identifiesthe duplicate rows for decision variables
Selects the solutions that need to be reevaluated with the original functions.
- desdeo_emo.utilities.model_management.remove_duplicate(X: numpy.ndarray, archive_x: numpy.ndarray)
identifiesthe duplicate rows for decision variables Args: X (np.ndarray): the current decision variables. archive_x (np.ndarray): The decision variables in the archive.
Returns: indicies (np.ndarray): the indicies of solutions that are NOT already in the archive.
- desdeo_emo.utilities.model_management.ikrvea_mm(reference_point: numpy.ndarray, individuals: numpy.ndarray, objectives: numpy.ndarray, uncertainity: numpy.ndarray, problem: desdeo_problem.MOProblem, u: int) float
Selects the solutions that need to be reevaluated with the original functions. This model management is based on the following papaer:
- ‘P. Aghaei Pour, T. Rodemann, J. Hakanen, and K. Miettinen, “Surrogate assisted interactive
multiobjective optimization in energy system design of buildings,” Optimization and Engineering, 2021.’
reference_front (np.ndarray) – The reference front that the current front is being compared to.
array. (Should be an one-dimensional) –
individuals (np.ndarray) – Current individuals generated by using surrogate models
objectives (np.ndarray) – Current objectives generated by using surrogate models
uncertainity (np.ndarray) – Current Uncertainty values generated by using surrogate models
problem – the problem class
the new problem object that has an updated archive.
- Return type: