As someone who has used genetic algorithms (GA) and simulated annealing (SA) to solve complex infinite-answer problems I can tell you whoever wrote that little blurb doesn’t have a clue about how they work.
GAs use generations to create a wide range of solutions. You start with disorder - random seeding of the possible answers within a problem. Then you grade the answers, cull the answers (weakest tend to die - but not always, and the strongest tend to survive - but not always). Then you let the survivors “breed” by creating offspring answers with traits of both parents AND potential mutations (harmful or helpful) added in.
Repeat as necessary, until you get a solution set that you accept with your own pre-conceived idea of “success”. There isn’t an “end” to the algorithm, it will keep happily spinning away, creating an infinite set of answers that all are viable in their own way.
GAs and SAs are highly useful in situations where there isn’t a “best answer”. Where you can have dozens - or sometimes, infinite - answers that will work for your situation. And where the problem space has dozens, hundreds, or even thousands of variables (the genes). GAs and SAs are ways to identify very good answers for extremely complex problem spaces in a very short amount of time.
Typically you’ll see an N^2 reduction in processing and search time over a standard brute-force solution approach. Suddenly problems that were too computationally complex to ever answer can be addressed.
The fact that there is a pre-determined “stop executing” point is not a function of the evolutionary nature of a GA; it is simply a recognition that there’s not need to continue looking for answers after you have one...
And the fact there is a “stop executing” point does not mean your answer is pre-ordained. I’ve run GAs on the same problem set, with the same initial seeding, and come up with different - but still very viable and useful - results.
Sounds like trial and error intelligent human design to me.
Genetic algorithms are irrelevant to evolution
David Abel, The Gene Emergence Project, The Origin of Life Science Foundation
http://creation.com/genetic-algorithms-are-irrelevant-to-evolution