CN102043870A - Method for evaluating and selecting optimal wiring route of electric locomotive - Google Patents

Abstract

The embodiment of the invention provides a method for evaluating and selecting the optimal wiring route of an electric locomotive, which comprises the following steps: establishing a wiring route selection index system model according to an analytic hierarchy process (AHP) to obtain a plurality of optional wiring routes, wherein the serial numbers of the optional wiring routes are k={1, 2,..., p}, the wiring route selection index system model comprises m types of evaluation indexes, and the serial numbers of the evaluation indexes are i={1, 2,..., m}; carrying out grey evaluation for the optimal wiring route selection on the optional wiring routes according to a grey model (GM) to obtain wiring index values corresponding to the optional wiring routes; and selecting the optional wiring route with the optimal wiring index value as the optimal wiring route. In the embodiment of the invention, the AHP and the GM are utilized, and the optimal wiring route is found out through comprehensive considerations before wiring, so that the design of the wiring route is unified, thereby shortening the design time and lowering the cost.

Description

The Evaluation and Selection method of the optimum routing path of electric locomotive

Technical field

The present invention relates to electric locomotive and make the field, relate in particular to the Evaluation and Selection method of the optimum routing path of a kind of electric locomotive.

Background technology

In manufacturing and designing the stage of electric locomotive, the design of the routing path of electric locomotive is very important, and the quality of wires design can badly influence the quality of electric locomotive product.The routing path design of electric locomotive is at present carried out according to some index usually, such as: electromagnetic compatibility degree, space interference degree, the cable boundling degree of crowding, cable length, wiring aesthetic measure, designer's tendency, client's specific requirement or the like.

But following problem often appears in the selection of existing routing path design easily:

1. it is too much that routing path is selected the index of institute's foundation, the routing path of different wires design's teacher designs also is not quite similar, and the wires design of general electric locomotive is because engineering is huge, generally all by several wiring installation's teacher work compounds, this routing path that just causes designing can not be accomplished unified, thereby prolonged design time, strengthened design cost.

2. locomotive routing path when maintenance or add-assembly is changeable, random big.Because the wiring thinking of former factory when repairing the needs wiring, is not understood in the mechanical repair plant; The wiring thinking of former factory is not understood by Railway Bureau yet when add-assembly equipment, to make locomotive maintenance and during add-assembly routing path changeable, random big.

Summary of the invention

At above-mentioned defective, the embodiment of the invention provides the Evaluation and Selection method of the optimum routing path of a kind of electric locomotive, and to find out optimum routing path, it is unified to make the routing path design accomplish, reduces design time and cost.

The embodiment of the invention provides the Evaluation and Selection method of the optimum routing path of a kind of electric locomotive, and this method comprises: (Analytic Hierarchy Process AHP) sets up routing path and selects the index system model according to analytical hierarchy process, obtain a plurality of optional routing paths, the sequence number of described optional routing path is k={1,2 ... p}, comprise m class evaluation index in the described routing path selection index system model, the sequence number of described evaluation index is i={1,2,, m}; According to gray model GM described a plurality of optional routing paths are carried out the grey evaluation that optimum routing path is selected, obtain wiring exponential quantity corresponding to described a plurality of optional routing paths; The described optional routing path of choosing described wiring exponential quantity optimum is optimum routing path.

Preferably, according to gray model GM described a plurality of optional routing paths are carried out the grey evaluation that optimum routing path is selected in the embodiment of the invention, obtain comprising: the evaluation information matrix of setting up described evaluation index corresponding to the wiring exponential quantity of described a plurality of optional routing paths; Determine to estimate grey class j={1 according to actual conditions, 2 ..., the grey number of the grade of g}, grey class j is with the albefaction weight function f of grey class j ash number _jDetermine the importance degree of described evaluation index; Carry out the definite and adjustment of self-adaptation of described evaluation index weights omega according to the importance degree of described evaluation index; Calculating is for evaluation index i, and k optional routing path belongs to total grey evaluation coefficient that each estimates grey class; Calculate each evaluation index of k optional routing path and estimate the grey evaluation weight matrix R of grey class for each ^(k)According to each evaluation index weights omega and grey evaluation weight matrix R ^(k)K optional routing path made comprehensive evaluation, and comprehensive evaluation result is done uniformization handle to obtain the wiring exponential quantity of described a plurality of optional routing paths.

