CN114218688A - Method for optimizing characteristic parameters of blades of sectional inclined grooves of ventilated brake disc - Google Patents

Method for optimizing characteristic parameters of blades of sectional inclined grooves of ventilated brake disc Download PDF

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CN114218688A
CN114218688A CN202111280119.5A CN202111280119A CN114218688A CN 114218688 A CN114218688 A CN 114218688A CN 202111280119 A CN202111280119 A CN 202111280119A CN 114218688 A CN114218688 A CN 114218688A
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inclined groove
brake disc
blade
optimization
characteristic parameters
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CN114218688B (en
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李�杰
陶龙
陈颖
顾佳玲
高紫钰
周一健
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Beijing University of Civil Engineering and Architecture
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
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    • G06F30/00—Computer-aided design [CAD]
    • G06F30/10—Geometric CAD
    • G06F30/17—Mechanical parametric or variational design
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F16—ENGINEERING ELEMENTS AND UNITS; GENERAL MEASURES FOR PRODUCING AND MAINTAINING EFFECTIVE FUNCTIONING OF MACHINES OR INSTALLATIONS; THERMAL INSULATION IN GENERAL
    • F16D—COUPLINGS FOR TRANSMITTING ROTATION; CLUTCHES; BRAKES
    • F16D65/00—Parts or details
    • F16D65/02—Braking members; Mounting thereof
    • F16D65/12—Discs; Drums for disc brakes
    • F16D65/128—Discs; Drums for disc brakes characterised by means for cooling
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F16—ENGINEERING ELEMENTS AND UNITS; GENERAL MEASURES FOR PRODUCING AND MAINTAINING EFFECTIVE FUNCTIONING OF MACHINES OR INSTALLATIONS; THERMAL INSULATION IN GENERAL
    • F16D—COUPLINGS FOR TRANSMITTING ROTATION; CLUTCHES; BRAKES
    • F16D65/00—Parts or details
    • F16D65/78—Features relating to cooling
    • F16D65/84—Features relating to cooling for disc brakes
    • F16D65/847—Features relating to cooling for disc brakes with open cooling system, e.g. cooled by air
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    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F16—ENGINEERING ELEMENTS AND UNITS; GENERAL MEASURES FOR PRODUCING AND MAINTAINING EFFECTIVE FUNCTIONING OF MACHINES OR INSTALLATIONS; THERMAL INSULATION IN GENERAL
    • F16D—COUPLINGS FOR TRANSMITTING ROTATION; CLUTCHES; BRAKES
    • F16D65/00—Parts or details
    • F16D65/78—Features relating to cooling
    • F16D2065/788—Internal cooling channels
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Abstract

The invention discloses a method for optimizing sectional type inclined groove blade characteristic parameters of a ventilated brake disc, which comprises the following steps: step one, establishing a sectional type inclined groove blade model of a brake disc; determining structural characteristic parameters required to be optimized by the sectional type inclined groove blade; determining an optimization target and constraint conditions; performing numerical simulation by adopting a sectional type inclined groove blade model, performing data sampling based on an optimal Latin hypercube method, fitting a response surface proxy model and verifying the accuracy of the proxy model; step three, solving a Pareto optimization solution set obtained by solving two objective functions by adopting NSGA-II; and step four, obtaining an optimal solution in the Pareto optimal solution set through a TOPSIS decision method, and performing CFD verification. The optimization method can optimize and improve the characteristic parameters of the sectional inclined groove blades in the brake disc, and improve the convection heat dissipation performance of the brake disc.

Description

Method for optimizing characteristic parameters of blades of sectional inclined grooves of ventilated brake disc
Technical Field
The invention relates to the technical field of vehicle braking, in particular to a method for optimizing characteristic parameters of a sectional type inclined groove blade of a ventilated brake disc.
Background
The inside straight blade that adopts of current ventilated formula brake disc that vehicle braking used more, the straight blade brake disc of ventilated formula has two outer friction surfaces, and the brake disc internal surface passes through straight blade and connects, allows the air flow, and the brake disc can reach higher temperature when braking, and the air current that passes the blade in succession provides good cooling, has prolonged the life of brake disc. However, when the straight blade brake disc rotates counterclockwise, the left side of the heat dissipation channel is subjected to high pressure relative to the right side, which are called the pressure side and the suction side respectively, because the flow velocity along the radial suction side is gradually reduced due to the air inflow angle, and the kinetic energy of the fluid itself is insufficient to take away the fluid on the suction side, so that a backflow area exists on the suction side in the flow channel. The existence of backward flow district has seriously blocked the flow of air in the ventilation formula brake disc passageway, and new cooling air is difficult to exchange with inside air, causes both sides to flow unevenly, finally leads to the interior heat dissipation of passageway uneven, has seriously reduced the convection heat dispersion of brake disc.
