It's easy to think of practical applications, example - I have a folder of videos/mp3s etc and I want to fit them on a few DVD-Rs. This algorithm can calculate the most efficient way of getting the most data on the disk without splitting files.
There are better ways to solve this problem, of course, but the primary goal was to talk about GAs, not to solve the knapsack problem in the most efficient manner.
Now the problem is to find bags types and corresponding amounts such that total cost is maximized.
it ended up starting out greedy, taking large panels first and adaptively backtracking when the current size could not be placed. if by the end of the iteration we did not reach a minimum coverage area, we would backtrack and remove the last significant size panel and fill it with smaller ones. it didnt get us the "optimal" solution but it was fast and more than sufficient.