Preferably, the evaluation information matrix of setting up described evaluation index in the embodiment of the invention comprises: the evaluation information value d that obtains i evaluation index of k optional routing path _{Ki '}, wherein, k={1,2 ..., p}, i={1,2 ..., m}; Set up evaluation information matrix D=(d according to described evaluation information value _Ki) _{P * m}

Preferably, the embodiment of the invention also comprises: to described evaluation information matrix D=(d _Ki) _{P * m}Carry out unified processing that index estimates:, remember that element after reunification is: δ if evaluation index when excellent more, is then carried out upper limit measure of merit for big more _Ki=d _Ki/ maxd _KiIf evaluation index, is then carried out floor effect and estimated when excellent more for more little, remember that element after reunification is: δ _Ki=mind _Ki/ d _KiObtain changing evaluation information matrix delta=(δ after unified processing of estimating according to These parameters _Ki) _{P * m}

Preferably, the importance degree of determining described evaluation index in the embodiment of the invention comprises: will comment described valency index to be divided into to be indifferent to, inessential, important and very important four grades; Described importance degree according to described evaluation index carries out the self-adaptation of described evaluation index weights omega and determines to comprise with adjustment: described unconcerned evaluation index weight is made as 0, utilize the subjective enabling legislation of (2,2) EM to calculate each evaluation index weights omega=(ω that optimum routing path is selected ₁, ω ₂..., ω _m), wherein

Preferably, the embodiment of the invention is fallen into a trap and is got it right in evaluation index i, k optional routing path belongs to each total grey evaluation coefficient of estimating grey class and comprises: calculate the grey evaluation coefficient: to evaluation index i, be designated as if k optional routing path belongs to j the grey evaluation coefficient of estimating grey class

, then have

To evaluation index i, k optional routing path belongs to each total grey evaluation coefficient of estimating grey class and is designated as Then have

Preferably, each evaluation index of calculating k optional routing path in the embodiment of the invention is estimated the grey evaluation weight matrix R of grey class for each ^(k)Comprise: to evaluation index i, the grey evaluation power that the individual optional routing path of k belongs to j grey class is designated as

Then

There is g because of estimating grey class, so the evaluation index i of k optional routing path is for the grey evaluation weight vector of each grey class

For:

$r_i^{\left(k\right)}=(r_{i1}^{\left(k\right)},r_{i2}^{\left(k\right)},...,r_{\mathrm{ig}}^{\left(k\right)});$

Thus will

Each evaluation index that comprehensively obtains k optional routing path is estimated the grey evaluation weight matrix R of grey class for each ^(k):

$R^{\left(k\right)}=\left[\begin{array}{c}{r}_1^{\left(k\right)}\\ r_2^{\left(k\right)}\\ .\\ .\\ .\\ r_m^{\left(k\right)}\end{array}\right]=\left[\begin{array}{cccc}{r}_{11}^{\left(k\right)}& r_{12}^{\left(k\right)}& ...& r_{1g}^{\left(k\right)}\\ r_{21}^{\left(k\right)}& r_{22}^{\left(k\right)}& ...& r_{2g}^{\left(k\right)}\\ .& .& & .\\ .& .& & .\\ .& .& ...& .\\ r_{m1}^{\left(k\right)}& r_{m2}^{\left(k\right)}& ...& r_{\mathrm{mg}}^{\left(k\right)}\end{array}\right].$

Preferably, in the embodiment of the invention according to each evaluation index weights omega and grey evaluation weight matrix R ^(k)K optional routing path is made comprehensive evaluation, and comprehensive evaluation result is done uniformization handle and comprise: according to each evaluation index weights omega and grey evaluation weight matrix R with the wiring exponential quantity that obtains described a plurality of optional routing paths ^(k)K optional routing path made comprehensive evaluation, and establishing comprehensive evaluation result is B ^(k), then:

$B^{\left(k\right)}=\mathrm{\ω}{R}^{\left(k\right)}=(b_1^{\left(k\right)},b_2^{\left(k\right)},...,b_g^{\left(k\right)});$

Described comprehensive evaluation result is done uniformization to be handled to obtain the wiring exponential quantity of described a plurality of optional routing paths.

Preferably, in the embodiment of the invention described comprehensive evaluation result being done the uniformization processing comprises with the wiring exponential quantity that obtains described a plurality of optional routing paths: the weight coefficient C that sets the grey class j of described evaluation _j(j=1,2 ..., g), obtain the wiring exponential quantity r of described a plurality of optional routing paths according to following formula ^(k):

The Evaluation and Selection method of the optimum routing path of the electric locomotive of the embodiment of the invention has been utilized analytical hierarchy process and gray model, before wiring, just take all factors into consideration and find out optimum routing path, it is unified to make the routing path design accomplish, has reduced design time and cost.In addition,, be convenient to locomotive the determining of routing path when maintenance or add-assembly, make locomotive when maintenance and add-assembly, be unlikely to occur changeable, the random big problem of routing path because in the past the thing of empirical had been become actual data.

