Algorithmic Detection of Rank Reversals, Transitivity Violations, and Decomposition Inconsistencies in Multi-Criteria Decision Analysis
- URL: http://arxiv.org/abs/2508.00129v1
- Date: Thu, 31 Jul 2025 19:31:41 GMT
- Title: Algorithmic Detection of Rank Reversals, Transitivity Violations, and Decomposition Inconsistencies in Multi-Criteria Decision Analysis
- Authors: Agustín Borda, Juan Bautista Cabral, Gonzalo Giarda, Diego Nicolás Gimenez Irusta, Paula Pacheco, Alvaro Roy Schachner,
- Abstract summary: We present three tests that detect the presence of Rank Reversals, along with their implementation in the Scikit-Criteria library.<n>We also address the complications that arise when implementing these tests for general scenarios and the design considerations we made to handle them.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: In Multi-Criteria Decision Analysis, Rank Reversals are a serious problem that can greatly affect the results of a Multi-Criteria Decision Method against a particular set of alternatives. It is therefore useful to have a mechanism that allows one to measure the performance of a method on a set of alternatives. This idea could be taken further to build a global ranking of the effectiveness of different methods to solve a problem. In this paper, we present three tests that detect the presence of Rank Reversals, along with their implementation in the Scikit-Criteria library. We also address the complications that arise when implementing these tests for general scenarios and the design considerations we made to handle them. We close with a discussion about how these additions could play a major role in the judgment of multi-criteria decision methods for problem solving.
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