pyrepo_mcda.mcda_methods.vikor_smaa

Classes

VIKOR_SMAA

Module Contents

class pyrepo_mcda.mcda_methods.vikor_smaa.VIKOR_SMAA(normalization_method=None, v=0.5)

v

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.

weightsndarray
Matrix with i vectors in rows of n weights in columns. i means number of iterations of SMAA

typesndarray
Vector with criteria types. Profit criteria are represented by 1 and cost by -1.

Returns

ndrarray, ndarray, ndarray
Matrix with acceptability indexes values for each alternative in rows in relation to each rank in columns, Matrix with central weight vectors for each alternative in rows Matrix with final ranking of alternatives

Examples

>>> vikor_smaa = VIKOR_SMAA(normalization_method = minmax_normalization)
>>> rank_acceptability_index, central_weight_vector, rank_scores = vikor_smaa(matrix, weights, types)

_generate_weights(n, iterations)

Function to generate multiple weight vectors

Parameters

nint
Number of criteria

iterationsint
Number of weight vector to generate

Returns

ndarray
Matrix containing in rows vectors with weights for n criteria

static _vikor_smaa(self, matrix, weights, types, normalization_method, v)