遗传算法python代码
时间: 2023-03-21 21:00:54 浏览: 82
以下是遗传算法的示例代码:
```
import random
def generate_random_chromosome(length):
chromosome = [random.randint(0, 1) for _ in range(length)]
return chromosome
def fitness(chromosome):
count = sum(chromosome)
return count
def crossover(chromosome1, chromosome2):
index = random.randint(1, len(chromosome1) - 1)
chromosome1[index:], chromosome2[index:] = chromosome2[index:], chromosome1[index:]
return chromosome1, chromosome2
def mutate(chromosome):
index = random.randint(0, len(chromosome) - 1)
chromosome[index] = 1 - chromosome[index]
return chromosome
def select_chromosome(chromosomes, fitnesses):
fitnesses = [f / sum(fitnesses) for f in fitnesses]
fitnesses_cumulative = [fitnesses[0]]
for i in range(1, len(fitnesses)):
fitnesses_cumulative.append(fitnesses_cumulative[-1] + fitnesses[i])
random_value = random.random()
for i, fc in enumerate(fitnesses_cumulative):
if random_value <= fc:
return chromosomes[i]
def genetic_algorithm(population_size, chromosome_length, max_generations, fitness_function):
chromosomes = [generate_random_chromosome(chromosome_length) for _ in range(population_size)]
best_chromosome = None
best_fitness = 0
for generation in range(max_generations):
fitnesses = [fitness_function(chromosome) for chromosome in chromosomes]
if max(fitnesses) > best_fitness:
best_fitness = max(fitnesses)
best_chromosome = chromosomes[fitnesses.index(best_fitness)]
new_chromosomes = []
while len(new_chromosomes) < population_size:
chromosome1 = select_chromosome(chromosomes, fitnesses)
chromosome2 = select_chromosome(chromosomes, fitnesses)
chromosome1, chromosome2 = crossover(chromosome1, chromosome2)
chromosome1 = mutate(chromosome1)
chromosome2 = mutate(chromosome2)
new_chromosomes.append(chromosome1)
if len(new_chromosomes) < population_size:
new_chromosomes.append(chromosome2)
chromosomes = new_chromosomes
return best_chromosome, best_fitness
if __name__ == '__main__':
result, fitness = genetic_algorithm(100, 20, 100, fitness)
print(result, fitness)
```
这是一个简单的遗传算法的实现,它生成了一个随机的初始
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