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Added tolerance-based termination

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SimpleArt
2020-11-09 15:58:09 -05:00
parent 4902e7c931
commit 7a8f16c622
2 changed files with 24 additions and 3 deletions
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2
src/attributes.py
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@ -49,6 +49,7 @@ class Attributes:
current_fitness = 0, current_fitness = 0,
generation_goal = 15, generation_goal = 15,
fitness_goal = None, fitness_goal = None,
tolerance_goal = 1e-3,
chromosome_mutation_rate = 0.15, chromosome_mutation_rate = 0.15,
gene_mutation_rate = 0.03, gene_mutation_rate = 0.03,
initialization_impl = Initialization_Methods.random_initialization, initialization_impl = Initialization_Methods.random_initialization,
@ -93,6 +94,7 @@ class Attributes:
self.current_fitness = deepcopy(current_fitness) self.current_fitness = deepcopy(current_fitness)
self.generation_goal = deepcopy(generation_goal) self.generation_goal = deepcopy(generation_goal)
self.fitness_goal = deepcopy(fitness_goal) self.fitness_goal = deepcopy(fitness_goal)
self.tolerance_goal = deepcopy(tolerance_goal)
# Mutation variables # Mutation variables
self.chromosome_mutation_rate = deepcopy(chromosome_mutation_rate) self.chromosome_mutation_rate = deepcopy(chromosome_mutation_rate)

25
src/termination_point/termination_methods.py
View File

@ -12,12 +12,31 @@ class Termination_Methods:
if ga.fitness_goal is not None: if ga.fitness_goal is not None:
# If minimum fitness goal reached, stop ga. # If minimum fitness goal reached, stop ga.
if ga.target_fitness_type == 'min' and ga.get_chromosome_fitness(0) >= ga.convert_fitness(ga.fitness_goal): if ga.target_fitness_type == 'min' and ga.population.get_chromosome(0).get_fitness() <= ga.fitness_goal:
return False return False
# If maximum fitness goal reached, stop ga. # If maximum fitness goal reached, stop ga.
elif ga.target_fitness_type == 'max' and ga.get_chromosome_fitness(0) >= ga.convert_fitness(ga.fitness_goal): elif ga.target_fitness_type == 'max' and ga.population.get_chromosome(0).get_fitness() >= ga.fitness_goal:
return False return False
# If generation goal is set, check it. # If generation goal is set, check it.
return ga.generation_goal is None or ga.current_generation < ga.generation_goal if ga.generation_goal is not None and ga.current_generation >= ga.generation_goal:
return False
# If tolerance is set, check it.
if ga.tolerance_goal is not None:
best_fitness = ga.population.get_chromosome(0).get_fitness()
convergence_count = 0
tol = ga.tolerance_goal * (1 + abs(best_fitness))
# Find out how many chromosomes have converged
for chromosome in ga.population.get_chromosome_list():
if abs(best_fitness - chromosome.get_fitness()) < tol:
convergence_count += 1
# Terminate if 10% of the population has converged
if convergence_count > 0.1*ga.population.size():
return False
return True