Optimization Instance with budget and archive
Source:R/OptimInstanceMultiCrit.R
OptimInstanceMultiCrit.Rd
Wraps a multi-criteria Objective function with extra services for convenient evaluation. Inherits from OptimInstance.
Automatic storing of results in an Archive after evaluation.
Automatic checking for termination. Evaluations of design points are performed in batches. Before a batch is evaluated, the Terminator is queried for the remaining budget. If the available budget is exhausted, an exception is raised, and no further evaluations can be performed from this point on.
Super class
bbotk::OptimInstance
-> OptimInstanceMultiCrit
Active bindings
result_x_domain
(
list()
)
(transformed) x part of the result in the domain space of the objective.result_y
(
numeric(1)
)
Optimal outcome.
Methods
Method new()
Creates a new instance of this R6 class.
Usage
OptimInstanceMultiCrit$new(
objective,
search_space = NULL,
terminator,
keep_evals = "all",
check_values = TRUE,
callbacks = list()
)
Arguments
objective
(Objective).
search_space
(paradox::ParamSet)
Specifies the search space for the Optimizer. The paradox::ParamSet describes either a subset of thedomain
of the Objective or it describes a set of parameters together with atrafo
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)
Multi-criteria terminator.keep_evals
(
character(1)
)
Keepall
or onlybest
evaluations in archive?check_values
(
logical(1)
)
Should x-values that are added to the archive be checked for validity? Search space that is logged into archive.callbacks
(list of mlr3misc::Callback)
List of callbacks.
Method assign_result()
The Optimizer object writes the best found points and estimated performance values here (probably the Pareto set / front). For internal use.
Arguments
xdt
(
data.table::data.table()
)
Set of untransformed points / points from the search space. One point per row, e.g.data.table(x1 = c(1, 3), x2 = c(2, 4))
. Column names have to match ids of thesearch_space
. However,xdt
can contain additional columns.ydt
(
numeric(1)
)
Optimal outcomes, e.g. the Pareto front.