Algorithmic Detection of Rank Reversals, Transitivity Violations, and Decomposition Inconsistencies in Multi-Criteria Decision Analysis
Fuente:
arXiv
Salvato in:
| Autori principali: | , , , , , |
|---|---|
| Natura: | Preprint |
| Pubblicazione: |
2025
|
| Soggetti: | |
| Accesso online: | |
| Tags: |
Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne!!
|
| _version_ | 1866908474947928064 |
|---|---|
| author | Borda, Agustín Cabral, Juan Bautista Giarda, Gonzalo Irusta, Diego Nicolás Gimenez Pacheco, Paula Schachner, Alvaro Roy |
| author_facet | Borda, Agustín Cabral, Juan Bautista Giarda, Gonzalo Irusta, Diego Nicolás Gimenez Pacheco, Paula Schachner, Alvaro Roy |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2508_00129 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Algorithmic Detection of Rank Reversals, Transitivity Violations, and Decomposition Inconsistencies in Multi-Criteria Decision Analysis Borda, Agustín Cabral, Juan Bautista Giarda, Gonzalo Irusta, Diego Nicolás Gimenez Pacheco, Paula Schachner, Alvaro Roy Artificial Intelligence Optimization and Control 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. |
| title | Algorithmic Detection of Rank Reversals, Transitivity Violations, and Decomposition Inconsistencies in Multi-Criteria Decision Analysis |
| topic | Artificial Intelligence Optimization and Control |
| url | https://arxiv.org/abs/2508.00129 |