soo_function: Single Objective Optimization Function

In soobench: Single Objective Optimization Benchmark Functions

Description

Define a new soo_function object.

Usage

soo_function(
  name,
  id,
  fun,
  dimensions,
  lower_bounds,
  upper_bounds,
  best_value,
  best_par
)

Arguments

name	Name of function.
id	Short id for the function. Must be unique to the function instance and should not contain any other characters than [a-z], [0-9] and ‘-’.
fun	Function definition.
dimensions	Size of parameter space.
lower_bounds	Lower bounds of the parameter space.
upper_bounds	Upper bounds of the parameter space.
best_value	Best known function value.
best_par	Parameter settings that correspond to best_value. If there are multiple global minima, this should be a list with one entry for each minimum.

Value

A soo_function object.

Examples

## Given the following simple benchmark function:
f_my_sphere <- function(x)
  sum((x-1)*(x-1))

## we can define a corresponding 2d soo_function:
f <- soo_function("My Sphere", "my-sphere-2d", f_my_sphere, 2,
                  c(-10, -10), c(10, 10),
                  0, c(1, 1))

## And then plot it:
plot(f)

soobench documentation built on Feb. 9, 2020, 5:08 p.m.