I largely agree with you, but there are recent pushes to make the study of genetic algorithms (usually not stated this way) more palatable to the theory community. Look, for example, to the work of Christos Papadimitriou [1] (who is the anti snake-oil guy if I've ever seen one). He gave a talk last year at the Simons Institute on his ideas [2]. See also [3].

The essential argument of this new school is that GAs (and evolution in general) do not try to find the optimal individual. Here is a reader's digest argument as to why: say you had actually achieved the perfect individual, then sex would result in imperfect children while the parents die off. So if evolution isn't optimizing fitness, what is it optimizing? One hypothesis is that it's balancing fitness and variation, so that if the environment changes drastically the entire population does not die off.

[Edit: another note to add] And there is a common adage in CS theory that for every problem, a focused gradient descent algorithm (using knowledge about the optimization function, domain, etc.) will always outperform GA. So this is a sort of meta-theorem that says asexual reproduction is better at finding the optimal individual than sexual reproduction.

There are concrete techniques being analyzed in this context, for example the "Multiplicative Weights Update Algorithm," which has been proven to perform well against adversarial manipulations of the environment. See [4] for a long and detailed reference of its applications to classical CS problems.

[1]: http://www.informatik.uni-trier.de/~ley/pers/hd/p/Papadimitr... [2]: https://www.youtube.com/watch?v=cWv-s6KuDlM [3]: http://simons.berkeley.edu/programs/evolution2014 [4]: https://www.cs.princeton.edu/~arora/pubs/MWsurvey.pdf