MaxOfTwoASF

class desdeo_tools.scalarization.MaxOfTwoASF(nadir, ideal, lt_inds, lte_inds, rho=1e-06, rho_sum=1e-06)[source]

Bases: desdeo_tools.scalarization.ASF.ASFBase

Implements the ASF as defined in eq. 3.1 Miettinen 2006

Parameters

  • nadir (np.ndarray) – The nadir point.

  • ideal (np.ndarray) – The ideal point.

  • lt_inds (List[int]) – Indices of the objectives categorized to be

  • decreased. –

  • lte_inds (List[int]) – Indices of the objectives categorized to be

  • until some value is reached. (reduced) –

  • rho (float) – A small number to form the utopian point.

  • rho_sum (float) – A small number to be used as a weight for the sum

  • term. –

nadir

The nadir point.

Type

np.ndarray

ideal

The ideal point.

Type

np.ndarray

lt_inds

Indices of the objectives categorized to be

Type

List[int]

decreased.
lte_inds

Indices of the objectives categorized to be

Type

List[int]

reduced until some value is reached.
rho

A small number to form the utopian point.

Type

float

rho_sum

A small number to be used as a weight for the sum

Type

float

term.

Methods Summary

__call__(objective_vector, reference_point)

Evaluate the ASF.

Methods Documentation

__call__(objective_vector, reference_point)[source]

Evaluate the ASF.

Parameters

  • objective_vectors (np.ndarray) – The objective vectors to calculate

  • values. (the) –

  • reference_point (np.ndarray) – The reference point to calculate the

  • values. –

Returns

Either a single ASF value or a vector of values if objective is a 2D array.

Return type

Union[float, np.ndarray]

Note

The reference point may not always necessarily be feasible, but it’s dimensions should match that of the objective vector.