Welcome to objective-weighting documentation!

objective-weighting is Python 3 library dedicated to multi-criteria decision analysis with criteria weights determined by objective weighting methods. This library includes:

  • The VIKOR method VIKOR

  • Objective weighting methods for determining criteria weights required by Multi-Criteria Decision Analysis (MCDA) methods:

    • equal_weighting (Equal weighting method)

    • entropy_weighting (Entropy weighting method)

    • std_weighting (Standard deviation weighting method)

    • critic_weighting (CRITIC weighting method)

    • gini_weighting (Gini coefficient-based weighting method)

    • merec_weighting (MEREC weighting method)

    • stat_var_weighting (Statistical variance weighting method)

    • cilos_weighting (CILOS weighting method)

    • idocriw_weighting (IDOCRIW weighting method)

    • angle_weighting (Angle weighting method)

    • coeff_var_weighting (Coefficient of variation weighting method)

  • Stochastic Multicriteria Acceptability Analysis Method - SMAA combined with VIKOR (VIKOR_SMAA)

  • Correlation coefficients:

    • spearman (Spearman rank correlation coefficient)

    • weighted_spearman (Weighted Spearman rank correlation coefficient)

    • pearson_coeff (Pearson correlation coefficient)

  • Methods for normalization of decision matrix:

    • linear_normalization (Linear normalization)

    • minmax_normalization (Minimum-Maximum normalization)

    • max_normalization (Maximum normalization)

    • sum_normalization (Sum normalization)

    • vector_normalization (Vector normalization)

  • additions:

    • rank_preferences (Method for ordering alternatives according to their preference values obtained with MCDA methods)

Check out the Usage section for further information, including how to Installation the project.

Note

This project is under active development.

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