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fminunc stopped because it cannot decrease the objective function along the current search direction.

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Ola Debiec
Ola Debiec on 30 Apr 2020
Commented: Ola Debiec on 2 May 2020
Hi, I'm trying to use fminunc function with the gradient but it doesn't work properly.
my start point is: [1.5;-2.5]
this is my objective function:
function [f, g, H] = rosenboth(x)
% Calculate objective f
a = 0.5;
b = -1.5;
f = (1 - x(1) + a)^2 + 100 * (x(2) - b - (x(1) - a)^2)^2;
if nargout > 1 % gradient required
g = [2 * (-200 * (x(1) - 1) * (-x(1)^2 + 2 * x(1) + x(2)) + x(1) - 2);
200 * (-x(1)^2 + 2 * x(1) + x(2))];
if nargout > 2 % Hessian required
H = [1200 * x(1)^2 - 2400 * x(1) - 400 * x(2) + 802, -400 * (x(1) - 1);
-400 * (x(1) - 1), 200];
end
end
and that's the generated code from optimtool
function [x,fval,exitflag,output,grad,hessian] = fmin_gradient(x0,OptimalityTolerance_Data,StepTolerance_Data)
%% This is an auto generated MATLAB file from Optimization Tool.
%% Start with the default options
options = optimoptions('fminunc');
%% Modify options setting
options = optimoptions(options,'Display', 'off');
options = optimoptions(options,'OptimalityTolerance', OptimalityTolerance_Data);
options = optimoptions(options,'FunctionTolerance', OptimalityTolerance_Data);
options = optimoptions(options,'StepTolerance', StepTolerance_Data);
options = optimoptions(options,'PlotFcn', @optimplotfval);
options = optimoptions(options,'Algorithm', 'quasi-newton');
options = optimoptions(options,'SpecifyObjectiveGradient', true);
options = optimoptions(options,'Hessian', 'off');
[x,fval,exitflag,output,grad,hessian] = fminunc(@rosenboth,x0,options);
end

Accepted Answer

Alan Weiss
Alan Weiss on 1 May 2020
Please run with the CheckGradients option set to true. I think that you will find that you did not calculate the derivatives correctly.
Alan Weiss
MATLAB mathematical toolbox documentation

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