mathdatech/Python
1
0
Fork 0
mirror of https://github.com/TheAlgorithms/Python.git synced 2025-02-25 10:28:39 +00:00
Code Issues Packages Projects Releases Wiki Activity

[pre-commit.ci] auto fixes from pre-commit.com hooks

Browse Source 
for more information, see https://pre-commit.ci
This commit is contained in:
pre-commit-ci[bot] 2024-11-15 09:26:56 +00:00
parent 84b29c0eed
commit 9049228ff8
1 changed files with 15 additions and 10 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

9
genetic_algorithm/genetic_algorithm_optimization.py
View File

@ -251,7 +251,9 @@ class GeneticAlgorithm:
raise ValueError("Population score is empty. No individuals evaluated.") raise ValueError("Population score is empty. No individuals evaluated.")
# Check the best individual # Check the best individual
best_individual = max(population_score, key=lambda score_tuple: score_tuple[1])[0] best_individual = max(
population_score, key=lambda score_tuple: score_tuple[1]
)[0]
best_fitness = self.fitness(best_individual) best_fitness = self.fitness(best_individual)
# Select parents for next generation # Select parents for next generation
@ -260,7 +262,10 @@ class GeneticAlgorithm:
# Generate offspring using crossover and mutation # Generate offspring using crossover and mutation
for i in range(0, len(parents), 2): for i in range(0, len(parents), 2):
parent1, parent2 = parents[i], parents[(i + 1) % len(parents)] # Wrap around for odd cases parent1, parent2 = (
parents[i],
parents[(i + 1) % len(parents)],
) # Wrap around for odd cases
child1, child2 = self.crossover(parent1, parent2) child1, child2 = self.crossover(parent1, parent2)
next_generation.append(self.mutate(child1)) next_generation.append(self.mutate(child1))
next_generation.append(self.mutate(child2)) next_generation.append(self.mutate(child2))