At present, most scholars at home and abroad mainly focus on simulation analysis, prediction and experimental verification on the pneumatic performance and the heat exchange effect of the brake disc in the aspect of research on improving the heat dissipation efficiency of the ventilated brake disc, but the optimization research on the characteristic parameters of the sectional type inclined groove blade in the internal channel backflow area is less.
There is therefore a need for a method of improving the heat dissipation of a brake rotor by improving the segmental inclined groove blade characteristics of a ventilated brake rotor to compromise mass flow and heat transfer.
Disclosure of Invention
In view of this, the invention provides a method for optimizing characteristic parameters of a segment-type inclined groove blade of a ventilated brake disc, which can optimize and improve the characteristic parameters of the segment-type inclined groove blade in the brake disc and improve the convective heat dissipation performance of the brake disc.
The invention adopts the following specific technical scheme:
a method for optimizing the characteristic parameters of the blades of a sectional inclined groove of a ventilated brake disc is disclosed, wherein the ventilated brake disc is provided with two external friction surfaces, two oppositely arranged internal surfaces and a plurality of radiating blades connected between the two internal surfaces; the plurality of radiating blades are uniformly distributed around the circumferential direction of the brake disc; each radiating blade is divided into an inner blade and an outer blade which are arranged along the radial direction of the brake disc by a middle inclined groove; the inclined groove and the radial center line of the inner blade form an included angle of an opening facing the outside of the brake disc, and the inclined groove is used for introducing fluid on a pressure side to a suction side to reduce a backflow area; the optimization method comprises the following steps:
step one, establishing a sectional type inclined groove blade model of a brake disc; determining optimized structural characteristic parameters required by the sectional type inclined groove blade of the ventilated brake disc, wherein the optimized structural characteristic parameters comprise the opening width H of the inclined groove of the sectional type inclined groove blade, the opening inclination angle alpha of the inclined groove and the number N of the blades; determining an optimization target and a constraint condition, wherein the two optimization targets are the maximum mass flow m and the maximum heat exchange coefficient h passing through an internal channel;
performing numerical simulation by adopting a sectional type inclined groove blade model, performing data sampling based on an Optimal Latin Hypercube (OLHS) method, fitting a Response Surface (RSM) agent model and verifying the accuracy of the agent model;
step three, solving a Pareto (Pareto) optimization solution set obtained by two objective functions (m, h) by adopting NSGA-II;
and step four, obtaining an optimal solution in the Pareto optimal solution set by a TOPSIS (technical for Order Preference by Similarity to an Ideal solution) decision method, and carrying out CFD (Computational Fluid Dynamics) verification on the result.
Further, in step one, the variation range of the structural feature parameter in the design variables is:
the value-taking distribution interval of the opening width H of the optimized parameter inclined groove is 8-13 mm;
the value taking distribution interval of the inclination angle alpha of the opening of the optimized parameter inclined groove is 30-60 degrees;
the value taking distribution interval of the number N of the optimized parameter blades is 20-40.
Furthermore, in the second step, the response surface proxy model is a polynomial of the objective function fitted by a least square method, so as to realize the display of the objective function; the basic expression of the objective function is:
Figure BDA0003326352100000031
wherein x isiIs the i-th component, β, of an n-dimensional argument x0Is a constant term undetermined coefficient, betaiIs the primary undetermined coefficient, betaijThe undetermined coefficients of the quadratic term form a column vector beta, n is the number of design variables, and epsilon is an error.
Further, in order to calculate the accuracy of the result, the accuracy of the fitting equation is determined in the form of variance, and the basic expression of the determination is as follows:
Figure BDA0003326352100000032
where N is the number of sample points, yiIn order to be the true response value,
Figure BDA0003326352100000033
the resulting response values are calculated for the response surface model,
Figure BDA0003326352100000034
is the average of the true response values.
