As I understand GAs, this is misleading. "The optimized solution" implies that there is a single optimal solution that is known to the searcher beforehand. As PGS describes them, though, and from other things I've read, that's not true. The searcher establishes parameters for what will constitute a successful solution, but doesn't know exactly what that solution will be until the GA arrives at it.
He also says "The appeal of GAs is that they are modeled after biological evolution. The latter is the main motivation for tolerating such an inefficient awkward process." From PGS's description, they're not inefficient or awkward at all--they're actually more efficient than trying to arrive at a solution through a completely directed process, because they can explore the entire solution space at the same time.
The rest of that excerpt seems to be mostly bald assertions. For one, I don't see why we can't learn about physical processes from formal representations. He puts it in italics, but it's still just his assertion.
Okay, when the program "displaying" the genetic algorithm terminates, describe the "solution". When does the genetic algorithm program terminate? Why does it terminate?