OptimizerBatchNLoptr
class that implements non-linear optimization. Calls
nloptr::nloptr()
from package nloptr.
Source
Johnson, G S (2020). “The NLopt nonlinear-optimization package.” https://github.com/stevengj/nlopt.
Parameters
algorithm
character(1)
eval_g_ineq
function()
xtol_rel
numeric(1)
xtol_abs
numeric(1)
ftol_rel
numeric(1)
ftol_abs
numeric(1)
start_values
character(1)
Createrandom
start values or based oncenter
of search space? In the latter case, it is the center of the parameters before a trafo is applied.
For the meaning of the control parameters, see nloptr::nloptr()
and
nloptr::nloptr.print.options()
.
The termination conditions stopval
, maxtime
and maxeval
of
nloptr::nloptr()
are deactivated and replaced by the Terminator
subclasses. The x and function value tolerance termination conditions
(xtol_rel = 10^-4
, xtol_abs = rep(0.0, length(x0))
, ftol_rel = 0.0
and
ftol_abs = 0.0
) are still available and implemented with their package
defaults. To deactivate these conditions, set them to -1
.
Progress Bars
$optimize()
supports progress bars via the package progressr
combined with a Terminator. Simply wrap the function in
progressr::with_progress()
to enable them. We recommend to use package
progress as backend; enable with progressr::handlers("progress")
.
Super classes
bbotk::Optimizer
-> bbotk::OptimizerBatch
-> OptimizerBatchNLoptr
Examples
# \donttest{
if (requireNamespace("nloptr")) {
search_space = domain = ps(x = p_dbl(lower = -1, upper = 1))
codomain = ps(y = p_dbl(tags = "minimize"))
objective_function = function(xs) {
list(y = as.numeric(xs)^2)
}
objective = ObjectiveRFun$new(
fun = objective_function,
domain = domain,
codomain = codomain)
# We use the internal termination criterion xtol_rel
terminator = trm("none")
instance = OptimInstanceBatchSingleCrit$new(
objective = objective,
search_space = search_space,
terminator = terminator)
optimizer = opt("nloptr", algorithm = "NLOPT_LN_BOBYQA")
# Modifies the instance by reference
optimizer$optimize(instance)
# Returns best scoring evaluation
instance$result
# Allows access of data.table of full path of all evaluations
as.data.table(instance$archive)
}
#> x y timestamp batch_nr x_domain_x
#> <num> <num> <POSc> <int> <num>
#> 1: 6.432053e-01 4.137131e-01 2024-10-25 12:52:24 1 6.432053e-01
#> 2: 6.432053e-01 4.137131e-01 2024-10-25 12:52:24 2 6.432053e-01
#> 3: 6.432053e-01 4.137131e-01 2024-10-25 12:52:24 3 6.432053e-01
#> 4: 9.108013e-01 8.295591e-01 2024-10-25 12:52:24 4 9.108013e-01
#> 5: 3.756093e-01 1.410824e-01 2024-10-25 12:52:24 5 3.756093e-01
#> 6: 1.080133e-01 1.166687e-02 2024-10-25 12:52:24 6 1.080133e-01
#> 7: 0.000000e+00 0.000000e+00 2024-10-25 12:52:24 7 0.000000e+00
#> 8: -2.675960e-02 7.160763e-04 2024-10-25 12:52:24 8 -2.675960e-02
#> 9: 2.675960e-03 7.160763e-06 2024-10-25 12:52:24 9 2.675960e-03
#> 10: -2.675960e-04 7.160763e-08 2024-10-25 12:52:24 10 -2.675960e-04
#> 11: 2.675960e-05 7.160763e-10 2024-10-25 12:52:24 11 2.675960e-05
#> 12: -3.091070e-21 9.554716e-42 2024-10-25 12:52:24 12 -3.091070e-21
# }