Further, the third step comprises the following specific steps:
generating an initial population with the size of N in a random mode, and obtaining a first generation offspring population by basic operations of three genetic algorithms of selection, intersection and variation after non-dominated sorting is carried out on the initial population;
combining the offspring population and the parent population from the second generation, performing rapid non-dominant sorting, simultaneously performing congestion degree calculation on the individuals in each non-dominant layer, and selecting N individuals according to the non-dominant relationship and the congestion degree of the individuals and selecting conditions to form a new next generation population;
and then, generating new offspring populations through selection, crossing and mutation operations to circulate in sequence until the conditions of program ending are met.
Further, the step four comprises the following specific steps:
if n evaluation objects are provided, and each evaluation object has m indexes, the decision matrix is:
X＝(xij)n×m(i＝1，2，…，n；j＝1，2，…，m)；
normalizing the initial matrix:
Figure BDA0003326352100000041
setting a weighting factor wjWeighting the normalization matrix as:
aij＝wj×bij；
determining a positive ideal solution Z+Negative ideal solution Z-：
Figure BDA0003326352100000042
Calculating the distance from each evaluation object to the ideal solution
Figure BDA0003326352100000043
And the distance from each evaluation object to the negative ideal solution
Figure BDA0003326352100000044
Figure BDA0003326352100000045
Calculating closeness ri：
Figure BDA0003326352100000051
Has the advantages that:
according to the method for optimizing the characteristic parameters of the sectional inclined groove blade, theoretical analysis is carried out on the convection heat dissipation performance of a ventilated brake disc, and the structural characteristic parameters needing to be optimized of the sectional inclined groove blade are determined to be the opening width H of an inclined groove of the sectional inclined groove blade, the opening inclination angle alpha of the inclined groove and the number N of the blade; firstly, carrying out simulation calculation according to an established finite element simulation model, obtaining response sampling data corresponding to a plurality of sampling points by utilizing an OLHS (on-line analytical processing) method, and then obtaining a fitting function of an optimization target by adopting a response surface model; solving by a second-generation non-inferior ranking genetic algorithm NSGA-II based on the Pareto optimal solution to obtain a Pareto optimal solution set with the mass flow m and the maximum convective heat transfer coefficient h; finding an optimal solution based on the TOPSIS principle, and setting a sectional type inclined groove blade structure according to the optimal value, thereby obtaining a ventilated brake disc with stronger convection heat exchange performance, and realizing the rationality optimization of the sectional type inclined groove blade structure characteristic parameters of the ventilated brake disc. The optimization method has wider applicability and higher accuracy in the field of engineering design.
Drawings
FIG. 1 is a flow chart of a method for optimizing the characteristic parameters of a segment-type inclined groove blade of a ventilated brake disc according to the present invention;
FIG. 2 is a schematic view of a straight inter-blade channel recirculation zone of a prior art ventilated brake disc;
FIG. 3 is a schematic view of a prior art straight blade configuration of a ventilated brake disc;
FIG. 4 is a two-dimensional characteristic parameter diagram of a segmented inclined groove blade of a ventilated brake disc;
FIG. 5 is a sectional type inclined groove blade CFD numerical simulation fluid domain grid schematic diagram;
FIG. 6 is a schematic structural view of a ventilated brake disc optimized for use with the present invention;
FIG. 7 is a graph of a Pareto optimization solution obtained using the optimization method of the present invention;
FIG. 8 is a graph comparing the optimization results of the present invention with the variation curve of the average temperature of the blade surface with the rotation speed in the prior art.
Wherein 1-outer friction surface, 2-inner surface, 3-inclined groove, 4-inner blade, 5-outer blade, 6-cooling channel, 7-suction side, 8-pressure side, 9-straight blade
Detailed Description
The invention is described in detail below by way of example with reference to the accompanying drawings.
