Merge pull request #129 from kerschke/master

Integration of MO benchmark functions from the CEC2019 competition

DESCRIPTION

@@ -5,8 +5,8 @@ Description: Provides generators for a high number of both single- and multi-
     objective test functions which are frequently used for the benchmarking of
     (numerical) optimization algorithms. Moreover, it offers a set of convenient
     functions to generate, plot and work with objective functions.
-Version: 1.6.0.2
-Date: 2020-01-07
+Version: 1.6.0.3
+Date: 2020-04-01
 Authors@R: c(person("Jakob", "Bossek", email = "j.bossek@gmail.com", role =
     c("aut", "cre")), person("Pascal", "Kerschke", email = "kerschke@uni-muenster.de",
     role = "ctb"))
@@ -32,4 +32,5 @@ Suggests:
 LazyData: yes
 ByteCompile: yes
 LinkingTo: Rcpp, RcppArmadillo
-RoxygenNote: 6.1.1
+RoxygenNote: 7.1.0
+Encoding: UTF-8

NAMESPACE

@@ -172,6 +172,25 @@ export(makeKeaneFunction)
 export(makeKearfottFunction)
 export(makeKursaweFunction)
 export(makeLeonFunction)
+export(makeMMF10Function)
+export(makeMMF11Function)
+export(makeMMF12Function)
+export(makeMMF13Function)
+export(makeMMF14Function)
+export(makeMMF14aFunction)
+export(makeMMF15Function)
+export(makeMMF15aFunction)
+export(makeMMF1Function)
+export(makeMMF1eFunction)
+export(makeMMF1zFunction)
+export(makeMMF2Function)
+export(makeMMF3Function)
+export(makeMMF4Function)
+export(makeMMF5Function)
+export(makeMMF6Function)
+export(makeMMF7Function)
+export(makeMMF8Function)
+export(makeMMF9Function)
 export(makeMOP1Function)
 export(makeMOP2Function)
 export(makeMOP3Function)
@@ -185,13 +204,16 @@ export(makeMcCormickFunction)
 export(makeMichalewiczFunction)
 export(makeModifiedRastriginFunction)
 export(makeMultiObjectiveFunction)
+export(makeOmniTestFunction)
 export(makePeriodicFunction)
 export(makePowellSumFunction)
 export(makePriceN1Function)
 export(makePriceN2Function)
 export(makePriceN4Function)
 export(makeRastriginFunction)
 export(makeRosenbrockFunction)
+export(makeSYMPARTrotatedFunction)
+export(makeSYMPARTsimpleFunction)
 export(makeSchafferN2Function)
 export(makeSchafferN4Function)
 export(makeSchwefelFunction)

NEWS

@@ -1,3 +1,11 @@
+smoof 1.6.3
+===========
+
+* Added MMF1 to MMF13 problems from CEC2019 test suite
+* Added SYM-Part simple, SYM-Part rotated and Omni-Test problems from CEC2019 test suite
+* Added MMF14, MMF14a, MMF15 and MMF15a problems from CEC2019 test suite
+
+
 smoof 1.6.0
 ===========
 

NEWS.md

@@ -1,3 +1,11 @@
+# smoof 1.6.3
+
+## New features
+
+* Added MMF1 to MMF13 problems from CEC2019 test suite
+* Added SYM-Part simple, SYM-Part rotated and Omni-Test problems from CEC2019 test suite
+* Added MMF14, MMF14a, MMF15 and MMF15a problems from CEC2019 test suite
+
 # smoof 1.6.0
 
 ## New features

R/RcppExports.R

@@ -37,6 +37,94 @@ mof_ED_2 <- function(x, m, gamma, theta) {
     .Call(`_smoof_mof_ED_2`, x, m, gamma, theta)
 }
 
+mof_cec2019_SYM_PART_SIMPLE <- function(x, a, b, c) {
+    .Call(`_smoof_mof_cec2019_SYM_PART_SIMPLE`, x, a, b, c)
+}
+
+mof_cec2019_SYM_PART_ROTATED <- function(x, w, a, b, c) {
+    .Call(`_smoof_mof_cec2019_SYM_PART_ROTATED`, x, w, a, b, c)
+}
+
+mof_cec2019_OMNI_Test <- function(x) {
+    .Call(`_smoof_mof_cec2019_OMNI_Test`, x)
+}
+
+mof_cec2019_mmf1 <- function(x) {
+    .Call(`_smoof_mof_cec2019_mmf1`, x)
+}
+
+mof_cec2019_mmf1_z <- function(x, k) {
+    .Call(`_smoof_mof_cec2019_mmf1_z`, x, k)
+}
+
+mof_cec2019_mmf1_e <- function(x, a) {
+    .Call(`_smoof_mof_cec2019_mmf1_e`, x, a)
+}
+
+mof_cec2019_mmf2 <- function(x) {
+    .Call(`_smoof_mof_cec2019_mmf2`, x)
+}
+
+mof_cec2019_mmf3 <- function(x) {
+    .Call(`_smoof_mof_cec2019_mmf3`, x)
+}
+
+mof_cec2019_mmf4 <- function(x) {
+    .Call(`_smoof_mof_cec2019_mmf4`, x)
+}
+
+mof_cec2019_mmf5 <- function(x) {
+    .Call(`_smoof_mof_cec2019_mmf5`, x)
+}
+
+mof_cec2019_mmf6 <- function(x) {
+    .Call(`_smoof_mof_cec2019_mmf6`, x)
+}
+
+mof_cec2019_mmf7 <- function(x) {
+    .Call(`_smoof_mof_cec2019_mmf7`, x)
+}
+
+mof_cec2019_mmf8 <- function(x) {
+    .Call(`_smoof_mof_cec2019_mmf8`, x)
+}
+
+mof_cec2019_mmf9 <- function(x, np) {
+    .Call(`_smoof_mof_cec2019_mmf9`, x, np)
+}
+
+mof_cec2019_mmf10 <- function(x) {
+    .Call(`_smoof_mof_cec2019_mmf10`, x)
+}
+
+mof_cec2019_mmf11 <- function(x, np) {
+    .Call(`_smoof_mof_cec2019_mmf11`, x, np)
+}
+
+mof_cec2019_mmf12 <- function(x, np, q) {
+    .Call(`_smoof_mof_cec2019_mmf12`, x, np, q)
+}
+
+mof_cec2019_mmf13 <- function(x, np) {
+    .Call(`_smoof_mof_cec2019_mmf13`, x, np)
+}
+
+mof_cec2019_mmf14 <- function(x, M, np) {
+    .Call(`_smoof_mof_cec2019_mmf14`, x, M, np)
+}
+
+mof_cec2019_mmf14_a <- function(x, M, np) {
+    .Call(`_smoof_mof_cec2019_mmf14_a`, x, M, np)
+}
+
+mof_cec2019_mmf15 <- function(x, M, np) {
+    .Call(`_smoof_mof_cec2019_mmf15`, x, M, np)
+}
+
+mof_cec2019_mmf15_a <- function(x, M, np) {
+    .Call(`_smoof_mof_cec2019_mmf15_a`, x, M, np)
+}
+
 kursawe <- function(x) {
     .Call(`_smoof_kursawe`, x)
 }

R/mof.SYMPARTrotated.R

@@ -0,0 +1,64 @@
+#' @title
+#' MMF13 Function
+#'
+#' @description
+#' Test problem from the set of "multimodal multiobjective functions" as for
+#' instance used in the CEC2019 competition.
+#' 
+#' @param w [\code{double}(1)]\cr
+#'   Parametrizable factor. In the CEC2019 competition, the organizers used
+#'   \code{w = pi / 4}.
+#' @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
+makeSYMPARTrotatedFunction = function(w = pi / 4, a = 1, b = 10, c = 8) {
+  assertNumber(x = w, finite = TRUE)
+  assertNumber(x = a, finite = TRUE)
+  assertNumber(x = b, finite = TRUE)
+  assertNumber(x = c, finite = TRUE)
+  force(w)
+  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_ROTATED(x = x, w = w, a = a, b = b, c = c))
+  }
+
+  n.objectives = 2L
+  makeMultiObjectiveFunction(
+    name = "SYMPART-rotated function",
+    id = sprintf("SYMPART-rotated-%id-%io", 2L, n.objectives),
+    description = "SYMPART-rotated 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(makeSYMPARTrotatedFunction) = c("function", "smoof_generator")
+attr(makeSYMPARTrotatedFunction, "name") = c("SYMPART-rotated")
+attr(makeSYMPARTrotatedFunction, "type") = c("multi-objective")
+attr(makeSYMPARTrotatedFunction, "tags") = c("multi-objective")

R/mof.SYMPARTsimple.R

@@ -0,0 +1,59 @@
+#' @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")

