desdeo_emo.surrogatemodels.Problem

Module Contents

Classes

surrogateProblem

The base class from which every other class representing a problem should

class desdeo_emo.surrogatemodels.Problem.surrogateProblem(performance_evaluator)

Bases: desdeo_problem.problem.ProblemBase

The base class from which every other class representing a problem should derive.

evaluate(self, model_parameters, use_surrogates=False)

Evaluates the problem using an ensemble of input vectors. Uses surrogate models if available. Otherwise, it uses the true evaluator.

Parameters

• decision_vectors (np.ndarray) – An array of decision variable

• vectors. (input) –

• use_surrogate (bool) – A bool to control whether to use the true, potentially

• function or a surrogate model to evaluate the objectives. (expensive) –

Returns

Dict with the following keys:

’objectives’ (np.ndarray): The objective function values for each input

vector.

’constraints’ (Union[np.ndarray, None]): The constraint values of the

problem corresponding each input vector.

’fitness’ (np.ndarray): Equal to objective values if objective is to be

minimized. Multiplied by (-1) if objective to be maximized.

’uncertainity’ (Union[np.ndarray, None]): The uncertainity in the

objective values.

Return type

(Dict)

evaluate_constraint_values(self)

Evaluate just the constraint function values using the attributes decision_vectors and objective_vectors

Note

Currently not supported by ScalarMOProblem

get_variable_bounds(self)

get_objective_names(self)