Multi Criteria Optimization Instance for Batch Optimization
Source:R/OptimInstanceBatchMultiCrit.R
OptimInstanceBatchMultiCrit.Rd
The OptimInstanceBatchMultiCrit specifies an optimization problem for an OptimizerBatch.
The function oi()
creates an OptimInstanceBatchMultiCrit.
Super classes
bbotk::OptimInstance
-> bbotk::OptimInstanceBatch
-> OptimInstanceBatchMultiCrit
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
OptimInstanceBatchMultiCrit$new(
objective,
search_space = NULL,
terminator,
check_values = TRUE,
callbacks = NULL,
archive = NULL
)
Arguments
objective
(Objective)
Objective function.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
Termination criterion.check_values
(
logical(1)
)
Should points before the evaluation and the results be checked for validity?callbacks
(list of mlr3misc::Callback)
List of callbacks.archive
(Archive).
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
(
data.table::data.table()
)
Optimal outcome....
(
any
)
ignored.