I'm using interior point algorithm for solving a nonlinear optimization problem and want to provide Hessian of the Lagrangian as part of fmincon to speed up the process (running couple of thousand variations for different sets of parameters)

The workflow that I'm designing has the (nonlinear) objective function, form of linear and nonlinear constraints each in separate function files. Since i'm running different variations of the problems, sometimes there may be zero nonlinear equality & zero nonlinear inequality constraints and in other scenarios, nonzero number of nonlinear equality/inequality constraints. In short the number of nonlinear constraints are dynamic and stored in the 2 variables "NumOfNonLinEqConstr" and "NumOfNonLinInEqConstr"

I have taken a look at Generating Hessian using Symbolic toolbox and few other web-pages but cannot see an example where the Hessian of the Lagrangian is constructed for dynamic number of constraints. In the referred matlab webpage example, like in one variation I tried replacing 10 with NumOfNonLinInEqConstr bu it doesn't work as matlabFunction does not work on cell data type. Can anybody provide a working example for constructing hessian of the lagrangian with dynamic number of nonlinear constraints

Relevant code lines from the matlab link provided below: My question is how could I avoid hard-coding 10 in the below code (and also manually add the product of hessian of the constraint and lambda.ineqnonlin 10 times)?

hessc = cell(1, 10);
for i = 1:10
    hessc{i} = jacobian(gradc(:,i),x);

for i = 1:10
    ii = num2str(i);
    thename = ['hessc',ii];
    filename = [currdir,thename,'.m'];

function H = hessfinal(X,lambda)
% Call the function hessenergy to start
H = hessenergy(X);

% Add the Lagrange multipliers * the constraint Hessians
H = H + hessc1(X) * lambda.ineqnonlin(1);
H = H + hessc2(X) * lambda.ineqnonlin(2);
H = H + hessc3(X) * lambda.ineqnonlin(3);
H = H + hessc4(X) * lambda.ineqnonlin(4);
H = H + hessc5(X) * lambda.ineqnonlin(5);
H = H + hessc6(X) * lambda.ineqnonlin(6);
H = H + hessc7(X) * lambda.ineqnonlin(7);
H = H + hessc8(X) * lambda.ineqnonlin(8);
H = H + hessc9(X) * lambda.ineqnonlin(9);
H = H + hessc10(X) * lambda.ineqnonlin(10);

  • $\begingroup$ In case anybody else has a similar question check out the helpful response I got in Matlab Central. Finally, I have been able to automate the program completely. $\endgroup$ – Hari Jul 24 '14 at 21:31

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