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This repository has been archived by the owner on Feb 23, 2023. It is now read-only.
currently a batch solution can contain infeasible points in case of batch generation and local penalization (LP). The constrains are checked when the acquisition function is evaluated, but then the acquisition function value is penalized for the local penalization strategy. I would suggest to consider the case of not feasible points as a separate case so that these points will not be consider as possible minima in the next steps. For example, if the constraints are not respected, the penalized acquisition function value is set to infinite. Would this be a proper solution?
Thank you.
The text was updated successfully, but these errors were encountered:
I think I have encountered a similar solution, although I had constructed (naively?) functions which throw assertions then infeasible points are evaluated.
Hi,
currently a batch solution can contain infeasible points in case of batch generation and local penalization (LP). The constrains are checked when the acquisition function is evaluated, but then the acquisition function value is penalized for the local penalization strategy. I would suggest to consider the case of not feasible points as a separate case so that these points will not be consider as possible minima in the next steps. For example, if the constraints are not respected, the penalized acquisition function value is set to infinite. Would this be a proper solution?
Thank you.
The text was updated successfully, but these errors were encountered: