pyrepo_mcda.mcda_methods.cocoso

Classes

COCOSO

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

Module Contents

class pyrepo_mcda.mcda_methods.cocoso.COCOSO(normalization_method=minmax_normalization, lambda_param=0.5)

Bases: pyrepo_mcda.mcda_methods.mcda_method.MCDA_method

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

normalization_method

lambda_param

__call__(matrix, weights, types)

Score alternatives provided in decision matrix matrix with m alternatives in rows and n criteria in columns using criteria weights and criteria types.

Parameters

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

weights: ndarray
Vector with criteria weights. Sum of weights must be equal to 1.

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

Returns

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

Examples

>>> cocoso = COCOSO(lambda_param = lambda_param)
>>> pref = cocoso(matrix, weights, types)
>>> rank = rank_preferences(pref, reverse = True)

static _cocoso(matrix, weights, types, normalization_method=minmax_normalization, lambda_param=0.5)