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)

eval_g_ineq

function()

xtol_rel

numeric(1)

xtol_abs

numeric(1)

ftol_rel

numeric(1)

ftol_abs

numeric(1)

start_values

character(1)
Create random start values or based on center 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

### Method clone()

The objects of this class are cloneable with this method.

OptimizerNLoptr$clone(deep = FALSE) #### Arguments deep Whether to make a deep clone. ## Examples # \donttest{ if(requireNamespace("nloptr")) { library(paradox) domain = ParamSet$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$new( objective = objective, search_space = search_space, terminator = terminator) optimizer = opt("nloptr", algorithm = "NLOPT_LN_BOBYQA") # Modifies the instance by reference optimizer$optimize(instance)

# Returns best scoring evaluation
instance$result # Allows access of data.table of full path of all evaluations as.data.table(instance$archive)
}