def lvxm(P, i, b, lb, ub, par):
alpha, beta, pm, etam = par[0], par[1], par[2], par[3]
np.random.shuffle(b)
p1 = P[i]
p2 = P[b[0]]
y = p1 + alpha * levy(beta, len(p1)) * (p1 - p2)
y = repair(y, lb, ub)
y = poly_mutation(y, lb, ub, etam, pm)
y = repair(y, lb, ub)
return y
def dem(P, i, b, lb, ub, par):
f, pm, etam = par[0], par[1], par[2]
np.random.shuffle(b)
p1 = P[i]
p2, p3 = P[b[0]], P[b[1]]
y = p1 + f * (p2 - p3)
y = repair(y, lb, ub)
y = poly_mutation(y, lb, ub, etam, pm)
y = repair(y, lb, ub)
return y
def ga(P, i, b, lb, ub, par):
pc, pm, etac, etam = par[0], par[1], par[2], par[3]
np.random.shuffle(b)
p1, p2 = P[b[0]], P[b[1]]
if np.random.uniform(0, 1) < pc:
c1, c2 = sbx_crossover(p1, p2, lb, ub, etac)
else:
c1, c2 = p1, p2
if np.random.uniform(0, 1) < 0.5:
y = c1
else:
y = c2
y = repair(y, lb, ub)
y = poly_mutation(y, lb, ub, etam, pm)
y = repair(y, lb, ub)
return y
def lvx(P, i, b, lb, ub, par):
alpha, beta = par[0], par[1]
np.random.shuffle(b)
p1 = P[i]
p2 = P[b[0]]
y = p1 + alpha * levy(beta, len(p1)) * (p1 - p2)
y = repair(y, lb, ub)
return y
def de(P, i, b, lb, ub, par):
f = par[0]
np.random.shuffle(b)
p1 = P[i]
p2, p3 = P[b[0]], P[b[1]]
y = p1 + f * (p2 - p3)
y = repair(y, lb, ub)
return y
def de_normal(P, i, b, lb, ub, par):
f = par[0]
np.random.shuffle(b)
p1 = P[i]
p2, p3 = P[b[0]], P[b[1]]
y = np.zeros((len(p1), 1))
for j in range(len(p1)):
y[j] = p1[j] + f * np.random.normal(1) * (p2[j] - p3[j])
y = repair(y, lb, ub)
return y
def ga(P, rank, distances, lb, ub, par):
pc, pm, etac, etam, = par[0], par[1], par[2], par[3]
Q = []
while len(Q) < len(P):
p = []
for _ in range(2):
idx = np.arange(len(P))
np.random.shuffle(idx)
t = idx[:2]
res = bin_tournament(t, rank, distances)
p.append(res)
p1, p2 = P[p[0]], P[p[1]]
if np.random.uniform(0, 1) <= pc:
c1, c2 = sbx_crossover(p1, p2, lb, ub, etac)
else:
c1, c2 = p1, p2
c1, c2 = repair(c1, lb, ub), repair(c2, lb, ub)
c1 = poly_mutation(c1, lb, ub, etam, pm)
c2 = poly_mutation(c2, lb, ub, etam, pm)
c1, c2 = repair(c1, lb, ub), repair(c2, lb, ub)
Q.append(c1)
Q.append(c2)
return Q