non linear optimization with fmincon

1 次查看（过去 30 天）

Anoire BEN JDIDIA 2016-11-2

0
链接

此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/310261-non-linear-optimization-with-fmincon

评论： Alexandra Harkai 2016-11-2

Hi, I am solving a nonlinear optimization problem: Xop=fmincon(@ident1,[0.1;0.1],[],[],[],[],[1 1],[50 5]); problem.options =optimset('Display','iter-detailed'); I found Xop= 2.6147 1.0000 I don't understand why the second value of Xop don't change although i change the upper value. If upper value is 0.5 Xop(2)=0.5 Can you help me? thanks

11 个评论
显示 9更早的评论隐藏 9更早的评论

Anoire BEN JDIDIA 2016-11-2

编辑：Walter Roberson 2016-11-2

在 MATLAB Online 中打开

function [eps] =ident1(x)
global Hilb
global tsim
x
eps=sum(abs(Hilb-(x(1)*13270.8617*(55.89*exp(-((tsim- 2.915)/7.182).^2) + 65.16*exp(-((tsim- 378.4)/224.1).^2) +  4.952 *exp(-((tsim-41.41)/9.817).^2) + 8.203*exp(-((tsim-228.6)/ 48.32).^2) +  6.925*exp(-((tsim- 166.4)/54.56).^2) +  2.585*exp(-((tsim-274.2 )/ 28.11).^2) +53.45*exp(-((tsim-50.93)/ 146.7).^2) +  1.155*exp(-((tsim-302)/16.94).^2)-0.29*(30.65*exp(-((tsim-1.463)/1.283).^2) -3.707*exp(-((tsim-12.16)/9.039).^2) +  158.4*exp(-((tsim-9.824e+004)/ 5.722e+004).^2) + 0.09067*exp(-((tsim- 156.9 )/ 0.2263 ).^2)+ 0.1171*exp(-((tsim- 220.8)/23.39).^2) -0.6953*exp(-((tsim- 182.4 )/396.7).^2) + 0.2898*exp(-((tsim- 158.8)/33.83).^2) -0.1958*exp(-((tsim- 183.8)/ 0.3628).^2)))+ x(2)*0.688*(55.89*exp(-((tsim- 2.915)/7.182).^2) + 65.16*exp(-((tsim- 378.4)/224.1).^2) +  4.952 *exp(-((tsim-41.41)/9.817).^2) + 8.203*exp(-((tsim-228.6)/ 48.32).^2) +  6.925*exp(-((tsim- 166.4)/54.56).^2) +  2.585*exp(-((tsim-274.2 )/ 28.11).^2) +53.45*exp(-((tsim-50.93)/ 146.7).^2) +  1.155*exp(-((tsim-302)/16.94).^2)-0.29*(30.65*exp(-((tsim-1.463)/1.283).^2) -3.707*exp(-((tsim-12.16)/9.039).^2) +  158.4*exp(-((tsim-9.824e+004)/ 5.722e+004).^2) + 0.09067*exp(-((tsim- 156.9 )/ 0.2263 ).^2)+ 0.1171*exp(-((tsim- 220.8)/23.39).^2) -0.6953*exp(-((tsim- 182.4 )/396.7).^2) + 0.2898*exp(-((tsim- 158.8)/33.83).^2) -0.1958*exp(-((tsim- 183.8)/ 0.3628).^2))).^2+ 0.87*( 30.65*exp(-((tsim-1.463)/1.283).^2) -3.707*exp(-((tsim-12.16)/9.039).^2) +  158.4*exp(-((tsim-9.824e+004)/ 5.722e+004).^2) + 0.09067*exp(-((tsim- 156.9 )/ 0.2263 ).^2)+ 0.1171*exp(-((tsim- 220.8)/23.39).^2) -0.6953*exp(-((tsim- 182.4 )/396.7).^2) + 0.2898*exp(-((tsim- 158.8)/33.83).^2) -0.1958*exp(-((tsim- 183.8)/ 0.3628).^2)).^2 + x(2)*6156180.1101 +1732750.255 + 567.84 - x(1)*13270.8617*( 39.78*exp(-((tsim- 62.36)/ 51.23 ).^2) + 39.99*exp(-((tsim+13.07)/ 49.11).^2) +  6.574*exp(-((tsim-95.15)/ 7.534).^2) +  7.534*exp(-((tsim-131)/ 20.23).^2) + 3.91e+013*exp(-((tsim- 1.36e+005)/ 2.603e+004).^2) + 15.31*exp(-((tsim-162.5)/49.37).^2) + 11.18*exp(-((tsim- 11.18)/ 41.93).^2) +  5.944*exp(-((tsim- 275.8)/  15.14 ).^2)-0.29*( 4.629e+004*cos(0.01037*tsim) -8.526e+004*sin(0.01037*tsim ) -6.644e+004*cos(2*0.01037*tsim) +  3426 *sin(2*0.01037*tsim) + 3290*cos(3*0.01037*tsim) +  4.341e+004*sin(3*0.01037*tsim) + 2.338e+004 *cos(4*0.01037*tsim) -2284*sin(4*0.01037*tsim) -1166*cos(5*0.01037*tsim) -1.008e+004*sin(5*0.01037*tsim) -3297 *cos(6*0.01037*tsim) + 421.1*sin(6*0.01037*tsim) +  96.45 *cos(7*0.01037*tsim) + 738.4*sin(7*0.01037*tsim) +6.41*cos(8*0.01037*tsim) -10.68*sin(8*0.01037*tsim)))+ x(2)*0.688*(( 39.78*exp(-((tsim- 62.36)/ 51.23 ).^2) + 39.99*exp(-((tsim+13.07)/ 49.11).^2) +  6.574*exp(-((tsim-95.15)/ 7.534).^2) +  7.534*exp(-((tsim-131)/ 20.23).^2) + 3.91e+013*exp(-((tsim- 1.36e+005)/ 2.603e+004).^2) + 15.31*exp(-((tsim-162.5)/49.37).^2) + 11.18*exp(-((tsim- 11.18)/ 41.93).^2) +  5.944*exp(-((tsim- 275.8)/  15.14 ).^2)-0.29*( 4.629e+004*cos(0.01037*tsim) -8.526e+004*sin(0.01037*tsim ) -6.644e+004*cos(2*0.01037*tsim) +  3426 *sin(2*0.01037*tsim) + 3290*cos(3*0.01037*tsim) +  4.341e+004*sin(3*0.01037*tsim) + 2.338e+004 *cos(4*0.01037*tsim) -2284*sin(4*0.01037*tsim) -1166*cos(5*0.01037*tsim) -1.008e+004*sin(5*0.01037*tsim) -3297 *cos(6*0.01037*tsim) + 421.1*sin(6*0.01037*tsim) +  96.45 *cos(7*0.01037*tsim) + 738.4*sin(7*0.01037*tsim) +6.41*cos(8*0.01037*tsim) -10.68*sin(8*0.01037*tsim)))).^2+ 0.87*( 4.629e+004*cos(0.01037*tsim) -8.526e+004*sin(0.01037*tsim ) -6.644e+004*cos(2*0.01037*tsim) +  3426 *sin(2*0.01037*tsim) + 3290*cos(3*0.01037*tsim) +  4.341e+004*sin(3*0.01037*tsim) + 2.338e+004 *cos(4*0.01037*tsim) -2284*sin(4*0.01037*tsim) -1166*cos(5*0.01037*tsim) -1.008e+004*sin(5*0.01037*tsim) -3297 *cos(6*0.01037*tsim) + 421.1*sin(6*0.01037*tsim) +  96.45 *cos(7*0.01037*tsim) + 738.4*sin(7*0.01037*tsim) +6.41*cos(8*0.01037*tsim) -10.68*sin(8*0.01037*tsim)).^2)));
end

Anoire BEN JDIDIA 2016-11-2

在 MATLAB Online 中打开

if i try : problem.options = optimset('Display','iter-detailed','Algorithm','SQP','PlotFcn',@optimplotx);

[xop, ~, exitflag] = fmincon(@ident1,[3;3],[],[],[],[],[1 2.5],[100 100],[],problem.options); i found xop =

    3.1273
    2.5000

Alexandra Harkai 2016-11-2

I don't know all the parameters you are using for your optimisation, but regardless, the best advice I can give is to look at all the previous questions above and try to find out how your optimisation behaves. Check the iteration process, not just the final result. Check the linked MATLAB Documentation here too.

请先登录，再进行评论。

请先登录，再回答此问题。

回答（0 个）

请先登录，再回答此问题。

类别

MATLAB Mathematics Optimization

在 Help Center 和 File Exchange 中查找有关 Optimization 的更多信息

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by

non linear optimization with fmincon

11 个评论
显示 9更早的评论隐藏 9更早的评论

回答（0 个）

另请参阅

类别

标签

Community Treasure Hunt

non linear optimization with fmincon

11 个评论 显示 9更早的评论隐藏 9更早的评论

回答（0 个）

另请参阅

类别

标签

Community Treasure Hunt

11 个评论
显示 9更早的评论隐藏 9更早的评论