wasn't fmincon supposed to try other values of x before getting to that final result?
No, fmincon is a gradient-based solver (unlike ga) so if x0 is feasible and the gradient there is already zero, then fmincon has no reason to try other points. Often this happens because you have discretization operations like round() or ceil() in your objective function, which make it locally flat almost everwhere. For example, this 1D function is locally flat at all points except the integers:
fun=@(x) floor(x);
opts=optimoptions('fmincon','Display','none');
fplot(fun,[0,5]); xlabel 'x', ylabel 'Objective'
and therefore almost any initial point you choose will be locally optimal,
>> fmincon(fun,1.5,[],[],[],[],0,5,[],opts)
ans =
1.5000
>> fmincon(fun,2.7,[],[],[],[],0,5,[],opts)
ans =
2.7000
>> fmincon(fun,3.99,[],[],[],[],0,5,[],opts)
ans =
3.9900
