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使用 pymoo 优化函数时，如果我包含 if 语句，则会收到如下错误：

ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()

我无法理解此错误的原因，它似乎与 numpy 有关

简化代码如下：

import numpy as np from pymoo.model.problem import Problem

#function with 2 variables to be maximised but not over a critical figure

def joist_h_des(b, h):
    defCHK = 581818181/(b*h**3/12)/50

    #ensures return value is as close to 1 as possible but does not exceed
    if defCHK > 1:
        defCHK = 0
    else:
        defCHK = defCHK

    return defCHK


#multi objective optimisation using pymoo class MyProblem(Problem):

    def __init__(self):
        super().__init__(n_var=2,
                         n_obj=2,
                         n_constr=2,
                         xl=np.array([25,100]),
                         xu=np.array([100,300]))

    def _evaluate(self, X, out, *args, **kwargs):
        f1 = -joist_h_des(X[:, 0], X[:, 1])
        f2 = X[:, 0] * X[:, 1]

        g1 = ((X[:, 0] * X[:, 1])-200000)
        g2 = - (X[:, 0] * X[:, 1])-60000

        out["F"] = np.column_stack([f1, f2])
        out["G"] = np.column_stack([g1, g2])


problem = MyProblem()


#3. Initialization of an Algorithm

from pymoo.algorithms.nsga2 import NSGA2 from pymoo.factory import get_sampling, get_crossover, get_mutation

algorithm = NSGA2(
    pop_size=40,
    n_offsprings=10,
    sampling=get_sampling("real_random"),
    crossover=get_crossover("real_sbx", prob=0.9, eta=15),
    mutation=get_mutation("real_pm", eta=20),
    eliminate_duplicates=True )

#4. Definition of a Termination Criterion

from pymoo.factory import get_termination

termination = get_termination("n_gen", 40)


#5. Optimize from pymoo.optimize import minimize

res = minimize(problem,
               algorithm,
               termination,
               seed=1,
               save_history=True,
               verbose=True)

这会产生：

Traceback (most recent call last):
  File "C:/Users/richa/PycharmProjects/untitled3/basic.py", line 70, in <module>
    verbose=True)
  File "C:\Users\richa\anaconda3\lib\site-packages\pymoo\optimize.py", line 85, in minimize
    res = algorithm.solve()
  File "C:\Users\richa\anaconda3\lib\site-packages\pymoo\model\algorithm.py", line 226, in solve
    self._solve(self.problem)
  File "C:\Users\richa\anaconda3\lib\site-packages\pymoo\model\algorithm.py", line 321, in _solve
    self.next()
  File "C:\Users\richa\anaconda3\lib\site-packages\pymoo\model\algorithm.py", line 243, in next
    self.initialize()
  File "C:\Users\richa\anaconda3\lib\site-packages\pymoo\model\algorithm.py", line 215, in initialize
    self._initialize()
  File "C:\Users\richa\anaconda3\lib\site-packages\pymoo\algorithms\genetic_algorithm.py", line 81, in _initialize
    self.evaluator.eval(self.problem, pop, algorithm=self)
  File "C:\Users\richa\anaconda3\lib\site-packages\pymoo\model\evaluator.py", line 78, in eval
    self._eval(problem, pop[I], **kwargs)
  File "C:\Users\richa\anaconda3\lib\site-packages\pymoo\model\evaluator.py", line 97, in _eval
    **kwargs)
  File "C:\Users\richa\anaconda3\lib\site-packages\pymoo\model\problem.py", line 286, in evaluate
    out = self._evaluate_batch(X, calc_gradient, out, *args, **kwargs)
  File "C:\Users\richa\anaconda3\lib\site-packages\pymoo\model\problem.py", line 385, in _evaluate_batch
    self._evaluate(X, out, *args, **kwargs)
  File "C:/Users/richa/PycharmProjects/untitled3/basic.py", line 28, in _evaluate
    f1 = -joist_h_des(X[:, 0], X[:, 1])
  File "C:/Users/richa/PycharmProjects/untitled3/basic.py", line 9, in joist_h_des
    if defCHK > 1:
ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()

Process finished with exit code 1

任何建议将不胜感激

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