufficient U1+U2+……+Un=Un,The second level set of factors then can be obtained in i ≠ j (i, j=1,2 ... ..., n)
It closes:
U/P=(U1,U2,…,Un)
(2) single factor test fuzzy evaluation.U1=U11,U12,,……U1K, U1Each factor weight allocation vector P1By level point
Analysis method calculated result determines, it is assumed that U1Comment gathers be combined into V1=(v1,v2,……,vv) (subscript v indicates comment set element
Number), i.e. the Blur scale set of evaluation approach, such as it is good, preferable, medium, poor, poor；Each evaluation approach institute is provided simultaneously
Corresponding opinion scale E, i.e. (v1,v2,……,vv)=(e1,e2,……,ev).To U1Each evaluation index carry out single factor test
Evaluation, can be obtained evaluations matrix Rj=(rj1,rj2,……,rjv), wherein rji (i=1,2 ... ..., v), indicates j-th of evaluation
Index gives comment viDegree of membership.To U1As Comprehensive Evaluation, then comprehensive evaluation matrix can be obtained: B1=P1R=P1(R1,
R2,……,Rk)T, wherein K indicates set of factors U1Middle evaluation index number.
(3) fuzzy comprehensive evoluation.After carrying out overall merit to all factors of U/P, total evaluations matrix: B is just obtained
=(B1,B2,……,Bn)TIf the weight distribution of U/P is W, then to second level fuzzy Judgment vector are as follows: U=WB, wherein W is same
It is determined by analytic hierarchy process (AHP) calculated result.
According to above-mentioned steps, it is each right, which finally to obtain, to be judged to y judgment matrix object (i.e. participation in the election scheme)
The comprehensive descision vector of elephant: Uy=(u1,u2,……,uv)。
(4) numerical procedure priority.To all schemes for participating in evaluation or evaluation object, according to Comprehensive Evaluation vector Uy=
(u1,u2,……,uv) and opinion scale E=(u1,u2,……,uv)=(e1,e2,……,ev) the fuzzy of each scheme can be calculated
The total score of comprehensive descision is Sy=u1e1+u2e2+…+uvev, then it is ranked up according to the height of total score, highest scoring person
It is optimal for optimal case or evaluation goal.
4, model is verified
(1) AHP overall merit is verified
For the index system of above-mentioned building, the matrix of expert estimation is established, and calculates the weight of each index.
1. establishing recursive hierarchy structure；
2. constructing multilevel iudge matrix (positive reciprocal matrix) two-by-two.
For process progress dimension, judgment matrix is established are as follows:
1 process progress judgment matrix of table
In conjunction with the practical business of process progress, critical workflow is repaired for distribution, the different degree of each index is from high to low
Sequence successively are as follows: troubleshooting duration, reach live duration, order send that working hour is long, pays a return visit when filing duration and service handling
It is long.
The weight obtained are as follows:
2 process progress dimension weight of table
For flow quality class dimension, judgment matrix is established are as follows:
3 flow quality judgment matrix of table
In conjunction with the practical business of flow quality, critical workflow is repaired for distribution, the importance sorting of each index is successively
Are as follows: processing satisfaction, fault harm degree and troublshooting urgency level.
The weight obtained are as follows:
4 flow quality dimension weight of table
Class dimension is utilized for process resources, establishes judgment matrix are as follows:
5 process resources of table utilize judgment matrix
In conjunction with the practical business that process resources utilize, critical workflow, the importance sorting of each index are repaired for distribution
Successively are as follows: faulty equipment property right, the classification of processing scene and service languages.
The weight obtained are as follows:
6 process resources of table utilize dimension weight
Comprehensive three dimensions, judgment matrix are as follows:
7 process totality judgment matrix of table
Full-range practical business is repaired in conjunction with distribution, critical workflow, the different degree row of each index are repaired for distribution
Sequence is successively are as follows: flow quality, process resources utilize and process progress.
Obtain the weight of different dimensions are as follows:
8 critical workflow overall merit dimension weight of table
From analysis above results, it can be seen that under process progress dimension, the important ratio of troubleshooting duration compared with
It is high；Under flow quality dimension, the importance of customer satisfaction is relatively high；Process resources utilize under dimension, faulty equipment property right category
The importance of property is relatively high；All in all, the importance highest of flow quality dimension.That is to say, bright for critical workflow, business
Aspect needs the flow quality of control work order to determine the superiority and inferiority of work order overall flow.
