As a special lesson, I would like to show students the very basic idea of genetic\evolutionary algorithms. I let them play a bit in a genetic algorithm online game, to get the idea.
Then I teach them the main concepts (Population, individual with genes, mutation, crossover, fitness etc.) and I introduce the Traveling Salesman Problem. Then I go through solving TSP with genetic algorithm with them, so they see it in action and in practice. However I'm out of practice exercises.
So, I am looking for problems that have a solution which can vary in its "goodness", and its goodness can be judged by some requirements. To explain this, take the example of a timetable for tests over a month. a solution is a random time table. a good solution is one where tests are suffeciently spaced so that students have time to revise. in the game, a solution is just any vehicle, but a good solution, is one that gets far.
Note: I am not necessarily looking for an answer that shows any previous knowledge about genetic algorithms (though it is appreciated
;)), just any problem as described above.
What kinds of exercises\problems such as those are used?
The students are high-school students learning in java, and they are familiar with OOP.