Description of drawings

In order to be illustrated more clearly in the embodiment of the invention or technical scheme of the prior art, to do to introduce simply to the accompanying drawing of required use in embodiment or the description of the Prior Art below, apparently, accompanying drawing in describing below only is some embodiments of the present invention, for those of ordinary skills, under the prerequisite of not paying creative work, can also obtain other accompanying drawing according to these accompanying drawings.

The Evaluation and Selection method flow diagram of the optimum routing path of a kind of electric locomotive that Fig. 1 provides for the embodiment of the invention one;

A kind of routing path that Fig. 2 provides for the embodiment of the invention one is selected index system structure of models figure;

The Evaluation and Selection method flow diagram of the optimum routing path of a kind of electric locomotive that Fig. 3 provides for the embodiment of the invention two;

The synoptic diagram of a kind of white function that Fig. 4 provides for the embodiment of the invention two;

A kind of evaluation index importance degree synoptic diagram that Fig. 5 provides for the embodiment of the invention two;

The another kind of evaluation index importance degree synoptic diagram that Fig. 6 provides for the embodiment of the invention two.

Embodiment

In order to make the purpose, technical solutions and advantages of the present invention clearer,, the present invention is described in further details below in conjunction with embodiment and accompanying drawing.At this, exemplary embodiment of the present invention and explanation thereof are used to explain the present invention, but not as a limitation of the invention.

Embodiment one

Be illustrated in figure 1 as the Evaluation and Selection method flow diagram of the optimum routing path of a kind of electric locomotive that the embodiment of the invention one provides, this method comprises the steps:

S101: set up routing path according to analytical hierarchy process AHP and select the index system model, obtain a plurality of optional routing paths.

The model that AHP constructed is a kind of stratum's aggregated(particle) structure model of passing, and in general the hierarchical structure of AHP can be divided into three types: destination layer: only comprise an element, the general objective of expression decision analysis; The middle layer: comprise the several layers element, expression realizes each involved sub-goal of general objective, comprises various criterions, constraint, strategy etc.; Solution layer: the feasible program of each decision objective of expression realization, measure etc.

Such as: a kind of routing path that being illustrated in figure 2 as the embodiment of the invention one provides is selected index system structure of models figure.This model structure figure is the routing path of setting up according to AHP and selects the index system model, wherein:

Destination layer: the Evaluation and Selection of optimum routing path;

Indicator layer (middle layer): select electromagnetic compatibility degree, space interference degree, the cable boundling degree of crowding, cable length, wiring aesthetic measure and designer's tendency, be used as selecting the evaluation index of optimum routing path;

Solution layer: provided 2 kinds of feasible paths, can routing footpath 1 and feasible path 2.This feasible path is determined according to the evaluation index standard.

S102: according to gray model GM described a plurality of optional routing paths are carried out the grey evaluation that optimum routing path is selected, obtain wiring exponential quantity corresponding to described a plurality of optional routing paths.

Gray model is the model of setting up with gray system theory; it is the Differential Equation Model of n rank, a h variable; brief note is GM (n; h) the modeling mechanism of model .GM model is; random quantity is regarded as the grey colo(u)r specification that changes in the certain limit; after generation is handled to irregular raw data process, set up and generate Differential Equation Model, set up different models with different data generations and improve model accuracy.Just because of existing many uncertain enchancement factors in the routing path selection course, therefore, can adopt gray model to carry out optimum routing path and select.

S103: the described optional routing path of choosing described wiring exponential quantity optimum is optimum routing path.

The Evaluation and Selection method of the optimum routing path of the electric locomotive of the embodiment of the invention has been utilized analytical hierarchy process and gray model, before wiring, just take all factors into consideration and find out optimum routing path, it is unified to make the routing path design accomplish, has reduced design time and cost.In addition,, be convenient to locomotive the determining of routing path when maintenance or add-assembly, make locomotive when maintenance and add-assembly, be unlikely to occur changeable, the random big problem of routing path because in the past the thing of empirical had been become actual data.

Embodiment two

Be illustrated in figure 3 as the Evaluation and Selection method flow diagram of the optimum routing path of a kind of electric locomotive that the embodiment of the invention two provides, this method comprises the steps:

S301: set up routing path according to analytical hierarchy process AHP and select the index system model, obtain a plurality of optional routing paths, the sequence number of described optional routing path is k={1,2 ... p}, comprise m class evaluation index in the described routing path selection index system model, the sequence number of described evaluation index is i={1,2,, m}.

