So when you search randomly and reach up to a set of optimised parameters, how do you know if it can't be optimised any further, since you haven't looked up all possible sets like in a grid?
You generally don't know if you've reached a suitable maxima, which is why it is good to run a nondeterministic optimizer a few times (if computation power allows) and see if there are any reliable parameters form there.
There are also somewhat better-than-random strategies such as Bayesian optimization and particle swarm optimization that can help you to search more efficiently.