Further, it is also possible to carry out fuzzy overall evaluation verifying.Specifically, it can be commented in conjunction with distribution repairing critical workflow synthesis
Each two-level index of valence, obtains the distribution situation of practical index value, then in conjunction with expert estimation the case where and combine AHP
The index value that weight and Field Using Fuzzy Comprehensive Assessment of each index calculated under different dimensions are calculated, it can be deduced that final
Evaluation of result.In terms of critical workflow overall merit is repaired in distribution, the end-to-end index of end of service is linked into according to client and is drawn
Then screening process progress, flow quality, process resources utilize dimension index to divider, recursive hierarchy structure are established, by judging square
Battle array parameter weight obtains evaluations matrix by expert estimation, and overall target weight and expert opinion obtain repairing work order
Comprehensive score.The comprehensive monitoring for realizing critical workflow can find repairing process implementation procedure by evaluation result in time
The problem of, the weak link for influencing troubleshooting satisfaction is excavated, for weak link, corresponding rectification is taken to arrange
It applies, further improves the comprehensive evaluation result of critical workflow comprehensively.
The application also provides a kind of assessment system for critical workflow, and the system is applied to the critical workflow of power distribution network
In, the system comprises:
Judgment matrix forms unit, for establishing hierarchy Model, and forms the judgment matrix compared two-by-two；
Weight vector setting unit, for solving the corresponding Maximum characteristic root of the judgment matrix and the Maximum characteristic root pair
The feature vector answered, and consistency desired result is carried out to the Maximum characteristic root and described eigenvector, and according to check results
Weight vector is set；
Consistency desired result unit calculates right vector for the weight vector according to setting, and is combined consistency inspection
It tests；
Comprehensive descision vector generation unit, for determining the judge collection of each object, and according to the right vector point
It is other that progress single factor test fuzzy evaluation and fuzzy comprehensive evoluation are collected to the judge, to obtain the comprehensive descision vector of each object；
Evaluation result determination unit, for being based on the comprehensive descision vector and opinion scale, it is described each right to generate
The judge total value of elephant, and evaluation result is determined based on maximum membership grade principle.
In the present embodiment, the judgment matrix compared two-by-two is indicated by following formula:
A=(aij)n×n(i, j=1,2 ..., n)
In formula, aij=1/aji, n is constant, and A is the judgment matrix；
The judgment matrix forms unit and forms the judgment matrix in the following way:
Since the 2nd layer of the hierarchy Model, for being subordinated to or influencing the same layer of upper one layer of each factor
In each factor, with Paired Comparisons and 1-9 scale Judgement Matricies, until lowest level.
In the present embodiment, the weight vector setting unit is corresponding most according to the following formula solution judgment matrix
Big characteristic root and the corresponding feature vector of the Maximum characteristic root:
Each column of judgment matrix A are made into normalized, obtain normalization result
Seek the sum of each row element of judgment matrix A
It is rightIt is normalized to obtain wi:
According to Aw=λmaxW finds out Maximum characteristic root and its feature vector, wherein w wiThe vector of composition.
In the present embodiment, comprehensive descision vector generation unit determines the judge collection of each object according to following formula:
For given set of factors U, it is divided into n subset U1, U2..., Un, wherein the n son collection meets:
Then obtain the second level sets of factors (U1,U2,…,Un), whereinIndicate intersection element.
The present invention determines that each index weights are answered with combining for fuzzy evaluation Calculation Estimation matrix using analytic hierarchy process (AHP) (AHP)
Overall merit is carried out with the critical workflow in repairing distribution, so as to General Promotion distribution network construction and management level, is mentioned
Service satisfaction of the high user to power supply company.
Those skilled in the art are supplied to the purpose described to the description of the various embodiments of the application above.It is not
It is intended to exhaustion or be not intended to and limit the invention to single disclosed embodiment.As described above, the application's is various
Substitution and variation will be apparent for above-mentioned technology one of ordinary skill in the art.Therefore, although specifically begging for
Some alternative embodiments are discussed, but other embodiment will be apparent or those skilled in the art are opposite
It is easy to obtain.The application is intended to include all substitutions of the invention discussed herein, modification and variation, and falls in
Other embodiment in the spirit and scope of above-mentioned application.
Claims (10)
1. a kind of appraisal procedure for critical workflow, which is characterized in that the method is applied in the critical workflow of power distribution network,
The described method includes:
Hierarchy Model is established, and forms the judgment matrix compared two-by-two；
Solve the corresponding Maximum characteristic root of the judgment matrix and the corresponding feature vector of the Maximum characteristic root, and to it is described most
Big characteristic root and described eigenvector carry out consistency desired result, and weight vector is arranged according to check results；
According to the weight vector of setting, right vector is calculated, and is combined consistency check；
It determines the judge collection of each object, and is commented according to the right vector is fuzzy to judge collection progress single factor test respectively
Valence and fuzzy comprehensive evoluation, to obtain the comprehensive descision vector of each object；
Based on the comprehensive descision vector and opinion scale, the judge total value of each object is generated, and is subordinate to based on maximum
Category degree principle determines evaluation result.
