oi: Syntactic Sugar for Optimization Instance Construction

In bbotk: Black-Box Optimization Toolkit

Syntactic Sugar for Optimization Instance Construction

Description

Function to construct a OptimInstanceBatchSingleCrit and OptimInstanceBatchMultiCrit.

Usage

oi(
  objective,
  search_space = NULL,
  terminator,
  callbacks = NULL,
  check_values = TRUE,
  keep_evals = "all"
)

Arguments

objective	(Objective) Objective function.
search_space	(paradox::ParamSet) Specifies the search space for the Optimizer. The paradox::ParamSet describes either a subset of the domain of the Objective or it describes a set of parameters together with a trafo function that transforms values from the search space to values of the domain. Depending on the context, this value defaults to the domain of the objective.
terminator	Terminator Termination criterion.
callbacks	(list of mlr3misc::Callback) List of callbacks.
check_values	(logical(1)) Should points before the evaluation and the results be checked for validity?
keep_evals	(character(1)) Keep all or only best evaluations in archive?

Examples

# define the objective function
fun = function(xs) {
  list(y = - (xs[[1]] - 2)^2 - (xs[[2]] + 3)^2 + 10)
}

# set domain
domain = ps(
  x1 = p_dbl(-10, 10),
  x2 = p_dbl(-5, 5)
)

# set codomain
codomain = ps(
  y = p_dbl(tags = "maximize")
)

# create objective
objective = ObjectiveRFun$new(
  fun = fun,
  domain = domain,
  codomain = codomain,
  properties = "deterministic"
)

# initialize instance
instance = oi(
  objective = objective,
  terminator = trm("evals", n_evals = 20)
)

bbotk documentation built on Nov. 5, 2025, 6:23 p.m.