Provide gradient for Fmincon

Dear all,

How can I include Gradient for Objective Function in code below?

Thank you so much for your help!

Dat

 function [p,fval] = MC_NT(p0,Aeq,beq,N)
    if nargin < 5
        opts = optimoptions('fmincon','Algorithm','interior-point');
    end

    M=length(p0);
    pr1=[0.3185  0.0001  0.1574  0.2902  0.0003  0.00001  0.8426  0.7098  0.6804  0.0822  0.00001  0.00001  0.0008  0.9177  0.00001  0.00001];
    pr=horzcat(pr1,(0.25*ones(48,1)'))';
    p=nan(M,N);
    fval=nan(1,N);

   for i=1:N
    fun=@(p) sum(p.*log(p./pr));
    [p(:,i),fval(i)] = fmincon(fun,p0,[],[],Aeq,beq,[],[],[],opts);
    pr=p(:,i);
   end

Answer 1

[Walter Roberson]

You would have to recode fun as a real function instead of anonymous function, as it is difficult for an anonymous function to return multiple outputs.

The function you provide would need to return the gradient in the second output.

You would need to specify the 'GradObj', 'on' option in your optimoptions()

There is an example showing a gradient calculation at http://www.mathworks.com/help/optim/ug/fmincon.html#busxd7j-1

As you have linear equality constraints but no bounds constraints and no non-linear constraints, you would have the option of switching to trust-region-reflective algorithm once you provide the gradient.