def genetic_algorithm(population_size, generations):

population = initialize_population(population_size)

for generation in range(generations):

fitness_scores = evaluate_fitness(population)

parents = select_parents(population, fitness_scores)

offspring = crossover(parents)

population = mutate(offspring)

best_solution = max(population, key=evaluate_fitness)

return best_solution

def initialize_population(size):

# 初始化种群

pass

def evaluate_fitness(individual):

# 计算适应度

pass

def select_parents(population, scores):

# 选择父代

pass

def crossover(parents):

# 交叉操作

pass

def mutate(offspring):

# 变异操作

pass

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