Name
Title | ||
|---|---|---|
A Population-Based Algorithm for Learning a Majority Rule Sorting Model with Coalitional Veto. |
Abstract | ||
|---|---|---|
MR-Sort Majority Rule Sorting is a multiple criteria sorting method which assigns an alternative a to category $$C^h$$ when a is better than the lower limit of $$C^h$$ on a weighted majority of criteria, and this is not true with the upper limit of $$C^h$$. We enrich the descriptive ability of MR-Sort by the addition of coalitional vetoes which operate in a symmetric way as compared to the MR-Sort rule w.r.t. to category limits, using specific veto profiles and veto weights. We describe a heuristic algorithm to learn such an MR-Sort model enriched with coalitional veto from a set of assignment examples, and show how it performs on real datasets. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1007/978-3-319-54157-0_39 | EMO |
Field | DocType | Citations |
Multiple criteria,Heuristic (computer science),Population based algorithm,Sorting,Integer programming,Artificial intelligence,Majority rule,Veto,Mathematics | Conference | 0 |
PageRank | References | Authors |
0.34 | 16 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Olivier Sobrie | 1 | 27 | 3.58 |
| Vincent Mousseau | 2 | 808 | 50.52 |
| Marc Pirlot | 3 | 333 | 39.10 |