将参数传递给pymoo，以便评估函数可以看到它们

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

class MyProblem(Problem):
    def __init__(self):
        super().__init__(n_var=2, n_obj=1, n_constr=0, xl=np.array([-5,-5]), xu=np.array([5,5]))

    def _evaluate(self, x, out, *args, **kwargs):
        # 在这里计算目标值
        f1 = x[0]**2 + x[1]**2
        out["F"] = [f1]

problem = MyProblem()

# 定义优化算法和参数
algorithm = NSGA2(pop_size=100)

# 运行优化
res = minimize(problem,
               algorithm,
               termination=('n_gen', 100),
               seed=1,
               verbose=True)

# 输出结果
print("最优解：", res.X)
print("最优目标值：", res.F)