S302: the evaluation information matrix of setting up described evaluation index.

At first, can obtain the evaluation information value d of i evaluation index of k optional routing path earlier _{Ki '}, wherein, k={1,2 ..., p}, i={1,2 ..., m};

And then set up evaluation information matrix D=(d according to this evaluation information value _Ki) _{P * m}

Then again this evaluation information matrix is carried out unified processing that evaluation index is estimated, the evaluation index here can be divided into " big more excellent more type " and " more little excellent more type " two kinds of situations in the present embodiment:

Big more when excellent more for evaluation index, use upper limit measure of merit, note element after reunification is: δ _Ki=d _Ki/ maxd _Ki

More little when excellent more for evaluation index, then carry out floor effect and estimate, note element after reunification is: δ _Ki=mind _Ki/ d _Ki

Just obtained conversion evaluation information matrix delta=(δ after unified processing that above-mentioned evaluation information matrix is estimated according to These parameters _Ki) _{P * m}

S303: determine to estimate grey class j={1 according to actual conditions, 2 ..., the grey number of the grade of g}, grey class j is with the albefaction weight function f of grey class j ash number _j

The grade classification of above-mentioned grey class, grey number are established a capital really according to the actual conditions analysis and are determined.In the present embodiment, excellent, good such as grey class being divided into, in, differ from 4 classes, and corresponding grey number and albefaction weight function are:

The first grey class: excellent (j=1), set grey number

White function f ₁See Fig. 4 (a);

The second grey class: good (j=2), set grey number White function f ₂See Fig. 4 (b);

The 3rd grey class: in (j=3), set grey number

White function f ₃See Fig. 4 (c);

The 4th grey class: poor (j=4), set grey number White function f ₄See Fig. 4 (d).

S304: the importance degree of determining described evaluation index.

The primary and secondary status of the importance degree of each evaluation index directive function that to be this index risen in this time wiring design, in the present embodiment, this importance degree is such as being divided into: be indifferent to, inessential, important and very important four grades, certainly, the embodiment of the invention is not got rid of yet and is adopted other rank division method to determine importance degree.

It is to be noted, the importance degree of each evaluation index is not quite similar in all cases, such as for six kinds of evaluation indexes that exemplified among the embodiment one: select electromagnetic compatibility degree, space interference degree, the cable boundling degree of crowding, cable length, wiring aesthetic measure and designer's tendency, their importance degrees in situation 1 can be as shown in Figure 5, and the importance degree in situation 2 can be as shown in Figure 6.In order to determine the weight of each evaluation index, the importance degree of determining evaluation index is very important.

S305: carry out the definite and adjustment of self-adaptation of described evaluation index weights omega according to the importance degree of described evaluation index.

Above-mentioned unconcerned evaluation index weight is made as 0, utilizes the subjective enabling legislation of (2,2) EM to calculate other each evaluation index weights omega=(ω that optimum routing path is selected ₁, ω ₂..., ω _m), wherein

Concrete step is as described below:

Step 1: for evaluation index i={1,2 ..., m} is by relatively obtaining comparator matrix C in twos:

$C=\left[\begin{array}{cccc}{C}_{11}& C_{12}& ...& C_{1m}\\ C_{21}& C_{22}& ...& C_{2m}\\ .& .& .& .\\ .& .& .& .\\ .& .& .& .\\ C_{m1}& C_{m2}& ...& C_{\mathrm{mm}}\end{array}\right],$

In the formula:

It is pointed out that the C among the comparator matrix C ₁₁, C ₂₂C _MmThe oneself who is evaluation index compares, and its value is 0, and does not have unconcerned evaluation index among the above-mentioned evaluation index i.

At mentioned above principle, the situation in the above-mentioned situation 2 can be converted to following comparator matrix C:

$C=\left[\begin{array}{ccccc}0& 0& 0& 1& -1\\ 0& 0& 0& 1& -1\\ 0& 0& 0& 1& -1\\ -1& -1& -1& 0& -2\\ 1& 1& 1& 2& 0\end{array}\right]$

Following formula is for after removing cable length, the comparator matrix of remaining evaluation index through obtaining after relatively in twos, wherein, the index numbering of electromagnetic compatibility degree, space interference degree, the cable boundling degree of crowding, wiring aesthetic measure and designer's tendency is respectively 1,2,3,4,5.

