pyrepo_mcda.mcda_methods.cradis

Classes

CRADIS

Module Contents

class pyrepo_mcda.mcda_methods.cradis.CRADIS(normalization_method=linear_normalization)

Bases: pyrepo_mcda.mcda_methods.mcda_method.MCDA_method

normalization_method

__call__(matrix, weights, types)

Score alternatives provided in decision matrix matrix using criteria weights and criteria types.

Parameters

matrixndarray
Decision matrix with m alternatives in rows and n criteria in columns.

weights: ndarray
Criteria weights. Sum of weights must be equal to 1.

types: ndarray
Criteria types. Profit criteria are represented by 1 and cost by -1.

Returns

ndrarray
Preference values of each alternative. The best alternative has the highest preference value.

Examples

>>> cradis = CRADIS()
>>> pref = cradis(matrix, weights, types)
>>> rank = rank_preferences(pref, reverse = True)

static _cradis(matrix, weights, types, normalization_method)