R/mof.dtlz2.R

@@ -32,6 +32,8 @@
 #' Multi-Objective Optimization Test Problems. Computer Engineering and Networks
 #' Laboratory (TIK), Swiss Federal Institute of Technology (ETH) Zurich, 112, 2001
 #'
+#' @note Note that in case of a bi-objective scenario (\code{n.objectives = 2L}) DTLZ2 and DTLZ5 are identical.
+#'
 #' @param dimensions [\code{integer(1)}]\cr
 #'   Number of decision variables.
 #' @param n.objectives [\code{integer(1)}]\cr

R/mof.dtlz5.R

@@ -39,6 +39,11 @@
 #' @references K. Deb and L. Thiele and M. Laumanns and E. Zitzler. Scalable
 #' Multi-Objective Optimization Test Problems. Computer Engineering and Networks
 #' Laboratory (TIK), Swiss Federal Institute of Technology (ETH) Zurich, 112, 2001
+#' 
+#' @note This problem definition does not exist in the succeeding work of Deb et al. (K. Deb
+#' and L. Thiele and M. Laumanns and E. Zitzler (2002). Scalable multi-objective optimization
+#' test problems, Proceedings of the IEEE Congress on Evolutionary Computation, pp. 825-830).\cr
+#' Also, note that in case of a bi-objective scenario (\code{n.objectives = 2L}) DTLZ2 and DTLZ5 are identical.
 #'
 #' @param dimensions [\code{integer(1)}]\cr
 #'   Number of decision variables.

R/mof.dtlz6.R

@@ -40,6 +40,11 @@
 #' Multi-Objective Optimization Test Problems. Computer Engineering and Networks
 #' Laboratory (TIK), Swiss Federal Institute of Technology (ETH) Zurich, 112, 2001
 #'
+#' @note Attention: Within the succeeding work of Deb et al. (K. Deb and L. Thiele and
+#' M. Laumanns and E. Zitzler (2002). Scalable multi-objective optimization test problems,
+#' Proceedings of the IEEE Congress on Evolutionary Computation, pp. 825-830)
+#' this problem was called DTLZ5.
+#'
 #' @param dimensions [\code{integer(1)}]\cr
 #'   Number of decision variables.
 #' @param n.objectives [\code{integer(1)}]\cr

R/mof.dtlz7.R

@@ -35,6 +35,11 @@
 #' @references K. Deb and L. Thiele and M. Laumanns and E. Zitzler. Scalable
 #' Multi-Objective Optimization Test Problems. Computer Engineering and Networks
 #' Laboratory (TIK), Swiss Federal Institute of Technology (ETH) Zurich, 112, 2001
+#' 
+#' @note Attention: Within the succeeding work of Deb et al. (K. Deb and L. Thiele and
+#' M. Laumanns and E. Zitzler (2002). Scalable multi-objective optimization test problems,
+#' Proceedings of the IEEE Congress on Evolutionary Computation, pp. 825-830)
+#' this problem was called DTLZ6.
 #'
 #' @param dimensions [\code{integer(1)}]\cr
 #'   Number of decision variables.

R/mof.mmf1.R

@@ -0,0 +1,43 @@
+#' @title
+#' MMF1 Function
+#'
+#' @description
+#' Test problem from the set of "multimodal multiobjective functions" as for
+#' instance used in the CEC2019 competition.
+#' 
+#' @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
+makeMMF1Function = function() {
+
+  # C implementation
+  fn = function(x) {
+    assertNumeric(x, len = 2L, any.missing = FALSE, all.missing = FALSE, finite = TRUE)
+    return(mof_cec2019_mmf1(x = x))
+  }
+
+  n.objectives = 2L
+  makeMultiObjectiveFunction(
+    name = "MMF1 function",
+    id = sprintf("MMF1-%id-%io", 2L, n.objectives),
+    description = "MMF1 function",
+    fn = fn,
+    par.set =  makeNumericParamSet(
+      len = 2L,
+      id = "x",
+      lower = c(1, -1),
+      upper = c(3, 1),
+      vector = TRUE
+    ),
+    minimize = rep(TRUE, n.objectives),
+    n.objectives = n.objectives
+  )
+}
+
+class(makeMMF1Function) = c("function", "smoof_generator")
+attr(makeMMF1Function, "name") = c("MMF1")
+attr(makeMMF1Function, "type") = c("multi-objective")
+attr(makeMMF1Function, "tags") = c("multi-objective")