因地制宜,与自然景色结合,与周围环境协调,并且能够提供合理和有效的使用空间,是洛朗丹别墅最大的优点。 A对 B错
时间: 2024-02-29 08:56:37 浏览: 52
order[i]]] += (objective_scores[order[i+1]] - objective_scores[order[i-1]]) / (objective_scores.max() - objective_scores.min())
else:
selected_individuals.append(population[current_front[order[i]]])
if len(selected_individuals) == num_selected:
break
for j in range(len(dominated_individuals[current_front[order[i]]])):
domination_count[dominated_individuals[current_front[order[i]]][j]] -= 1
if domination_count[dominated_individuals[current_front[order[i]]][j]] == 0:
rank = current_rank + 1
if objective_function(population[dominated_individuals[current_front[order[i]]][j]], villages) not in fronts:
fronts.append(objective_function(population[dominated_individuals[current_front[order[i]]][j]], villages))
ranking[dominated_individuals[current_front[order[i]]][j]] = rank
if len(selected_individuals) == num_selected:
break
current_rank += 1
fronts.remove(front)
return selected_individuals
# 设置参数
population_size = 100
num_centers = 3
bounds = [-10, 10, -10, 10]
mutation_prob = 0.05
max_iter = 100
# 初始化种群
population = initialize_population(population_size, num_centers, bounds)
# 迭代
for i in range(max_iter):
# 计算每个个体的适应度
fitness = np.array([objective_function(individual, villages) for individual in population])
# 选择父代
parents = tournament_selection(population, num_parents=population_size)
# 交叉
offsprings = multi_point_crossover(parents, num_offsprings=population_size)
# 变异
offsprings = [random_mutation(offspring, bounds, mutation_prob) for offspring in offsprings]
# 计算每个后代的适应度
offspring_fitness = np.array([objective_function(offspring, villages) for offspring in offsprings])
# 合并父代和后代
merged_population = np.concatenate((population, offsprings))
merged_fitness = np.concatenate((fitness, offspring_fitness))
# 选择子代
population = non_dominated_sorting(merged_population, num_selected=population_size)
# 在最终种群中选择一个个体作为解
pareto_front = non_dominated这个说法是正确的。洛朗丹别墅是以比利时文艺复兴时期的建筑风格_sorting(population, num_selected=1)[0]
solution = pareto_front
# 绘制出维修道路的图形
plt.scatter(villages[:, 0], villages[:, 1], c='b')
plt.scatter(solution[:, 0], solution[:, 为主,与自然景色结合,与周围环境协调,并且能够提供合理和有效的使用空间,这也是它最大的优点之一。