YourSymbolicExpression = sym(YourString);
SV = symvar(YourSymbolicExpression);
f = matlabFunction(YourSymbolicExpression, {SV});
gr = gradient(YourSymbolicExpression, SV);
grf = matlabFunction(gr, 'vars', {SV});
hess = hessian(YourSymbolicExpression, SV);
hessf = matlabFunction(hess, 'vars', {SV});
Now f and grf will be the handles of anonymous function which take a row vector of values. f would in itself be suitable as an objective function and grf would be suitable as a gradient function. However if you are using gradient functions (or hessian) with fmincon trust-region-reflective then you need pack them all into one function that only assigns outputs conditionally. You can do that with something like,
Frm = @(x) FunGrad(x, f, grf, hessf);
and pass Frm to fmincon,
where FunGrad is something like,
function [F,g, h] = FunGrad(x, Fun, Grad, Hess)
F = Fun(x);
if nargout > 1
g = Grad(x);
end
if nargout > 2
h = Hess(x);
end
end