2. the method according to claim 1, wherein the judgment matrix compared two-by-two is indicated by following formula:
A=(aij)n×n(i, j=1,2 ..., n)
In formula, aij=1/aji, n is constant, and A is the judgment matrix；
The judgment matrix is formed in the following way:
Since the 2nd layer of the hierarchy Model, for being subordinated to or influencing in the same layer of upper one layer of each factor
Each factor, with Paired Comparisons and 1-9 scale Judgement Matricies, until lowest level.
3. according to the method described in claim 2, it is characterized in that, solving the corresponding Maximum characteristic root of the judgment matrix and institute
Stating the corresponding feature vector of Maximum characteristic root includes:
Each column of judgment matrix A are made into normalized, obtain normalization result
Seek the sum of each row element of judgment matrix A
It is rightIt is normalized to obtain wi:
According to Aw=λmaxW finds out Maximum characteristic root and its feature vector, wherein w wiThe vector of composition.
4. the method according to claim 1, wherein determining that the judge collection of each object includes:
For given set of factors U, it is divided into n subset U1, U2..., Un, wherein the n son collection meets:
Then obtain the second level sets of factors (U1,U2,…,Un), whereinIndicate intersection element.
5. according to the method described in claim 4, carrying out single factor test fuzzy evaluation it is characterized in that, collecting to the judge and obscuring
Comprehensive Evaluation includes:
By U1It is split as Multiple factors: U1=U11,U12,,……U1K, wherein U1Each factor weight allocation vector P1By level point
Analysis method calculated result determines；
U1Comment gathers be combined into V1=(v1,v2,……,vv), wherein subscript v indicates comment set element number；
Determine the opinion scale set E=(e of each element in comment set1,e2,……,ev), and utilize the opinion scale
Set is to U1Each element carry out single factor evaluation, obtain evaluations matrix Rj=(rj1,rj2,……,rjv), wherein rji (i=
1,2 ... ..., v), indicate that j-th of evaluation index gives viDegree of membership；
To U1As Comprehensive Evaluation, comprehensive evaluation matrix B can be obtained1:
B1=P1R=P1(R1,R2,……,Rk)T, wherein k indicates set of factors U1Middle evaluation index number.
6. being given birth to the method according to claim 1, wherein being based on the comprehensive descision vector and opinion scale
Determine that evaluation result includes: at the judge total value of each object, and based on maximum membership grade principle
To all schemes for participating in evaluation or evaluation object, according to Comprehensive Evaluation vector Uy=(u1,u2,……,uv) and evaluation ruler
Spend E=(e1,e2,……,ev), the total score for calculating the fuzzy comprehensive estimation of each scheme is Sy=u1e1+u2e2+…+uvev,
Then it is ranked up according to the height of total score, highest scoring person is optimal case or best evaluation object.
7. a kind of assessment system for critical workflow, which is characterized in that the system is applied in the critical workflow of power distribution network,
The system comprises:
Judgment matrix forms unit, for establishing hierarchy Model, and forms the judgment matrix compared two-by-two；
Weight vector setting unit, it is corresponding for solving the corresponding Maximum characteristic root of the judgment matrix and the Maximum characteristic root
Feature vector, and consistency desired result is carried out to the Maximum characteristic root and described eigenvector, and be arranged according to check results
Weight vector；
Consistency desired result unit calculates right vector for the weight vector according to setting, and is combined consistency check；
Comprehensive descision vector generation unit, for determining the judge collection of each object, and it is right respectively according to the right vector
The judge collection carries out single factor test fuzzy evaluation and fuzzy comprehensive evoluation, to obtain the comprehensive descision vector of each object；
Evaluation result determination unit generates each object for being based on the comprehensive descision vector and opinion scale
Total value is judged, and evaluation result is determined based on maximum membership grade principle.
8. system according to claim 7, which is characterized in that the judgment matrix compared two-by-two is indicated by following formula:
A=(aij)n×n(i, j=1,2 ..., n)
In formula, aij=1/aji, n is constant, and A is the judgment matrix；
The judgment matrix forms unit and forms the judgment matrix in the following way:
Since the 2nd layer of the hierarchy Model, for being subordinated to or influencing in the same layer of upper one layer of each factor
Each factor, with Paired Comparisons and 1-9 scale Judgement Matricies, until lowest level.
9. system according to claim 8, which is characterized in that the weight vector setting unit solves institute according to following formula
State the corresponding Maximum characteristic root of judgment matrix and the corresponding feature vector of the Maximum characteristic root:
Each column of judgment matrix A are made into normalized, obtain normalization result
Seek the sum of each row element of judgment matrix A
It is rightIt is normalized to obtain wi:
According to Aw=λmaxW finds out Maximum characteristic root and its feature vector, wherein w wiThe vector of composition.
10. system according to claim 7, which is characterized in that comprehensive descision vector generation unit is true according to following formula
Determine the judge collection of each object:
For given set of factors U, it is divided into n subset U1, U2..., Un, wherein the n son collection meets:
Then obtain the second level sets of factors (U1,U2,…,Un), whereinIndicate intersection element.
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