[ValueError] Error in result in MOEA/D algorithm

[ubeydtalha]

Hello, I am getting an error like this, where am I doing wrong?

ref_dirs =  get_reference_directions(
    "multi-layer",
    get_reference_directions("das-dennis", 2, n_partitions=500, scaling=1.5),
    get_reference_directions("das-dennis", 2, n_partitions=500, scaling=0.5)
)
algorithm = MOEAD(
    ref_dirs,
    n_neighbors=7, 
    decomposition=get_decomposition("pbi", theta=5, eps=0),
    prob_neighbor_mating=0.7,
    sampling=get_sampling("real_random"), 
    crossover=get_crossover("real_sbx", prob=0.9, eta=15),
    mutation=get_mutation("real_pm", eta=20), 
    
)

res = minimize(problem,
               algorithm,
               ('n_gen', 100),
               seed=3878595,
               verbose=False,
               return_least_infeasible=False,)

Traceback (most recent call last): File "C:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.9_3.9.2288.0_x64__qbz5n2kfra8p0\lib\runpy.py", line 197, in _run_module_as_main return _run_code(code, main_globals, None, File "C:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.9_3.9.2288.0_x64__qbz5n2kfra8p0\lib\runpy.py", line 87, in _run_code exec(code, run_globals) File "c:\Users\Majin\.vscode\extensions\ms-python.python-2021.11.1422169775\pythonFiles\lib\python\debugpy\__main__.py", line 45, in <module> cli.main() File "c:\Users\Majin\.vscode\extensions\ms-python.python-2021.11.1422169775\pythonFiles\lib\python\debugpy/..\debugpy\server\cli.py", line 444, in main run() File "c:\Users\Majin\.vscode\extensions\ms-python.python-2021.11.1422169775\pythonFiles\lib\python\debugpy/..\debugpy\server\cli.py", line 285, in run_file runpy.run_path(target_as_str, run_name=compat.force_str("__main__")) File "C:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.9_3.9.2288.0_x64__qbz5n2kfra8p0\lib\runpy.py", line 268, in run_path return _run_module_code(code, init_globals, run_name, File "C:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.9_3.9.2288.0_x64__qbz5n2kfra8p0\lib\runpy.py", line 97, in _run_module_code _run_code(code, mod_globals, init_globals, File "C:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.9_3.9.2288.0_x64__qbz5n2kfra8p0\lib\runpy.py", line 87, in _run_code exec(code, run_globals) File "d:\Ubeyd\Bitirme_1\kod\genetik_algoritmalar\bitirme_I\pymoo\optimization\main.py", line 66, in <module> res = minimize(problem, File "d:\Ubeyd\Bitirme_1\kod\genetik_algoritmalar\bitirme_I\env\lib\site-packages\pymoo\optimize.py", line 83, in minimize res = algorithm.run() File "d:\Ubeyd\Bitirme_1\kod\genetik_algoritmalar\bitirme_I\env\lib\site-packages\pymoo\core\algorithm.py", line 213, in run self.next() File "d:\Ubeyd\Bitirme_1\kod\genetik_algoritmalar\bitirme_I\env\lib\site-packages\pymoo\core\algorithm.py", line 238, in next self.advance() File "d:\Ubeyd\Bitirme_1\kod\genetik_algoritmalar\bitirme_I\env\lib\site-packages\pymoo\core\algorithm.py", line 303, in advance self._advance(infills=infills, **kwargs) File "d:\Ubeyd\Bitirme_1\kod\genetik_algoritmalar\bitirme_I\env\lib\site-packages\pymoo\algorithms\moo\moead.py", line 124, in _advance self.ideal = np.min(np.vstack([self.ideal, off.F]), axis=0) File "<__array_function__ internals>", line 5, in vstack File "d:\Ubeyd\Bitirme_1\kod\genetik_algoritmalar\bitirme_I\env\lib\site-packages\numpy\core\shape_base.py", line 282, in vstack return _nx.concatenate(arrs, 0) File "<__array_function__ internals>", line 5, in concatenate ValueError: all the input array dimensions for the concatenation axis must match exactly, but along dimension 1, the array at index 0 has size 2 and the array at index 1 has size 1

[blankjul]

I am not able to reproduce the error. (what problem do you solve in your code? Does it have two objectives?)

from pymoo.algorithms.moo.moead import MOEAD
from pymoo.factory import get_reference_directions, get_decomposition
from pymoo.optimize import minimize
from pymoo.problems.multi import ZDT1

problem = ZDT1()

ref_dirs = get_reference_directions(
    "multi-layer",
    get_reference_directions("das-dennis", 2, n_partitions=500, scaling=1.5),
    get_reference_directions("das-dennis", 2, n_partitions=500, scaling=0.5)
)
algorithm = MOEAD(
    ref_dirs,
    n_neighbors=7,
    decomposition=get_decomposition("pbi", theta=5, eps=0),
    prob_neighbor_mating=0.7,
)

res = minimize(problem,
               algorithm,
               ('n_gen', 20),
               seed=3878595,
               verbose=True,
               return_least_infeasible=False)

[ubeydtalha]

I am trying to optimize the circuit. It is 2 objectives.

https://github.com/ubeydtalha/bitirme-projesi/tree/master/pymoo/optimization

[blankjul]

does NSGA2 work without any error? If no, I suspect issues with the problem definition or _evaluate function.

[ubeydtalha]

As you said, I encountered this error a few times, it may be related to _evaluate, I will examine it in more detail and come back. ^^