#optimization #function

optlib-testfunc

The functions to test optimization algorithms

1 unstable release

0.1.0 Nov 23, 2019

#146 in #function


Used in optlib

MIT license

6KB

optlib-testfunc

Current Version Documentation License

The crate contains functions for optimization algorithms testing. All functions have one global minimum.

Optlib-testfunc contains in this version follow function:

  • Paraboloid. y = (x0 - 1)^2 + (x1 - 2)^2 + (x2 - 3)^2 ... (xn - n)^2. For any x global minimum located in x' = (1.0, 2.0, ..., n). f(x') = 0.
  • The Schwefel function. For any x lies in [-500.0; 500.0] global minimum located in x' = (420.9687, 420.9687, ...). f(x') = 0.
  • The Rastrigin function. For any x lies in [-5.12; 5.12] global minimum located in x' = (0, 0, ...). f(x') = 0.
  • The Rosenbrock function. For any x lies in [-inf; inf] global minimum located in x' = (1, 1, ...). f(x') = 0.

Dependencies

~475KB