The embodiment of the invention provides a method for optimizing characteristic parameters of a sectional inclined groove blade of a ventilated brake disc, wherein a straight blade 9 structure of the conventional ventilated brake disc is shown as a structure in fig. 2 and 3, while the structure of the ventilated brake disc in the embodiment of the invention is shown as a structure in fig. 6, the ventilated brake disc in the embodiment of the invention is provided with two external friction surfaces 1, two oppositely arranged internal surfaces 2 and a plurality of radiating blades connected between the two internal surfaces 2, a cooling channel 6 is formed between the two adjacent radiating blades, one side of the cooling channel 6 is a Pressure side 8(Pressure side), and the other side of the cooling channel 6 is a Suction side 7(Suction side); a plurality of radiating blades are uniformly distributed around the circumference of the movable disc; each radiating blade is divided into an inner blade 4 and an outer blade 5 which are arranged along the radial direction of the brake disc by a middle inclined groove 3, and the specific structure is shown in FIG. 4; the inclined grooves 3 form an included angle with the radial center line of the inner blade 4, the included angle is opened towards the outer part of the brake disc, and the inclined grooves 3 are used for introducing fluid on a pressure side 8 to a suction side 7 to reduce a backflow area; as shown in fig. 1, the optimization method includes the following steps:
step one, establishing a sectional type inclined groove blade model of a brake disc; determining optimized structural characteristic parameters required by the sectional type inclined groove blade of the ventilated brake disc, wherein the optimized structural characteristic parameters comprise the opening width H of an inclined groove 3 of the sectional type inclined groove blade, the opening inclination angle alpha of the inclined groove 3 and the number N of the blades; determining an optimization target and a constraint condition, wherein the two optimization targets are the maximum mass flow m and the maximum heat exchange coefficient h passing through an internal channel;
performing numerical simulation by adopting the constructed sectional type inclined groove blade model, performing data sampling based on an Optimal Latin Hypercube (OLHS) method, fitting a response surface proxy model and verifying the accuracy of the proxy model;
step three, solving a Pareto optimization solution set obtained by two objective functions (m, h) by adopting NSGA-II;
and step four, obtaining an optimal solution in the Pareto optimal solution set through a TOPSIS decision method, and performing CFD verification on the result, as shown in FIG. 5.
In a specific embodiment, in the step one, designing a variation range of the structural feature parameter in the variable specifically includes:
the value-taking distribution interval of the opening width H of the optimized parameter inclined groove 3 is 8-13 mm;
the value taking distribution interval of the opening inclination angle alpha of the optimized parameter inclined groove 3 is 30-60 degrees;
the value taking distribution interval of the number N of the optimized parameter blades is 20-40.
Furthermore, in the second step, the response surface proxy model is a polynomial fit to the objective function by a least square method, so as to realize the display of the objective function; the basic expression of the objective function is:
Figure BDA0003326352100000071
wherein x isiIs the i-th component, β, of an n-dimensional argument x0Is a constant term undetermined coefficient, betaiIs the primary undetermined coefficient, betaijIs the quadratic term to be determinedCoefficients, constituting a column vector β, n being the number of design variables, and ε being the error.
In order to calculate the accuracy of the result, the accuracy of the fitting equation needs to be judged, the accuracy of the fitting equation is judged in the form of variance, and the basic expression of the judgment is as follows:
Figure BDA0003326352100000072
where N is the number of sample points, yiIn order to be the true response value,
Figure BDA0003326352100000073
the resulting response values are calculated for the response surface model,
Figure BDA0003326352100000081
is the average of the true response values.
In the embodiment of the invention, sampling points are obtained by using an Optimal Latin Hypercube (OLHS) method, each group of design variable values are obtained according to simulation tests, and simulation calculation is carried out according to a finite element simulation model established in the first step to obtain corresponding response sampling data of 30 sampling points, as shown in the following table 1.
Figure BDA0003326352100000082
Table 1 sample data results
Examples of the invention use R2To measure the degree of coincidence of the approximate model and the sample point item if R2The closer the value is to 1, the closer the approximate model is to the true value, i.e. the higher the accuracy of the established model. In the embodiment of the invention, the average mass flow m and the average convective heat transfer coefficient R2The values are 0.93647 and 0.91848 respectively, which are both larger than the set 0.9, so that the accuracy requirement of the response surface proxy model is met, and the method can be used for multi-objective optimization.
Specifically, step three may include the following specific steps:
generating an initial population with the size of N in a random mode, and obtaining a first generation offspring population by basic operations of three genetic algorithms of selection, intersection and variation after non-dominated sorting is carried out on the initial population;
combining the offspring population and the parent population from the second generation, performing rapid non-dominant sorting, simultaneously performing congestion degree calculation on the individuals in each non-dominant layer, and selecting N individuals according to the non-dominant relationship and the congestion degree of the individuals and selecting conditions to form a new next generation population;
and then, generating new offspring populations through selection, crossing and mutation operations to circulate in sequence until the conditions of program ending are met.
In the embodiment of the invention, the objective function of the agent model in the step two is taken as a basis, and a mathematical expression of multi-objective optimization is established as follows:
Figure BDA0003326352100000091
in the formula: p (α, N, H) is the objective function, mmaxIs the maximum mass flow of the cross section, hmaxThe maximum average convective heat transfer coefficient in the channel is called alpha, N and H as design variables.
