def f06_attractive_sector(x, xopt, fopt, Q, R, L, D):
z = Q @ L @ R @ (x - xopt)
s = np.full((D, ), 1)
s[z * xopt > 0] = 100
val = np.power(T_osz(np.sum(np.power(s * z, 2))), 0.9) + fopt
return FitObjPair(fitness=-val, objective=val - fopt)
def f01_sphere(x, xopt, fopt):
z = x - xopt
val = np.linalg.norm(z)**2 + fopt
return FitObjPair(fitness=-val, objective=val - fopt)
def f02_ellipsoidal(x, xopt, fopt, D, i):
z = T_osz(x - xopt)
val = np.sum(np.power(np.full(D, 10), i / (D - 1)) * z * z) + fopt
return FitObjPair(fitness=-val, objective=val - fopt)
def f08_rosenbrock(x, xopt, fopt, D):
z = np.max((1, np.sqrt(D) / 8)) * (x - xopt) + 1
val = np.sum(
np.power(np.power(z[:-1], 2) - z[1:], 2) +
np.power(z[:-1] - 1, 2)) + fopt
return FitObjPair(fitness=-val, objective=val - fopt)