myyouhua.m

来自「大量遗传算法实现程序」· M 代码 · 共 47 行

function  T_SimulationData = myyouhua( T_SimulationData ) ;
% this module simulate the data .
%计算举升中各点坐标，及杆件受力，速度，加速度
%  February 204
%  $Revision: 1.00 $ 
%读入参数
xx1 = T_SimulationData.Position(1).x1;
xx2 = T_SimulationData.Position(1).x2;
xx3 = T_SimulationData.Position(1).x3;
xx4 = T_SimulationData.Position(1).x4;
xx5 = T_SimulationData.Position(1).x5;
xx6 = T_SimulationData.Position(1).x6;
xx7 = T_SimulationData.Position(1).x7;
xx8 = T_SimulationData.Position(1).x8;
xx9 = T_SimulationData.Position(1).x9;
xx10 = T_SimulationData.Position(1).x10;
xx11 = T_SimulationData.Position(1).x11;
xx12 = T_SimulationData.Position(1).x12;
angel = T_SimulationData.Jiaodu;
Sudu = T_SimulationData.Sudu;
Zhongliang = T_SimulationData.Zhongliang;
Julidizuo = T_SimulationData.Julidizuo;
Zhijing = T_SimulationData.Zhijing;

S=T_SimulationData.S;
lb=T_SimulationData.lb;
ub=T_SimulationData.ub;
C_x=T_SimulationData.C_x;
C_y=T_SimulationData.C_y;
B_x=T_SimulationData.B_x;
B_y=T_SimulationData.B_y;
d=T_SimulationData.d;
size=T_SimulationData.size;

% 遗传算法优化计算
   FitnessFunction = @(x) parameterized_fitness(x,S,lb,ub,C_x,C_y,B_x,B_y,d,Julidizuo,xx11,xx12,angel);
   numberOfVariables = 10;
   options = gaoptimset('Vectorized','on','PlotFcns',{@gaplotbestf,@gaplotstopping},'PopInitRange',[lb;ub],'PopulationSize',size);
   
   patternsearchOptions = psoptimset('PlotFcns',{@psplotbestf,@psplotfuncount});
   options = gaoptimset(options,'HybridFcn',{@patternsearch, patternsearchOptions});
   [x,fval] = ga(FitnessFunction,numberOfVariables,options);
   
   T_SimulationData.x = x;