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#' @title
#' MMF13 Function
#'
#' @description
#' Test problem from the set of "multimodal multiobjective functions" as for
#' instance used in the CEC2019 competition.
#'
#' @param a [\code{double}(1)]\cr
#' Parametrizable factor. In the CEC2019 competition, the organizers used
#' \code{a = 1}.
#' @param b [\code{double}(1)]\cr
#' Parametrizable factor. In the CEC2019 competition, the organizers used
#' \code{b = 10}.
#' @param c [\code{double}(1)]\cr
#' Parametrizable factor. In the CEC2019 competition, the organizers used
#' \code{c = 8}.
#'
#' @references
#' Caitong Yue, Boyang Qu, Kunjie Yu, Jing Liang, and Xiaodong Li, "A novel
#' scalable test problem suite for multimodal multiobjective optimization," in
#' Swarm and Evolutionary Computation, Volume 48, August 2019, pp. 62–71, Elsevier.
#' @return [\code{smoof_multi_objective_function}]
#' @export
makeSYMPARTsimpleFunction = function(a = 1, b = 10, c = 8) {
assertNumber(x = a, finite = TRUE)
assertNumber(x = b, finite = TRUE)
assertNumber(x = c, finite = TRUE)
force(a)
force(b)
force(c)
# C implementation
fn = function(x) {
assertNumeric(x, len = 2L, any.missing = FALSE, all.missing = FALSE, finite = TRUE)
return(mof_cec2019_SYM_PART_SIMPLE(x = x, a = a, b = b, c = c))
}
n.objectives = 2L
makeMultiObjectiveFunction(
name = "SYMPART-simple function",
id = sprintf("SYMPART-simple-%id-%io", 2L, n.objectives),
description = "SYMPART-simple function",
fn = fn,
par.set = makeNumericParamSet(
len = 2L,
id = "x",
lower = rep(-20, 2L),
upper = rep(20, 2L),
vector = TRUE
),
minimize = rep(TRUE, n.objectives),
n.objectives = n.objectives
)
}
class(makeSYMPARTsimpleFunction) = c("function", "smoof_generator")
attr(makeSYMPARTsimpleFunction, "name") = c("SYMPART-simple")
attr(makeSYMPARTsimpleFunction, "type") = c("multi-objective")
attr(makeSYMPARTsimpleFunction, "tags") = c("multi-objective")
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