distance_metrics_mcda.mcda_methods.topsis

Module Contents

Classes

TOPSIS

Helper class that provides a standard way to create an ABC using
class distance_metrics_mcda.mcda_methods.topsis.TOPSIS(normalization_method=minmax_normalization, distance_metric=euclidean)[source]

Bases: distance_metrics_mcda.mcda_methods.mcda_method.MCDA_method

Helper class that provides a standard way to create an ABC using inheritance.

__call__(self, matrix, weights, types)[source]

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

Parameters

  • matrix (ndarray) – 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

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

Return type

ndrarray

Examples

>>> topsis = TOPSIS(normalization_method = minmax_normalization, distance_metric = euclidean)
>>> pref = topsis(matrix, weights, types)
>>> rank = rank_preferences(pref, reverse = True)
static _topsis(matrix, weights, types, normalization_method, distance_metric)[source]