def f20(x, rotation=None, shift=None, shuffle=None):
"""
Hybrid Function 10 (N=6)
Args:
x (array): Input vector of dimension 2, 10, 20, 30, 50 or 100.
rotation (matrix): Optional rotation matrix. If None (default), the
official matrix from the benchmark suite will be used.
shift (array): Optional shift vector. If None (default), the official
vector from the benchmark suite will be used.
shuffle (array): Optionbal shuffle vector. If None (default), the
official permutation vector from the benchmark suite will be used.
"""
nx = len(x)
if rotation is None:
rotation = transforms.rotations[nx][19]
if shift is None:
shift = transforms.shifts[19][:nx]
if shuffle is None:
shuffle = transforms.shuffles[nx][9]
x_transformed = np.matmul(rotation, x - shift)
x_parts = _shuffle_and_partition(x_transformed, shuffle,
[0.1, 0.1, 0.2, 0.2, 0.2, 0.2])
y = basic.happy_cat(x_parts[0])
y += basic.katsuura(x_parts[1])
y += basic.ackley(x_parts[2])
y += basic.rastrigin(x_parts[3])
y += basic.modified_schwefel(x_parts[4])
y += basic.schaffers_f7(x_parts[5])
return y + 2000.0
def f18(x, rotation=None, shift=None, shuffle=None):
"""
Hybrid Function 8 (N=5)
Args:
x (array): Input vector of dimension 2, 10, 20, 30, 50 or 100.
rotation (matrix): Optional rotation matrix. If None (default), the
official matrix from the benchmark suite will be used.
shift (array): Optional shift vector. If None (default), the official
vector from the benchmark suite will be used.
shuffle (array): Optionbal shuffle vector. If None (default), the
official permutation vector from the benchmark suite will be used.
"""
nx = len(x)
if rotation is None:
rotation = transforms.rotations[nx][17]
if shift is None:
shift = transforms.shifts[17][:nx]
if shuffle is None:
shuffle = transforms.shuffles[nx][7]
x_transformed = np.matmul(rotation, x - shift)
x_parts = _shuffle_and_partition(x_transformed, shuffle,
[0.2, 0.2, 0.2, 0.2, 0.2])
y = basic.high_conditioned_elliptic(x_parts[0])
y += basic.ackley(x_parts[1])
y += basic.rastrigin(x_parts[2])
y += basic.h_g_bat(x_parts[3])
y += basic.discus(x_parts[4])
return y + 1800.0
def f19(x, rotation=None, shift=None, shuffle=None):
"""
Hybrid Function 9 (N=5)
Args:
x (array): Input vector of dimension 2, 10, 20, 30, 50 or 100.
rotation (matrix): Optional rotation matrix. If None (default), the
official matrix from the benchmark suite will be used.
shift (array): Optional shift vector. If None (default), the official
vector from the benchmark suite will be used.
shuffle (array): Optionbal shuffle vector. If None (default), the
official permutation vector from the benchmark suite will be used.
"""
nx = len(x)
if rotation is None:
rotation = transforms.rotations[nx][18]
if shift is None:
shift = transforms.shifts[18][:nx]
if shuffle is None:
shuffle = transforms.shuffles[nx][8]
x_transformed = np.matmul(rotation, x - shift)
x_parts = _shuffle_and_partition(x_transformed, shuffle,
[0.2, 0.2, 0.2, 0.2, 0.2])
y = basic.bent_cigar(x_parts[0])
y += basic.rastrigin(x_parts[1])
y += basic.expanded_griewanks_plus_rosenbrock(x_parts[2])
y += basic.weierstrass(x_parts[3])
y += basic.expanded_schaffers_f6(x_parts[4])
return y + 1900.0
def f15(x, rotation=None, shift=None, shuffle=None):
"""
Hybrid Function 5 (N=4)
Args:
x (array): Input vector of dimension 2, 10, 20, 30, 50 or 100.
rotation (matrix): Optional rotation matrix. If None (default), the
official matrix from the benchmark suite will be used.
shift (array): Optional shift vector. If None (default), the official
vector from the benchmark suite will be used.
shuffle (array): Optionbal shuffle vector. If None (default), the
official permutation vector from the benchmark suite will be used.
"""
nx = len(x)
if rotation is None:
rotation = transforms.rotations[nx][14]
if shift is None:
shift = transforms.shifts[14][:nx]
if shuffle is None:
shuffle = transforms.shuffles[nx][4]
x_transformed = np.matmul(rotation, x - shift)
x_parts = _shuffle_and_partition(x_transformed, shuffle,
[0.2, 0.2, 0.3, 0.3])
y = basic.bent_cigar(x_parts[0])
y += basic.h_g_bat(x_parts[1])
y += basic.rastrigin(x_parts[2])
y += basic.rosenbrock(x_parts[3])
return y + 1500.0
def f5(x, rotation=None, shift=None):
"""
Shifted and Rotated Rastrigin's Function
Args:
x (array): Input vector of dimension 2, 10, 20, 30, 50 or 100.
rotation (matrix): Optional rotation matrix. If None (default), the
official matrix from the benchmark suite will be used.
shift (array): Optional shift vector. If None (default), the official
vector from the benchmark suite will be used.
"""
nx = len(x)
if rotation is None:
rotation = transforms.rotations[nx][4]
if shift is None:
shift = transforms.shifts[4][:nx]
x_transformed = np.matmul(rotation, (x - shift))
return basic.rastrigin(x_transformed) + 500.0
