def comp_by_cv_and_fitness(pop, P, **kwargs):
S = np.full(P.shape[0], np.nan)
for i in range(P.shape[0]):
a, b = P[i, 0], P[i, 1]
# if at least one solution is infeasible
if pop[a].CV > 0.0 or pop[b].CV > 0.0:
S[i] = compare(a,
pop[a].CV,
b,
pop[b].CV,
method='smaller_is_better',
return_random_if_equal=True)
# both solutions are feasible just set random
else:
S[i] = compare(a,
pop[a].F,
b,
pop[b].F,
method='smaller_is_better',
return_random_if_equal=True)
return S[:, None].astype(np.int)
def comp_by_cv_and_clearing_fitness(pop, P, **kwargs):
S = np.full(P.shape[0], np.nan)
for i in range(P.shape[0]):
a, b = P[i, 0], P[i, 1]
# if at least one solution is infeasible
if pop[a].CV > 0.0 or pop[b].CV > 0.0:
S[i] = compare(a,
pop[a].CV,
b,
pop[b].CV,
method='smaller_is_better',
return_random_if_equal=True)
# first compare by the round the individual was selected
else:
S[i] = compare(a,
pop[a].get("iter"),
b,
pop[b].get("iter"),
method='smaller_is_better')
# if it was the same round - then use the rank of the fitness directly
if np.isnan(S[i]):
S[i] = compare(a,
pop[a].get("rank"),
b,
pop[b].get("rank"),
method='smaller_is_better',
return_random_if_equal=True)
return S[:, None].astype(int)
def binary_tournament(pop, P, algorithm):
if P.shape[1] != 2:
raise ValueError("Only implemented for binary tournament!")
tournament_type = algorithm.tournament_type
S = np.full(P.shape[0], np.nan)
for i in range(P.shape[0]):
a, b = P[i, 0], P[i, 1]
if tournament_type == 'comp_by_dom_and_crowding':
rel = Dominator.get_relation(pop[a].F, pop[b].F)
if rel == 1:
S[i] = a
elif rel == -1:
S[i] = b
elif tournament_type == 'comp_by_rank_and_crowding':
S[i] = compare(a,
pop[a].rank,
b,
pop[b].rank,
method='smaller_is_better')
else:
raise Exception("Unknown tournament type.")
if np.isnan(S[i]):
S[i] = compare(a,
pop[a].get("crowding"),
b,
pop[b].get("crowding"),
method='larger_is_better',
return_random_if_equal=True)
return S[:, None].astype(np.int)
def comp_by_rank_and_ref_line_dist(pop, P, **kwargs):
S = np.full(P.shape[0], np.nan)
for i in range(P.shape[0]):
a, b = P[i, 0], P[i, 1]
# if at least one solution is infeasible
if pop[a].CV > 0.0 or pop[b].CV > 0.0:
S[i] = compare(a, pop[a].CV, b, pop[b].CV, method='smaller_is_better', return_random_if_equal=True)
# both solutions are feasible
else:
# if in the same niche select by rank
if pop[a].get("niche") == pop[b].get("niche"):
if pop[a].get("rank") != pop[b].get("rank"):
S[i] = compare(a, pop[a].get("rank"), b, pop[b].get("rank"), method='smaller_is_better')
else:
S[i] = compare(a, pop[a].get("dist_to_niche"), b, pop[b].get("dist_to_niche"),
method='smaller_is_better')
if np.isnan(S[i]):
S[i] = np.random.choice([a, b])
return S[:, None].astype(np.int)
def binary_tournament(pop, P, algorithm, **kwargs):
if P.shape[1] != 2:
raise ValueError("Only implemented for binary tournament!")
tournament_type = algorithm.tournament_type
S = np.full(P.shape[0], np.nan)
for i in range(P.shape[0]):
a, b = P[i, 0], P[i, 1]
# if at least one solution is infeasible
if pop[a].CV > 0.0 or pop[b].CV > 0.0:
S[i] = compare(
a,
pop[a].CV,
b,
pop[b].CV,
method="smaller_is_better",
return_random_if_equal=True,
)
# both solutions are feasible
else:
if tournament_type == "comp_by_dom_and_crowding":
rel = Dominator.get_relation(pop[a].F, pop[b].F)
if rel == 1:
S[i] = a
elif rel == -1:
S[i] = b
elif tournament_type == "comp_by_rank_and_crowding":
S[i] = compare(
a, pop[a].rank, b, pop[b].rank, method="smaller_is_better"
)
else:
raise Exception("Unknown tournament type.")
# if rank or domination relation didn't make a decision compare by crowding
if np.isnan(S[i]):
S[i] = compare(
a,
pop[a].get("crowding"),
b,
pop[b].get("crowding"),
method="larger_is_better",
return_random_if_equal=True,
)
return S[:, None].astype(np.int)
def comp_by_rank(pop, P, **kwargs):
S = np.full(P.shape[0], np.nan)
for i in range(P.shape[0]):
a, b = P[i, 0], P[i, 1]
S[i] = compare(a, pop[a].get("rank"), b, pop[b].get("rank"), method='smaller_is_better',
return_random_if_equal=True)
return S[:, None].astype(np.int)
def binary_tournament(pop, P, algorithm, **kwargs):
if P.shape[1] != 2:
raise ValueError("Only implemented for binary tournament!")
S = np.full(P.shape[0], np.nan)
for i in range(P.shape[0]):
a, b = P[i, 0], P[i, 1]
# if at least one solution is infeasible
if pop[a].CV > 0.0 or pop[b].CV > 0.0:
S[i] = compare(a,
pop[a].CV,
b,
pop[b].CV,
method='smaller_is_better',
return_random_if_equal=True)
# both solutions are feasible
else:
S[i] = compare(a,
pop[a].get("rank"),
b,
pop[b].get("rank"),
method='smaller_is_better',
return_random_if_equal=True)
# if rank or domination relation didn't make a decision compare by crowding
if np.isnan(S[i]):
S[i] = compare(a,
pop[a].get("apd"),
b,
pop[b].get("apd"),
method='smaller_is_better',
return_random_if_equal=True)
return S[:, None].astype(np.int, copy=False)