Step 2: the weights of importance index r that calculates each index _i:

$r_i=\underset{j=1}{\overset{m}{\mathrm{\Σ}}}{C}_{\mathrm{ij}},(i=\mathrm{1,2},\·\·\·,m)$

Step 3: the element of asking judgment matrix B:

$b_{\mathrm{ij}}=\left\{\begin{array}{cc}{r}_i-r_j+1& r_i\≥r_j\\ (r_j-r_i+1)& r_i\≤r_j\end{array}\right.$

Obtain judgment matrix: $B=\left[\begin{array}{cccc}{b}_{11}& b_{12}& ...& b_{1m}\\ b_{21}& b_{22}& ...& b_{2m}\\ .& .& .& .\\ .& .& .& .\\ .& .& .& .\\ b_{m1}& b_{m2}& ...& b_{\mathrm{mn}}\end{array}\right]$

Step 4: utilize proper vector method (EM) to find the solution the maximum characteristic root λ of judgment matrix B _MaxThereby obtain weight vectors ω=(ω ₁, ω ₂..., ω _m), wherein

So just obtained the index weight that optimum routing path is selected, and this weight can be utilized said method self-adaptation adjustment in time according to the change of design.

S306: calculate for evaluation index i according to following formula, k optional routing path belongs to total grey evaluation coefficient that each estimates grey class

$X_{\mathrm{ij}}^{\left(k\right)}=f_i\left({\mathrm{\δ}}_{\mathrm{ki}}\right);$

To evaluation index i, k optional routing path belongs to each total grey evaluation coefficient of estimating grey class and is designated as

Be divided into 4 classes among grey class here such as the step S303, then have:

$X_i^{\left(k\right)}=\underset{j=1}{\overset{4}{\mathrm{\Σ}}}{X}_{\mathrm{ij}}^k.$

S307: each evaluation index of calculating k optional routing path is estimated the grey evaluation weight matrix R of grey class for each ^(k):

To evaluation index i, the grey evaluation power that the individual optional routing path of k belongs to j grey class is designated as

Then

$r_{\mathrm{ij}}^{\left(k\right)}=\frac{X_{\mathrm{ij}}^{\left(k\right)}}{X_i^{\left(k\right)}};$

There are 4 because of estimating grey class in the present embodiment, so the evaluation index i of k optional routing path is for the grey evaluation weight vector of each grey class

For:

$r_i^{\left(k\right)}=(r_{i1}^{\left(k\right)},r_{i2}^{\left(k\right)},r_{i3}^{\left(k\right)},r_{i4}^{\left(k\right)});$

Thus will

Each evaluation index that comprehensively obtains k optional routing path is estimated the grey evaluation weight matrix R of grey class for each ^(k):

$R^{\left(k\right)}=\left[\begin{array}{c}{r}_1^{\left(k\right)}\\ r_2^{\left(k\right)}\\ .\\ .\\ .\\ r_m^{\left(k\right)}\end{array}\right]=\left[\begin{array}{cccc}{r}_{11}^{\left(k\right)}& r_{12}^{\left(k\right)}& r_{13}^{\left(k\right)}& r_{14}^{\left(k\right)}\\ r_{21}^{\left(k\right)}& r_{22}^{\left(k\right)}& r_{23}^{\left(k\right)}& r_{24}^{\left(k\right)}\\ .& .& .& .\\ .& .& .& .\\ .& .& .& .\\ r_{m1}^{\left(k\right)}& r_{m2}^{\left(k\right)}& r_{m3}^{\left(k\right)}& r_{m4}^{\left(k\right)}\end{array}\right].$

S308: according to each evaluation index weights omega and grey evaluation weight matrix R ^(k)K optional routing path made comprehensive evaluation, and establishing comprehensive evaluation result is B ^(k), then:

$B^{\left(k\right)}=\mathrm{\ω}{R}^{\left(k\right)}=(b_1^{\left(k\right)},b_2^{\left(k\right)},b_3^{\left(k\right)},b_4^{\left(k\right)});$

Again comprehensive evaluation result being done uniformization handles to obtain the wiring exponential quantity of described a plurality of optional routing paths:

Set the weight coefficient C of the grey class j of described evaluation _j, this weight coefficient can rule of thumb be set by oneself in advance by the user. and such as getting (C in the present embodiment ₁=1.0, C ₂=0.8, C ₃=0.6, C ₄=0.4), just can obtain the wiring exponential quantity r of described a plurality of optional routing paths then according to following formula ^(k):

$r^{\left(k\right)}=\underset{j=1}{\overset{4}{\mathrm{\Σ}}}{B}^{\left(k\right)}{C}_j.$

S309: the described optional routing path of choosing above-mentioned wiring exponential quantity maximum is optimum routing path.

