M
martinus
Hi all, I am writing an particle swarm optimizer that tries to find
good floating point values for optimization problems. I have several
test cases, and some target fitness value that the optimizer should be
able to reach. The problem is that since such optimizers make lots of
use of random numbers, so the optimizer can only find in about 90% of
the cases the target fitness value. I can relax the target fitness
value, than 95% of the runs are ok; but that is not really a solution.
Any ideas how to write tests when you have such an uncertainty about
the result?
Martin
good floating point values for optimization problems. I have several
test cases, and some target fitness value that the optimizer should be
able to reach. The problem is that since such optimizers make lots of
use of random numbers, so the optimizer can only find in about 90% of
the cases the target fitness value. I can relax the target fitness
value, than 95% of the runs are ok; but that is not really a solution.
Any ideas how to write tests when you have such an uncertainty about
the result?
Martin