Sure 'genetic' sounds cool, but when the search space is as limited as it is in a build order optimization like this, you should use the right tools for the task.
What stands out is if you had asked anyone even a professional player to build this exact army composition (7 roaches) they would almost certainly not have pulled it off as fast as the method this algorithm discovered. The algorithm was able to do it by doing a few tricks that normally aren't intuitive but, work out so your resources match up perfectly to make the build happen.
Also, I can confirm as a mediocre Starcraft player the build was quite powerful.
How would a breadth first search work better? The search space is huge.
If your edges are 'building things' and your nodes are records of some type (current time, number of stuff, stuff currently building), then you can calculate when you will be able to build what next, and generate the descendent states.
Given we are interested in four types of buildings and three types of units, that's maximum 7 descendents per node. Getting to 7 roaches doesn't require more than 20-30 actions. That's 7^30 and too much, but a lot of states are easy to prune, e.g. don't build 2 zergling dens, and on top of that you can add some goal searching heuristics, like a*.