One of my favorite stories about genetic algorithms is how they made an e ink display work. Taken from a Stack Overflow thread:
>In January 2004, I was contacted by Philips New Display Technologies who were creating the electronics for the first ever commercial e-ink, the Sony Librie, who had only been released in Japan, years before Amazon Kindle and the others hit the market in US an Europe.
>The Philips engineers had a major problem. A few months before the product was supposed to hit the market, they were still getting ghosting on the screen when changing pages. The problem was the 200 drivers that were creating the electrostatic field. Each of these drivers had a certain voltage that had to be set right between zero and 1000 mV or something like this. But if you changed one of them, it would change everything.
>So optimizing each driver's voltage individually was out of the question. The number of possible combination of values was in billions,and it took about 1 minute for a special camera to evaluate a single combination. The engineers had tried many standard optimization techniques, but nothing would come close.
>The head engineer contacted me because I had previously released a Genetic Programming library to the open-source community. He asked if GP/GA's would help and if I could get involved. I did, and for about a month we worked together, me writing and tuning the GA library, on synthetic data, and him integrating it into their system. Then, one weekend they let it run live with the real thing.
>The following Monday I got these glowing emails from him and their hardware designer, about how nobody could believe the amazing results the GA found. This was it. Later that year the product hit the market.
>I didn't get paid one cent for it, but I got 'bragging' rights. They said from the begining they were already over budget, so I knew what the deal was before I started working on it. And it's a great story for applications of GAs. :)