Run the variable neighborhood trust region search algorithm.
Usage
vntrs(
f,
npar,
minimize = TRUE,
init_runs = 5L,
init_min = -1,
init_max = 1,
init_iterlim = 20L,
neighborhoods = 5L,
neighbors = 5L,
beta = 0.05,
iterlim = 100L,
tolerance = 1e-06,
inferior_tolerance = 1e-06,
time_limit = NULL,
cores = 1L,
lower = NULL,
upper = NULL,
collect_all = FALSE,
quiet = TRUE
)Arguments
- f
[
function]
A function that accepts anumericparameter vector and returns eithera
numericobjective value, ora
listwithvalueand optionalgradientandhessiancomponents.
Missing derivatives are approximated by finite differences.
- npar
[
integer(1)]
The number of parameters off.- minimize
[
logical(1)]
IfTRUE, minimizef; otherwise, maximize it.- init_runs
[
integer(1)]
Number of random starting points for the initialization stage.- init_min, init_max
[
numeric(1)]
Lower and upper bounds for the uniform initialization range.- init_iterlim
[
integer(1)]
Maximum trust-region iterations during initialization.- neighborhoods
[
integer(1)]
Number of neighborhood expansions to try.- neighbors
[
integer(1)]
Number of trial points sampled in each neighborhood.- beta
[
numeric(1)]
Non-negative scaling factor for neighborhood expansion.- iterlim
[
integer(1)]
Maximum trust-region iterations during the main search.- tolerance
[
numeric(1)]
Minimum Euclidean distance for two optima to be treated as distinct.- inferior_tolerance
[
numeric(1)]
Maximum objective-value gap from the best known solution before a local optimum is discarded early.- time_limit
[
numeric(1)|NULL]
Optional time limit in seconds. If reached, the search stops early with a warning.- cores
[
integer(1)]
Number of CPU cores used for parallel evaluation.- lower, upper
[
numeric(npar)|NULL]
Optional lower and upper parameter bounds. UseNULLfor unbounded dimensions.- collect_all
[
logical(1)]
IfTRUE, keep all converged local optima and disable early stopping for optima that are inferior to the best known solution.- quiet
[
logical(1)]
IfTRUE, suppress progress messages.
References
Bierlaire et al. (2009) "A Heuristic for Nonlinear Global Optimization" doi:10.1287/ijoc.1090.0343 .
