conversion function

Conversion between minimization and maximization problems.

Conversion between minimization and maximization problems.

We can minimize f by maximizing -f. The majority of predefined objective functions in smoof should be minimized by default. However, there is a handful of functions, e.g., Keane or Alpine02, which shall be maximized by default. For benchmarking studies it might be beneficial to inverse the direction. The functions convertToMaximization and convertToMinimization

do exactly that keeping the attributes.

convertToMaximization(fn) convertToMinimization(fn)

Arguments

  • fn: [smoof_function]

    Smoof function.

Returns

[smoof_function]

Note

Both functions will quit with an error if multi-objective functions are passed.

Examples

# create a function which should be minimized by default fn = makeSphereFunction(1L) print(shouldBeMinimized(fn)) # Now invert the objective direction ... fn2 = convertToMaximization(fn) # and invert it again fn3 = convertToMinimization(fn2) # Now to convince ourselves we render some plots opar = par(mfrow = c(1, 3)) plot(fn) plot(fn2) plot(fn3) par(opar)
  • Maintainer: Jakob Bossek
  • License: BSD_2_clause + file LICENSE
  • Last published: 2023-03-10