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At this point, it would require adding in new features to the GalacticOptim to support equality constraints.
There should be two places:
amss.md
opt_tax_recur.md
Both use the min_objective and we can keep it that way for now, but ideally we would add support for max_objective if it is more natural in this example.
The text was updated successfully, but these errors were encountered:
jlperla
changed the title
Convert all NLopt calls to use GalacticOptim (after it supports constrained optimization)
Convert all NLopt calls to use Optimization.jl wrapper
Dec 22, 2022
While equality constraints are not supported in the Optimization.jl wrapper, we map be able to port these with inequalities. The reason is that the algorithms used in AMSS don't directly support equality, and internally convert to inequalities---so it should be without loss. Need to see if other equality constrained optimizers are used.
#56 first.
At this point, it would require adding in new features to the
GalacticOptim
to support equality constraints.There should be two places:
amss.md
opt_tax_recur.md
Both use the
min_objective
and we can keep it that way for now, but ideally we would add support formax_objective
if it is more natural in this example.The text was updated successfully, but these errors were encountered: