non linear optimization with fmincon

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Anoire BEN JDIDIA 2016-11-2

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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

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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.

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