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我正在尝试使用多目标优化包 pymoo 在三个基准问题（DTLZ1 和 DTLZ7）上运行和比较三种算法（NSGAII、NSGAIII 和 MOEAD）。

至于性能指标，我使用的是执行时间（目前看来还可以）和代际距离。后者，无论精度和迭代次数如何，总是得到相同的值。由于三种算法都是进化的，这似乎不合理，因为每次迭代都有一个随机输入。

有机会知道什么是错的吗？

from pymoo.factory import get_problem, get_reference_directions
from pymoo.util.plotting import plot
from pymoo.algorithms.moo.nsga2 import NSGA2
from pymoo.algorithms.moo.nsga3 import NSGA3
from pymoo.algorithms.moo.moead import MOEAD
from pymoo.optimize import minimize
from pymoo.visualization.scatter import Scatter
from pymoo.factory import get_performance_indicator

import json

pop_size = 100
n_gen = 200
n_iter = 200

problem = get_problem("dtlz1") # 3 objs, 7 vars, easy pareto

ref_dirs = get_reference_directions("das-dennis", 3, n_partitions=12)

alg1 = NSGA2(pop_size=pop_size)
alg2 = NSGA3(pop_size=pop_size,
             ref_dirs=ref_dirs)
alg3 = MOEAD(ref_dirs,
             n_neighbors=15,
             prob_neighbor_mating=0.7)

timing1 = []
timing2 = []
timing3 = []

gd1 = []
gd2 = []
gd3 = []

for i in range(n_iter):
    sol1 = minimize(problem,
                    alg1,
                    ('n_gen', n_gen),
                    seed=42,
                    verbose=False)

    sol2 = minimize(problem,
                    alg2,
                    ('n_gen', n_gen),
                    seed=42,
                    verbose=False)

    sol3 = minimize(problem,
                    alg3,
                    ('n_gen', n_gen),
                    seed=42,
                    verbose=False)

    timing1.append(sol1.exec_time)
    timing2.append(sol2.exec_time)
    timing3.append(sol3.exec_time)

    gd1_temp = get_performance_indicator("gd", problem.pareto_front())
    gd1.append(gd1_temp.do(sol1.F))

    gd2_temp = get_performance_indicator("gd", problem.pareto_front())
    gd2.append(gd2_temp.do(sol2.F))

    gd3_temp = get_performance_indicator("gd", problem.pareto_front())
    gd3.append(gd3_temp.do(sol3.F))

    print('Iteration ' + str(i) + ' executed.')

output = {'timings_nsga_ii': timing1,
          'gd_nsga_ii': gd1,
          'timings_nsga_iii': timing2,
          'gd_nsga_iii': gd2,
          'timings_moead': timing3,
          'gd_moead': gd3}

json_string = json.dumps(output)

with open('output_dtlz1.json','w') as outfile:
    outfile.write(json_string)

这是 outfile 的一个片段：

{"timings_nsga_ii": [2.1769814491271973, 2.161776065826416, 2.225513219833374], "gd_nsga_ii": [0.43135516556723147, 0.43135516556723147, 0.43135516556723147], "timings_nsga_iii": [2.324997663497925, 2.3156368732452393, 2.3685479164123535], "gd_nsga_iii": [0.021620591196013776, 0.021620591196013776, 0.021620591196013776], "timings_moead": [29.92823576927185, 23.453261375427246, 30.512006282806396], "gd_moead": [0.01792278080458056, 0.01792278080458056, 0.01792278080458056]}
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