paulin/EasyGA
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

Cleaned up and distanced further for more genetic variety

Browse Source
This commit is contained in:
SimpleArt
2020-12-01 18:20:46 -05:00
parent 8579565bb6
commit 4a1b87a3b7
1 changed files with 8 additions and 12 deletions
Download Patch File Download Diff File Expand all files Collapse all files

20
src/EasyGA.py
View File

@ -125,25 +125,21 @@ class GA(Attributes):
# Change rates with:
multiplier = 1 + self.adapt_rate
# Minimum and maximum mutation rates
min_rate = 0.05
max_rate = 0.25
self.parent_ratio = min(self.percent_converged, self.parent_ratio * multiplier)
# Too few converged: cross more and mutate less
if tol(amount_converged//2) > tol(amount_converged//2)*4:
self.selection_probability = min(0.75 , self.selection_probability * multiplier)
self.chromosome_mutation_rate = max(min_rate, self.chromosome_mutation_rate / multiplier)
self.gene_mutation_rate = max(min_rate, self.gene_mutation_rate / multiplier)
self.selection_probability = min(0.75, self.selection_probability * multiplier)
self.chromosome_mutation_rate = max(0.05, self.chromosome_mutation_rate / multiplier)
self.gene_mutation_rate = max(0.05, self.gene_mutation_rate / multiplier)
# Too many converged: cross less and mutate more
else:
self.selection_probability = max(0.25 , self.selection_probability / multiplier)
self.chromosome_mutation_rate = min(max_rate, self.chromosome_mutation_rate * multiplier)
self.gene_mutation_rate = min(max_rate, self.gene_mutation_rate * multiplier)
self.selection_probability = max(0.25, self.selection_probability / multiplier)
self.chromosome_mutation_rate = min(0.25, self.chromosome_mutation_rate * multiplier)
self.gene_mutation_rate = min(0.25, self.gene_mutation_rate * multiplier)
# First non-zero tolerance after amount_converged/8
for i in range(amount_converged//8, len(self.population)):
@ -165,7 +161,7 @@ class GA(Attributes):
self,
self.population[n],
best_chromosome,
min(0.25, (tol(n) - tol(j)/4) / tol(n))
min(0.25, (4*tol(n) - tol(j)) / tol(n))
)
# If negative weights can't be used,
@ -175,7 +171,7 @@ class GA(Attributes):
self,
self.population[n],
self.population[j],
0.5
0.75
)
# Update fitnesses