smoof: mnof – R documentation

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mnof

Helper function to create numeric multi-objective optimization test function.

Description

This is a simplifying wrapper around makeMultiObjectiveFunction. It can be used if the function to generate is purely numeric to save some lines of code.

Usage

mnof(name = NULL, id = NULL, par.len = NULL, par.id = "x",
  par.lower = NULL, par.upper = NULL, n.objectives,
  description = NULL, fn, vectorized = FALSE, noisy = FALSE,
  fn.mean = NULL, minimize = rep(TRUE, n.objectives),
  constraint.fn = NULL, ref.point = NULL)

Arguments

`name`	[`character(1)`] Function name. Used for the title of plots for example.
`id`	[`character(1)` \| `NULL`] Optional short function identifier. If provided, this should be a short name without whitespaces and now special characters beside the underscore. Default is `NULL`, which means no ID at all.
`par.len`	[`integer(1)`] Length of parameter vector.
`par.id`	[`character(1)`] Optional name of parameter vector. Default is “x”.
`par.lower`	[`numeric`] Vector of lower bounds. A single value of length 1 is automatically replicated to `n.pars`. Default is -Inf.
`par.upper`	[`numeric`] Vector of upper bounds. A singe value of length 1 is automatically replicated to `n.pars`. Default is Inf.
`n.objectives`	[`integer(1)`] Number of objectives of the multi-objective function.
`description`	[`character(1)` \| `NULL`] Optional function description.
`fn`	[`function`] Objective function.
`vectorized`	[`logical(1)`] Can the objective function handle “vector” input, i.~e., does it accept matrix of parameters? Default is `FALSE`.
`noisy`	[`logical(1)`] Is the function noisy? Defaults to `FALSE`.
`fn.mean`	[`function`] Optional true mean function in case of a noisy objective function. This functions should have the same mean as `fn`.
`minimize`	[`logical`] Logical vector of length `n.objectives` indicating if the corresponding objectives shall be minimized or maximized. Default is the vector with all components set to `TRUE`.
`constraint.fn`	[`function \| NULL`] Function which returns a logical vector indicating whether certain conditions are met or not. Default is `NULL`, which means, that there are no constraints beside possible box constraints defined via the `par.set` argument.
`ref.point`	[`numeric`] Optional reference point in the objective space, e.g., for hypervolume computation.

Examples

# first we generate the 10d sphere function the long way
fn = makeMultiObjectiveFunction(
  name = "Testfun",
  fn = function(x) c(sum(x^2), exp(sum(x^2))),
  par.set = makeNumericParamSet(
    len = 10L, id = "a",
    lower = rep(-1.5, 10L), upper = rep(1.5, 10L)
  ),
  n.objectives = 2L
)

# ... and now the short way
fn = mnof(
 name = "Testfun",
 fn = function(x) c(sum(x^2), exp(sum(x^2))),
 par.len = 10L, par.id = "a", par.lower = -1.5, par.upper = 1.5,
 n.objectives = 2L
)

smoof

Single and Multi-Objective Optimization Test Functions

v1.6.0.2

BSD_2_clause + file LICENSE

Authors

Jakob Bossek [aut, cre], Pascal Kerschke [ctb]

Initial release

2020-02-17