Here because the weight coefficient of more excellent grey class is bigger, the exponential quantity that therefore connects up is big more, and then optional routing path is excellent more, if above-mentioned weight coefficient is made as: (C ₁=0.4, C ₂=0.6, C ₃=0.8, C ₄=1.0), then step S309 becomes: the described optional routing path of choosing wiring exponential quantity minimum is optimum routing path.

The Evaluation and Selection method of the optimum routing path of the electric locomotive of the embodiment of the invention has been utilized analytical hierarchy process and gray model, before wiring, just take all factors into consideration and find out optimum routing path, it is unified to make the routing path design accomplish, has reduced design time and cost.In addition,, be convenient to locomotive the determining of routing path when maintenance or add-assembly, make locomotive when maintenance and add-assembly, be unlikely to occur changeable, the random big problem of routing path because in the past the thing of empirical had been become actual data.

Embodiment three

Present embodiment is with the further specific descriptions of an object lesson to embodiment two.

Need in the present embodiment to select optimum routing path for locomotive control platform to the control module of certain model.Adopt the method for the embodiment of the invention, it comprises the steps:

1, the routing path of at first setting up according to analytical hierarchy process is selected the index system model, obtain 6 optional routing paths, comprise six kinds of indexs in this index system model: electromagnetic compatibility degree, space interference degree, the cable boundling degree of crowding, cable length, wiring aesthetic measure and client's special requirement.

2, obtain above-mentioned 6 optional routing paths at above-mentioned six kinds of evaluation of indexes value of information d _{Ki '}, and set up as the described evaluation information matrix D of step S302 among the embodiment two=(d _Ki) _{P * m}:

$\left[\begin{array}{cccccc}{d}_{11}& d_{12}& d_{13}& d_{14}& d_{15}& d_{16}\\ d_{21}& d_{22}& d_{23}& d_{24}& d_{25}& d_{26}\\ d_{31}& d_{32}& d_{33}& d_{34}& d_{35}& d_{36}\\ d_{41}& d_{42}& d_{43}& d_{44}& d_{45}& d_{46}\\ d_{51}& d_{52}& d_{53}& d_{54}& d_{55}& d_{56}\\ d_{61}& d_{62}& d_{63}& d_{64}& d_{65}& d_{66}\end{array}\right];$

Six kinds of index values that satisfy in each a kind of path of row representative in the above-mentioned matrix, such as, six kinds of index values that d11, d12, d13, d14, d15, d16 delegated path 1 are satisfied, these six kinds of index values are respectively: electromagnetic compatibility degree, space interference degree, the cable boundling degree of crowding, cable length, wiring aesthetic measure and client's special requirement.

In the present embodiment, the concrete numerical value of above-mentioned matrix D is:

$\left[\begin{array}{cccccc}1.0& 0.5& 0.7& 0.6& 0.8& 0.5\\ 0.8& 0.7& 1.0& 0.7& 0.4& 0.4\\ 0.7& 0.9& 0.8& 0.8& 1.0& 0.7\\ 0.6& 1.0& 0.7& 0.6& 0.9& 0.6\\ 0.3& 0.7& 0.4& 1.0& 0.9& 0.3\\ 0.4& 0.8& 0.5& 0.8& 0.9& 1.0\end{array}\right]$

The concrete numerical value of above-mentioned matrix is that the designer gives as the case may be, such as

[d ₁₁d ₁₂d ₁₃d ₁₄d ₁₅d ₁₆]=[1.0 0.5 0.7 0.6 0.8 0.5] represented: electromagnetic compatibility degree 1.0, space interference degree 0.5, the cable boundling degree of crowding 0.7, cable length 0.6, wiring aesthetic measure 0.8, client's special requirement 0.5, that is: industry standard is satisfied fully to electromagnetic compatibility requirements in path 1, numerical value 1.0; There is the wire harness of half interference to be arranged in various degree, numerical value 0.5; The cable boundling is not crowded, numerical value 0.7; Cable length is longer in 6 paths, numerical value 0.6; Numerical value 0.8 more attractive in appearance connects up; Client's special requirement satisfy half, numerical value 0.5.

In like manner other data also are the values that the designer gives according to certain standard.

