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Currently, the linear_dominted_bounder and quadratic_fast_bounder only improves the lower bound, there isn't an implemented way to use these algorithms to improve the upper bound. I have two options in mind to solve this
Implement a modified version of the algorithms to address the upper bound case.
Make an auxiliary function whose purpose is to apply the algorithms to the negative of the Taylor Model which gives the desired results.
I think the last one is the best option since is easier to implement, but I don't know if this approach will give unexpected results for some cases.
The text was updated successfully, but these errors were encountered:
I would proceed as you suggest, using the negative of the TaylorModel. One would expect a factor ~2 in the time to improve both bounds. This probably can be optimized by naive paralelization, using e.g. @threads.
Currently, the
linear_dominted_bounder
andquadratic_fast_bounder
only improves the lower bound, there isn't an implemented way to use these algorithms to improve the upper bound. I have two options in mind to solve thisI think the last one is the best option since is easier to implement, but I don't know if this approach will give unexpected results for some cases.
The text was updated successfully, but these errors were encountered: