It might be inefficient in absolute time, but in terms of programmer effort genetic algorithms can be tremendously efficient.<p>I used a genetic algorithm to optimize a signal processing routine in my research (I'm a grad student in biological engineering, the project is sizing nanoparticles).  It took me 3 days to write and debug a mutation algorithm, a fitness score, and a backbone that iterates breeding a new generation of code and keeping the most fit offspring.  I started running the code on a Friday and by Monday morning, at around 500 generations, the fitness score had improved 60%.  Colleagues of ours working on a very similar problem spent 3 months doing the same thing manually and only got to about 55% improvement.<p>I spent that weekend sailing and thinking, I'm glad my computer is doing my work for me right now.