Inputting the agent model, the constraint parameters and the range thereof into a genetic algorithm, wherein in the embodiment of the invention, the population number is set to be 50, the maximum iteration number is 200, the cross probability is 0.8, and the variation probability is 0.1; a Pareto optimization solution set of mass flow m and convective heat transfer coefficient h is obtained, as shown in fig. 7.
The fourth step comprises the following specific steps:
if n evaluation objects are provided, and each evaluation object has m indexes, the decision matrix is:
X＝(xij)n×m(i＝1，2，…，n；j＝1，2，…，m)；
normalizing the initial matrix:
Figure BDA0003326352100000092
setting a weighting factor wjWeighting the normalization matrix as:
aij＝wj×bij；
determining a positive ideal solution Z+Negative ideal solution Z-：
Figure BDA0003326352100000101
Calculating the distance between each evaluation object and the positive and negative ideal solutions:
Figure BDA0003326352100000102
calculating closeness ri：
Figure BDA0003326352100000103
In order to verify the accuracy of the solution of the multi-target genetic algorithm of the nsega-II based on the Pareto solution set, in the embodiment of the present invention, 5 discrete points are uniformly selected from the Pareto frontier shown in fig. 7 in proportion to be compared with the CFD simulation result, which is specifically shown in table 2 below:
Figure BDA0003326352100000104
TABLE 2 simulation and Pareto solution comparison
According to table 2, the simulation results of the mass flow and the convective heat transfer coefficient and the mean error of the solving value of the genetic algorithm are respectively 2.03% and 0.88%, and the two are well matched; the result of the multi-target genetic algorithm solution of the NSGA-II based on the Pareto solution set is reliable.
To obtain the optimal solution in the Pareto optimal solution set by the TOPSIS decision method, the closeness r of the feasible solutions in FIG. 7 is calculatediSelecting the most closely ordered resultThe advantages are taken as the solution of the embodiment of the invention.
In the implementation process, the optimal structural parameters of the finally selected sectional type inclined groove blade are that the width H of the opening of the groove is 12.7mm, the inclination angle alpha of the opening of the groove is 56.38 degrees, and the number N of the blades is 36. The mass flow through the brake disc after optimization was 49.88g/s, which was 12.37% higher than 44.39g/s before optimization. The average convective heat transfer coefficient of the optimized brake disc is 91.23W/m2K, heat exchange coefficient 82.16W/m compared to optimized front brake disc2The K is improved by 9.9 percent. Therefore, the optimized brake disc has good heat dissipation performance compared with the brake disc before optimization.
FIG. 5 compares the average temperature of the blade surfaces with the speed before and after optimization using CFD. Under the working condition that the rotating speed of the wheel is 200-1200 rpm, the average surface temperatures of the Straight blades 9(Straight Vane) and the sectional inclined groove blades (Vane with channel) are reduced along with the increase of the rotating speed; and the sectional type inclined groove blade structure design is better than the straight blade 9 radiating effect, the average temperature of the sectional type inclined groove blade surface is lower than the straight blade 9 temperature, the Reduction rate (Reduction rate) reaches 1.51% at the maximum when the rotating speed is 900rpm, as shown in fig. 8.
According to the method for optimizing the characteristic parameters of the sectional inclined groove blade, theoretical analysis is carried out on the convection heat dissipation performance of the ventilated brake disc, and the structural characteristic parameters needing to be optimized of the sectional inclined groove blade are determined to be the opening width H of the inclined groove 3 of the sectional inclined groove blade, the opening inclination angle alpha of the inclined groove 3 and the number N of the blade; firstly, carrying out simulation calculation according to an established finite element simulation model, obtaining response sampling data corresponding to a plurality of sampling points by utilizing an OLHS (on-line analytical processing) method, and then obtaining a fitting function of an optimization target by adopting a response surface model; solving by a second-generation non-inferior ranking genetic algorithm NSGA-II based on the Pareto optimal solution to obtain a Pareto optimal solution set with the mass flow m and the maximum convective heat transfer coefficient h; finding an optimal solution based on the TOPSIS principle, and setting a sectional type inclined groove blade structure according to the optimal value, thereby obtaining a ventilated brake disc with stronger convection heat exchange performance, and realizing the rationality optimization of the sectional type inclined groove blade structure characteristic parameters of the ventilated brake disc. The optimization method has wider applicability and higher accuracy in the field of engineering design.
