Parallel experiment execution can lead to identical seeds

[abeham]

In #2822 it was possible that multiple optimizers in an experiment were started in parallel. This led to problems that many random seeds were initialized to the same value. For instance, if you have 4 algorithms in an experiment and you execute that with 4 workers each run is likely started with the same random seed resulting in identical runs.

To fix the issue it was suggested to introduce a small timelag, e.g. 20ms when starting the workers. This does not impact the performance a lot and should resolve the problem.

The issue is fixed by implementing a static class RandomSeedGenerator which returns one seed after another from a static instance of System.Random that is guarded by a lock.

[jkarder]

r16071: added RandomSeedGenerator

[gkronber]

r16661: use RandomSeedGenerator in CrossValidation

[gkronber]

reviewed r16071. looks good.