In the present embodiment, evaluation index adopts " big more excellent more type ", is δ through after reunification element therefore _Ki=d _Ki/ maxd _Ki, will unify to estimate conversion according to the above-mentioned evaluation information matrix D of this formula, the evaluation information matrix delta=(δ as shown in Table 1 after obtaining changing _Ki) _{P * m}:

	The electromagnetic compatibility degree	The space interference degree	The cable boundling degree of crowding	Cable length	The wiring aesthetic measure	Client's special requirement
							Path
1	1.0	0.5	0.7	0.6	0.8	0.5
							Path 2	0.8	0.7	1.0	0.4	0.7	0.4
Path 3	0.7	0.9	0.8	0.8	1.0	0.7
							Path 4	0.6	1.0	0.7	0.6	0.9	0.6
Path 5	0.3	0.7	0.4	1.0	0.9	0.3
							Path 6	0.4	0.8	0.5	0.8	0.9	1.0

Table one

3, determine to estimate grey class j={1 according to actual conditions, 2 ..., the grey number of the grade of g}, grey class j is with the albefaction weight function f of grey class j ash number _jHere step S303 is similar among division of grey class and albefaction weight function and the embodiment two, has just no longer given unnecessary details at this.

4, determine the importance degree of described evaluation index, here the importance degree of evaluation index also be divided into be indifferent to, inessential, important and very important four grades.

5, according to the described formula of step S305 among the embodiment two, indicator vector ω=(0.144,0.527,0.144,0.041,0.144,0) in can present embodiment, concrete computation process has just no longer been given unnecessary details.

6, last again according to the formula described in the step S306-S308 among the embodiment two, can refer in the hope of the cloth linear index in the present embodiment: r ¹=0.7955, r ²=0.6489, r ³=0.8342, r ⁴=0.8339, r ⁵=0.6851, r ⁶=0.6978, i.e. r ³＞r ⁴＞r ¹＞r ⁶＞r ⁵＞r ²

7, visible cloth linear index optimal value is r ³=0.8342, so feasible path 3 is the routing path of the optimum of the embodiment of the invention.

One of ordinary skill in the art will appreciate that all or part of flow process that realizes in the foregoing description method, can instruct relevant hardware to finish by computer program, described program can be stored in the computer read/write memory medium, this program can comprise the flow process as the embodiment of above-mentioned each side method when carrying out.Wherein, described storage medium can be magnetic disc, CD, read-only storage memory body (Read-Only Memory, ROM) or at random store memory body (Random Access Memory, RAM) etc.

Above-described embodiment; purpose of the present invention, technical scheme and beneficial effect are further described; institute is understood that; the above only is the specific embodiment of the present invention; and be not intended to limit the scope of the invention; within the spirit and principles in the present invention all, any modification of being made, be equal to replacement, improvement etc., all should be included within protection scope of the present invention.

Claims (9)

1. the Evaluation and Selection method of the optimum routing path of an electric locomotive is characterized in that described method comprises:

Set up routing path according to analytical hierarchy process AHP and select the index system model, obtain a plurality of optional routing paths, the sequence number of described optional routing path is k={1,2 ... p}, comprise m class evaluation index in the described routing path selection index system model, the sequence number of described evaluation index is i={1,2,, m};

According to gray model GM described a plurality of optional routing paths are carried out the grey evaluation that optimum routing path is selected, obtain wiring exponential quantity corresponding to described a plurality of optional routing paths;

The described optional routing path of choosing described wiring exponential quantity optimum is optimum routing path.

2. the method for claim 1 is characterized in that, describedly according to gray model GM described a plurality of optional routing paths is carried out the grey evaluation that optimum routing path is selected, and obtains comprising corresponding to the wiring exponential quantity of described a plurality of optional routing paths:

Set up the evaluation information matrix of described evaluation index;

Determine to estimate grey class j={1 according to actual conditions, 2 ..., the grey number of the grade of g}, grey class j is with the albefaction weight function f of grey class j ash number _j

Determine the importance degree of described evaluation index;

Carry out the definite and adjustment of self-adaptation of described evaluation index weights omega according to the importance degree of described evaluation index;

Calculating is for evaluation index i, and k optional routing path belongs to total grey evaluation coefficient that each estimates grey class;

Calculate each evaluation index of k optional routing path and estimate the grey evaluation weight matrix R of grey class for each ^(k)

According to each evaluation index weights omega and grey evaluation weight matrix R ^(k)K optional routing path made comprehensive evaluation, and comprehensive evaluation result is done uniformization handle to obtain the wiring exponential quantity of described a plurality of optional routing paths.

