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).