It is not really a mistake, except perhaps a mistake of choice. Or you might say a mistake of understanding the tools involved.
GA is a stochastic algorithm. It is good at trying to not get stuck in a local minimum, while still trying to find the global solution. But it is not really that good at zeroing in on the exact solution. Or if you try to force it to do so, a stochastic optimizer will take a longer time to do so, because it will require many function evaluations.
Fmincon is designed to move down a smoothly structured surface, with rapid convergence when the solution is near. If you want, think of the quadratic convergence behavior of algorithms in the class of Newton's method.
Different algoithms have differing performance, and different things they do really well.
So you can have it either way, but you cannot so easily have the best of all worlds. Yes, I suppose you could use GA to do as well as it can in areasonable amount of time, then when it terminates, switch to fmincon to hone in on the solution.