3. method as claimed in claim 2 is characterized in that, the described evaluation information matrix of setting up described evaluation index comprises:

Obtain the evaluation information value d of i evaluation index of k optional routing path _{Ki '}, wherein, k={1,2 ..., p}, i={1,2 ..., m};

Set up evaluation information matrix D=(d according to described evaluation information value _Ki) _{P * m}

4. method as claimed in claim 3 is characterized in that, also comprises:

To described evaluation information matrix D=(d _Ki) _{P * m}Carry out unified processing that evaluation index is estimated:

If evaluation index when excellent more, is then carried out upper limit measure of merit for big more, remember that element after reunification is: δ _Ki=d _Ki/ maxd _Ki

If evaluation index, is then carried out floor effect and estimated when excellent more for more little, remember that element after reunification is: δ _Ki=mind _Ki/ d _Ki

Obtain changing evaluation information matrix delta=(δ after unified processing of estimating according to These parameters _Ki) _{P * m}

5. method as claimed in claim 4 is characterized in that, the importance degree of described definite described evaluation index comprises:

To comment described valency index to be divided into to be indifferent to, inessential, important and very important four grades;

Described importance degree according to described evaluation index carries out the self-adaptation of described evaluation index weights omega and determines to comprise with adjustment:

Described unconcerned evaluation index weight is made as 0, utilizes the subjective enabling legislation of (2,2) EM to calculate each evaluation index weights omega=(ω that optimum routing path is selected ₁, ω ₂..., ω _m), wherein

6. method as claimed in claim 5 is characterized in that, described calculating is for evaluation index i, and k optional routing path belongs to each total grey evaluation coefficient of estimating grey class and comprise:

Calculate the grey evaluation coefficient:, be designated as if k optional routing path belongs to j the grey evaluation coefficient of estimating grey class to evaluation index i

Then have

$X_{\mathrm{ij}}^{\left(k\right)}=f_i\left({\mathrm{\δ}}_{\mathrm{ki}}\right);$

To evaluation index i, k optional routing path belongs to each total grey evaluation coefficient of estimating grey class and is designated as

Then have

Wherein g is for estimating the number of grey class.

7. method as claimed in claim 6 is characterized in that, each evaluation index of described calculating k optional routing path is estimated the grey evaluation weight matrix R of grey class for each ^(k)Comprise: to evaluation index i, the grey evaluation power that the individual optional routing path of k belongs to j grey class is designated as

Then

$r_{\mathrm{ij}}^{\left(k\right)}=\frac{X_{\mathrm{ij}}^{\left(k\right)}}{X_i^{\left(k\right)}};$

There is g because of estimating grey class, so the evaluation index i of k optional routing path is for the grey evaluation weight vector of each grey class

For:

$r_i^{\left(k\right)}=(r_{i1}^{\left(k\right)},r_{i2}^{\left(k\right)},...,r_{\mathrm{ig}}^{\left(k\right)});$

Thus will

Each evaluation index that comprehensively obtains k optional routing path is estimated the grey evaluation weight matrix R of grey class for each ^(k):

$R^{\left(k\right)}=\left[\begin{array}{c}{r}_1^{\left(k\right)}\\ r_2^{\left(k\right)}\\ .\\ .\\ .\\ r_m^{\left(k\right)}\end{array}\right]=\left[\begin{array}{cccc}{r}_{11}^{\left(k\right)}& r_{12}^{\left(k\right)}& ...& r_{1g}^{\left(k\right)}\\ r_{21}^{\left(k\right)}& r_{22}^{\left(k\right)}& ...& r_{2g}^{\left(k\right)}\\ .& .& & .\\ .& .& & .\\ .& .& ...& .\\ r_{m1}^{\left(k\right)}& r_{m2}^{\left(k\right)}& ...& r_{\mathrm{mg}}^{\left(k\right)}\end{array}\right].$

8. method as claimed in claim 7 is characterized in that, and is described according to each evaluation index weights omega and grey evaluation weight matrix R ^(k)K optional routing path is made comprehensive evaluation, and comprehensive evaluation result is done uniformization handle and comprise with the wiring exponential quantity that obtains described a plurality of optional routing paths:

According to each evaluation index weights omega and grey evaluation weight matrix R ^(k)K optional routing path made comprehensive evaluation, and establishing comprehensive evaluation result is B ^(k), then:

$B^{\left(k\right)}=\mathrm{\ω}{R}^{\left(k\right)}=(b_1^{\left(k\right)},b_2^{\left(k\right)},...,b_g^{\left(k\right)});$

Described comprehensive evaluation result is done uniformization to be handled to obtain the wiring exponential quantity of described a plurality of optional routing paths.

9. method as claimed in claim 8 is characterized in that, describedly described comprehensive evaluation result is done uniformization handles and to comprise with the wiring exponential quantity that obtains described a plurality of optional routing paths:

Set the weight coefficient C of the grey class j of described evaluation _j(j=1,2 ..., g), obtain the wiring exponential quantity r of described a plurality of optional routing paths according to following formula ^(k):

$r^{\left(k\right)}=\underset{j=1}{\overset{g}{\mathrm{\Σ}}}{B}^{\left(k\right)}{C}_j.$

Images