The above description is only a preferred embodiment of the present invention, and is not intended to limit the scope of the present invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims (6)

1. A method for optimizing the characteristic parameters of a sectional inclined groove blade of a ventilated brake disc is characterized in that the ventilated brake disc is provided with two external friction surfaces, two oppositely arranged internal surfaces and a plurality of radiating blades connected between the two internal surfaces; the plurality of radiating blades are uniformly distributed around the circumferential direction of the brake disc; each radiating blade is divided into an inner blade and an outer blade which are arranged along the radial direction of the brake disc by a middle inclined groove; the inclined groove and the radial center line of the inner blade form an included angle of an opening facing the outside of the brake disc, and the inclined groove is used for introducing fluid on a pressure side to a suction side to reduce a backflow area; the optimization method comprises the following steps:
step one, establishing a sectional type inclined groove blade model of a brake disc; determining optimized structural characteristic parameters required by the sectional type inclined groove blade of the ventilated brake disc, wherein the optimized structural characteristic parameters comprise the opening width H of the inclined groove of the sectional type inclined groove blade, the opening inclination angle alpha of the inclined groove and the number N of the blades; determining an optimization target and a constraint condition, wherein the two optimization targets are the maximum mass flow m and the maximum heat exchange coefficient h passing through an internal channel;
performing numerical simulation by adopting a sectional type inclined groove blade model, performing data sampling based on an optimal Latin hypercube method, fitting a response surface proxy model and verifying the accuracy of the proxy model;
step three, solving a Pareto optimization solution set obtained by two objective functions (m, h) by adopting NSGA-II;
and step four, obtaining an optimal solution in the Pareto optimal solution set through a TOPSIS decision method, and performing CFD verification on the result.
2. The optimization method according to claim 1, wherein in step one, the variation range of the structural feature parameter in the design variables is:
the value-taking distribution interval of the opening width H of the optimized parameter inclined groove is 8-13 mm;
the value taking distribution interval of the inclination angle alpha of the opening of the optimized parameter inclined groove is 30-60 degrees;
the value taking distribution interval of the number N of the optimized parameter blades is 20-40.
3. The optimization method of claim 2, wherein in the second step, the response surface proxy model is a polynomial fit of the objective function by a least square method to realize visualization of the objective function; the basic expression of the objective function is:
Figure FDA0003326352090000021
wherein x isiIs the i-th component, β, of an n-dimensional argument x0Is a constant term undetermined coefficient, betaiIs the primary undetermined coefficient, betaijThe undetermined coefficients of the quadratic term form a column vector beta, n is the number of design variables, and epsilon is an error.
4. An optimization method according to claim 3, characterized in that, for calculating the accuracy of the result, the accuracy of the fitting equation is determined in the form of variance, and the basic expression of the determination is:
Figure FDA0003326352090000022
where N is the number of sample points, yiIn order to be the true response value,
Figure FDA0003326352090000023
the resulting response values are calculated for the response surface model,
Figure FDA0003326352090000024
is the average of the true response values.
5. The optimization method according to claim 4, wherein the third step comprises the following specific steps:
generating an initial population with the size of N in a random mode, and obtaining a first generation offspring population by basic operations of three genetic algorithms of selection, intersection and variation after non-dominated sorting is carried out on the initial population;
combining the offspring population and the parent population from the second generation, performing rapid non-dominant sorting, simultaneously performing congestion degree calculation on the individuals in each non-dominant layer, and selecting N individuals according to the non-dominant relationship and the congestion degree of the individuals and selecting conditions to form a new next generation population;
and then, generating new offspring populations through selection, crossing and mutation operations to circulate in sequence until the conditions of program ending are met.
6. The optimization method according to claim 5, wherein the step four comprises the following specific steps:
if n evaluation objects are provided, and each evaluation object has m indexes, the decision matrix is:
X＝(xij)n×m(i＝1，2，…，n；j＝1，2，…，m)；
normalizing the initial matrix:
Figure FDA0003326352090000031
setting a weighting factor wjWeighting the normalization matrix as:
aij＝wj×bij；
determining a positive ideal solution Z+Negative ideal solution Z-：
Figure FDA0003326352090000032
Calculating the distance between each evaluation object and the positive and negative ideal solutions:
Figure FDA0003326352090000033
calculating closeness ri：
Figure FDA0003326352090000034
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