How do I use multi-parameters in my optimization problem for fminunc?

So, right now, I am performing an optimization with respect to all elements of 'A' matrix using below command.

[Aopt,fopt]=fminunc(@(A)myObjective(A,N33,p1,v,limit,n),A0,options);

But now I want an extra parameter (x) to be used for optimization also. This will be a scalar. Is the code will look like this?

[Aopt,fopt]=fminunc(@(A,x)myObjective(A,x,N33,p1,v,limit,n),A0,x0,options);

Thanks in advance.

Answer 1

[Matt J]

You can do something like that in the problem-based framework.

A=optimvar('A',N,3);
x=optimvar('x',1);

fun=fcn2optimexpr(  @(A,x)myObjective(A,x,N33,p1,v,limit,n)   , A x)

 sol0.A=...  %initial A0
 sol0.x=...  %initial x0
sol=solve( optimproblem('Objective',fun) ,  sol0,options);

[Satyajit Ghosh]

After implementing above code segment, I am getting this error.

Error using optim.internal.problemdef.ProblemImpl/solveImpl

Expected a string scalar or character vector for the parameter name

Error in optim.problemdef.OptimizationProblem/solve

Error in Optimization_FINAL.m (line 145)

sol=solve(optimproblem('Objective',fun),sol0,options);

Answer 2

[John D'Errico]

No. It won't look like that. fminunc cannot somehow magically know how you intend the inputs to be used. Computers cannot read your mind. Well, not yet, but the mind reading toolbox is still under beta test.

Functions assume the input paraneters are as they are defined in the help.

If you want to optimize both A and x, then you need to treat all parameters in one vector (or array). Split them apart inside your objective function.