MOEA/D optimization

Question

Could you help me about an issue that I experience with Moed?

I try to use the code: https://pymoo.org/algorithms/moo/moead.html#nb-moead But, I encountered two errors related to the shape of the dataset.

First of all, the data has 12 lines. The code I use :

`df= pd.read_excel('aa.xlsx',header=0)

class ZDT1(Problem):

    def __init__(self, n_var=12, **kwargs):
        super().__init__(n_var=n_var, n_obj=2, n_ieq_constr=0, xl=0, xu=1, vtype=float, **kwargs)
    def _evaluate(self, x, out, *args, **kwargs):
        obj5_a =df['a']
        obj5_b =df['b']
        out["F"] = np.column_stack([obj5_a ,obj5_b])

problem = ZDT1()

# create the reference directions to be used for the optimization

ref_dirs = get_reference_directions("energy", 2, n_points=12)

# create the algorithm object

algorithm = MOEAD(ref_dirs=ref_dirs)

# execute the optimization

res = minimize(problem,
algorithm,
seed=1,
termination=('n_gen', 600))
res.F\*\*`

But, when I implement the code with the 'n_points=12 , the problem occurred:

--Exception: ('Problem Error: F can not be set, expected shape (12, 2) but provided (13, 2)', ValueError('cannot reshape array of size 26 into shape (12,2)'))

But, when I implement the code with the 'n_points=13 , the problem occurred:

--Exception: ('Problem Error: F can not be set, expected shape (1, 2) but provided (13, 2)', ValueError('cannot reshape array of size 26 into shape (1,2)'))

I don't find a way to solve this. My work with other algorithms like NSGA3,CTEA work well with this class definition. But not with MOEAD.

Please help me with this. Thank you.