newuoa: New Unconstrained Optimization with quadratic Approximation
Description
NEWUOA solves quadratic subproblems in a spherical trust regionvia a
truncated conjugate-gradient algorithm. For bound-constrained problems,
BOBYQA shold be used instead, as Powell developed it as an enhancement
thereof for bound constraints.
Usage
newuoa(x0, fn, nl.info = FALSE, control = list(), ...)
Arguments
x0
starting point for searching the optimum.
fn
objective function that is to be minimized.
nl.info
logical; shall the original NLopt info been shown.
control
list of options, see nl.opts for help.
...
additional arguments passed to the function.
Value
List with components:
par
the optimal solution found so far.
value
the function value corresponding to par.
iter
number of (outer) iterations, see maxeval.
convergence
integer code indicating successful completion (> 0)
or a possible error number (< 0).
message
character string produced by NLopt and giving additional
information.
Details
This is an algorithm derived from the NEWUOA Fortran subroutine of Powell,
converted to C and modified for the NLOPT stopping criteria.
References
M. J. D. Powell. ``The BOBYQA algorithm for bound constrained
optimization without derivatives,'' Department of Applied Mathematics and
Theoretical Physics, Cambridge England, technical reportNA2009/06 (2009).