poli.objective_repository.toy_continuous_problem.definitions

Defines several continuous toy problems.

This script defines all the artificial landscapes with signature [np.ndarray] -> np.ndarray. You might see that the signs have been flipped from [1] or [2]. This is because we’re dealing with maximizations instead of minimizations.

[1] Ali R. Al-Roomi (2015). Unconstrained Single-Objective Benchmark

Functions Repository [https://www.al-roomi.org/benchmarks/unconstrained]. Halifax, Nova Scotia, Canada: Dalhousie University, Electrical and Computer Engineering.

[2] Surjanovic, S. and Bingham, D. Virtual Library of Simulation Experiments:

Test Functions and Datasets. [https://www.sfu.ca/~ssurjano/optimization.html]

Functions

ackley_function_01(x)
alpine_01(x)
alpine_02(x)
bent_cigar(x)
branin_2d(x)	The 2D Branin function.
brown(x)
camelback_2d(x)	Taken directly from the LineBO repository [1].
chung_reynolds(x)
cosine_mixture(x)
cross_in_tray(xy)	Cross-in-tray has several local maxima in a quilt-like pattern.
deb_01(x)
deb_02(x)
deflected_corrugated_spring(x[, alpha, k])
easom(xy)	Easom is very flat, with a maxima at (pi, pi).
egg_holder(xy)	The egg holder is especially difficult.
hartmann_6d(x)	The 6 dimensional Hartmann function.
levy(x)	Compute the Levy function.
rosenbrock(x[, a, b])	Compute the Rosenbrock function.
shifted_sphere(x)	The usual squared norm, but shifted away from the origin by a bit.
styblinski_tang(x[, normalize])	This function is maximized at (-2.903534, ..., -2.903534), with a value of -39.16599 * d.