OptimizerNLoptr 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)

x0

numeric()

eval_g_ineq

function()

xtol_rel

numeric(1)

xtol_abs

numeric(1)

ftol_rel

numeric(1)

ftol_abs

numeric(1)

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.

Super class

bbotk::Optimizer -> OptimizerNLoptr

Methods

Public methods

Inherited methods

Method new()

Creates a new instance of this R6 class.

Usage

OptimizerNLoptr$new()


Method clone()

The objects of this class are cloneable with this method.

Usage

OptimizerNLoptr$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

Examples

# \donttest{ library(paradox) library(data.table) domain = ParamSet$new(list(ParamDbl$new("x", lower = -1, upper = 1))) search_space = ParamSet$new(list(ParamDbl$new("x", lower = -1, upper = 1))) codomain = ParamSet$new(list(ParamDbl$new("y", tags = "minimize"))) objective_function = function(xs) { list(y = as.numeric(xs)^2) } objective = ObjectiveRFun$new(fun = objective_function, domain = domain, codomain = codomain) # We use the internal termination criterion xtol_rel terminator = trm("none") instance = OptimInstanceSingleCrit$new(objective = objective, search_space = search_space, terminator = terminator) optimizer = opt("nloptr", x0 = 1, algorithm = "NLOPT_LN_BOBYQA") # Modifies the instance by reference optimizer$optimize(instance)
#> x x_domain y #> 1: 0 <list[1]> 0
# Returns best scoring evaluation instance$result
#> x x_domain y #> 1: 0 <list[1]> 0
# Allows access of data.table of full path of all evaluations instance$archive$data()
#> x y x_domain timestamp batch_nr #> 1: 1e+00 1.0e+00 <list[1]> 2020-11-26 04:14:18 1 #> 2: 1e+00 1.0e+00 <list[1]> 2020-11-26 04:14:18 2 #> 3: 1e+00 1.0e+00 <list[1]> 2020-11-26 04:14:18 3 #> 4: 5e-01 2.5e-01 <list[1]> 2020-11-26 04:14:18 4 #> 5: 0e+00 0.0e+00 <list[1]> 2020-11-26 04:14:18 5 #> 6: -5e-02 2.5e-03 <list[1]> 2020-11-26 04:14:18 6 #> 7: 5e-03 2.5e-05 <list[1]> 2020-11-26 04:14:18 7 #> 8: -5e-03 2.5e-05 <list[1]> 2020-11-26 04:14:18 8 #> 9: -5e-04 2.5e-07 <list[1]> 2020-11-26 04:14:18 9 #> 10: 5e-04 2.5e-07 <list[1]> 2020-11-26 04:14:18 10 #> 11: 0e+00 0.0e+00 <list[1]> 2020-11-26 04:14:18 11
# }