31 lines
908 B
Python
31 lines
908 B
Python
import matplotlib.pyplot as plt
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import numpy as np
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from gen import GARunConfig, genetic_algorithm
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def fitness_function(chromosome: np.ndarray) -> np.ndarray:
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return chromosome[0] ** 2 + 2 * chromosome[1] ** 2
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config = GARunConfig(
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x_min=np.array([-5.12, -5.12]),
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x_max=np.array([5.12, 5.12]),
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fitness_func=fitness_function,
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max_generations=200,
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pop_size=25,
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pc=0.5,
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pm=0.01,
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minimize=True,
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seed=17,
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fitness_avg_threshold=0.05,
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save_generations=[1, 2, 3, 5, 7, 10, 15],
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)
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result = genetic_algorithm(config)
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# Выводим результаты
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print(f"Лучшая особь: {result.best_generation.best}")
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print(f"Лучшее значение фитнеса: {result.best_generation.best_fitness:.6f}")
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print(f"Количество поколений: {result.generations_count}")
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print(f"Время выполнения: {result.time_ms:.2f} мс")
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