Why does NLopt have L-BFGS but not BFGS?
$begingroup$
NLopt, the "free/open-source library for nonlinear optimization, providing a common interface for a number of different free optimization routines..." has a L-BFGS
routine but seemingly, no BFGS
routine. The closest I can see in the list of algorithms might be the SLSQP
routine which does use BFGS
. I have two questions:
- Why is there no
BFGS
routine? - Should I just use the
L-BFGS
routine instead?
Some context. I am using R
which has a basic optim
function that allows you to choose BFGS
and L-BFGS
as algorithms. However, one situation where it is not possible to use L-BFGS
instead of BFGS
is when the objective function evaluates to NaN
at points of the search space. My problem only involves about ten parameters so memory is not an issue.
optimization
$endgroup$
add a comment |
$begingroup$
NLopt, the "free/open-source library for nonlinear optimization, providing a common interface for a number of different free optimization routines..." has a L-BFGS
routine but seemingly, no BFGS
routine. The closest I can see in the list of algorithms might be the SLSQP
routine which does use BFGS
. I have two questions:
- Why is there no
BFGS
routine? - Should I just use the
L-BFGS
routine instead?
Some context. I am using R
which has a basic optim
function that allows you to choose BFGS
and L-BFGS
as algorithms. However, one situation where it is not possible to use L-BFGS
instead of BFGS
is when the objective function evaluates to NaN
at points of the search space. My problem only involves about ten parameters so memory is not an issue.
optimization
$endgroup$
add a comment |
$begingroup$
NLopt, the "free/open-source library for nonlinear optimization, providing a common interface for a number of different free optimization routines..." has a L-BFGS
routine but seemingly, no BFGS
routine. The closest I can see in the list of algorithms might be the SLSQP
routine which does use BFGS
. I have two questions:
- Why is there no
BFGS
routine? - Should I just use the
L-BFGS
routine instead?
Some context. I am using R
which has a basic optim
function that allows you to choose BFGS
and L-BFGS
as algorithms. However, one situation where it is not possible to use L-BFGS
instead of BFGS
is when the objective function evaluates to NaN
at points of the search space. My problem only involves about ten parameters so memory is not an issue.
optimization
$endgroup$
NLopt, the "free/open-source library for nonlinear optimization, providing a common interface for a number of different free optimization routines..." has a L-BFGS
routine but seemingly, no BFGS
routine. The closest I can see in the list of algorithms might be the SLSQP
routine which does use BFGS
. I have two questions:
- Why is there no
BFGS
routine? - Should I just use the
L-BFGS
routine instead?
Some context. I am using R
which has a basic optim
function that allows you to choose BFGS
and L-BFGS
as algorithms. However, one situation where it is not possible to use L-BFGS
instead of BFGS
is when the objective function evaluates to NaN
at points of the search space. My problem only involves about ten parameters so memory is not an issue.
optimization
optimization
asked Jan 22 at 23:59
AlexAlex
193111
193111
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1 Answer
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Although the algorithms are similar, their implementation is quite different: BFGS often constructs and stores the approximated Hessian explicitly, while L-BFGS uses the two-loop recursion by Jorge Nocedal. You can mimic BFGS by setting nlopt_set_vector_storage to a large number (at least the number of iterations).
$endgroup$
add a comment |
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1 Answer
1
active
oldest
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1 Answer
1
active
oldest
votes
active
oldest
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active
oldest
votes
$begingroup$
Although the algorithms are similar, their implementation is quite different: BFGS often constructs and stores the approximated Hessian explicitly, while L-BFGS uses the two-loop recursion by Jorge Nocedal. You can mimic BFGS by setting nlopt_set_vector_storage to a large number (at least the number of iterations).
$endgroup$
add a comment |
$begingroup$
Although the algorithms are similar, their implementation is quite different: BFGS often constructs and stores the approximated Hessian explicitly, while L-BFGS uses the two-loop recursion by Jorge Nocedal. You can mimic BFGS by setting nlopt_set_vector_storage to a large number (at least the number of iterations).
$endgroup$
add a comment |
$begingroup$
Although the algorithms are similar, their implementation is quite different: BFGS often constructs and stores the approximated Hessian explicitly, while L-BFGS uses the two-loop recursion by Jorge Nocedal. You can mimic BFGS by setting nlopt_set_vector_storage to a large number (at least the number of iterations).
$endgroup$
Although the algorithms are similar, their implementation is quite different: BFGS often constructs and stores the approximated Hessian explicitly, while L-BFGS uses the two-loop recursion by Jorge Nocedal. You can mimic BFGS by setting nlopt_set_vector_storage to a large number (at least the number of iterations).
answered Jan 23 at 1:07
LinAlgLinAlg
9,9291521
9,9291521
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