def get_fitness(pop):
#get score for each gene
for p in pop:
score = 0
for q in pop:
if GA._is_dominate(q, p):
score += 1
p.update_flag({'score': score})
#get raw fitness for each gene
for p in pop:
raw = 0
for q in pop:
if GA._is_dominate(q, p):
q_score = q.get_flag("score")
raw += q_score
p.update_flag({"raw": raw})
#get density and fitness for each gene
N = math.ceil(math.sqrt(GLOB.POP + GLOB.MAX_ARCHIVE_SPEA2))
for p in pop:
dens = 0
for q in pop: #get distance from others
dist = np.linalg.norm(p.get_eval() - q.get_eval())
q.update_flag({'dist': dist})
sorted_pop = sorted(pop, key=lambda gene: gene.get_flag('dist'))
dens = sorted_pop[N + 1].get_flag('dist')
fitness = dens + p.get_flag('raw')
p.update_flag({'dense': dens, 'fitness': fitness})
def collect_non_dominated(pop, CA, DA):
def distance(eval1, eval2):
return np.linalg.norm(eval1 - eval2)
new_CA = CA[:]
new_DA = DA[:]
#step1: update CA and DA
for i in range(len(pop)):
p = pop[i]
#check if non dominated
p.update_flag({"non-dominated": True, "dominate-other": False})
for archive in new_CA + new_DA:
if GA._is_dominate(archive, p):
p.update_flag({"non-dominated": False})
break
if not p.get_flag("non-dominated"): #skip if not non-dominated
continue
#check if it dominated other
for archive in new_CA:
if GA._is_dominate(p, archive):
new_CA.remove(archive)
p.update_flag({"dominate-other": True})
for archive in new_DA:
if GA._is_dominate(p, archive):
new_DA.remove(archive)
p.update_flag({"dominate-other": True})
if p.get_flag("dominate-other"): #dominate other, add at CA
new_CA.append(p)
else: #not dominate other, add at DA
new_DA.append(p)
#step2: limit the size of CA and DA
if len(new_CA + new_DA) > GLOB.MAX_ARCHIVE_TAEA:
if len(new_CA) > GLOB.MAX_ARCHIVE_TAEA:
new_DA = []
return
for pop_da in new_DA:
pop_da.update_flag({"len": GLOB.LARGE})
for pop_ca in new_CA:
dist = distance(pop_da.get_eval(), pop_ca.get_eval())
if dist < pop_da.get_flag("len"):
pop_da.update_flag({"len": dist})
#remove some population in DA
new_DA = sorted(new_DA, key=lambda pop: pop.get_flag("len"))
new_DA = new_DA[-GLOB.MAX_ARCHIVE_TAEA + len(new_CA):]
return new_CA, new_DA