Bad exception handling in gradient_minimize .

[bryan-lunt]

gradient_minimize will partially roll back optimization if there is some kind of exception.
This means even if the previous parameter vector was acceptable and good.
When the exception happens, it does not save the objective function value that corresponds to the parameter vector that it does save (whatever that is.) It saves that value from the parameter vector that it didn't like.

This issue is multifold :

1. The best parameter vector seen is not saved.
2. The objective value reported is not that of the parameter vector that was saved.

[bryan-lunt]

Irrelevant now that we've moved to NLOPT. (This had to do with GSL based code.)