Abstract
Aggregating the preference of multiple experts is a very old problem which remains without an absolute solution. This assertion is supported by the Arrow's theorem: there is no aggregation method that simultaneously satisfies three fairness criteria (non-dictatorship, independence of irrelevant alternatives and Pareto efficiency). However, it is possible to find a solution having minimal distance to the consensus, although it involves a NP-hard problem even for only a few experts. This paper presents a model based on Ant Colony Optimization for facing this problem when input data are incomplete. It means that our model should build a complete ordering from partial rankings. Besides, we introduce a measure to determine the distance between items. It provides a more complete picture of the aggregated solution. In order to illustrate our contributions we use a real problem concerning Employer Branding issues in Belgium.
| Original language | English |
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| Title of host publication | Advances in Computational Intelligence |
| Editors | Ignacio Rojas, Gonzalo Joya, Andreu Catala |
| Place of Publication | Cham |
| Publisher | Springer International Publishing |
| Pages | 343-355 |
| Number of pages | 13 |
| ISBN (Print) | 978-3-319-19222-2 |
| Publication status | Published - 2015 |
| Externally published | Yes |
| Event | International Work-Conference on Artificial Neural Networks IWANN 2015 - Duration: 10 Jun 2015 → … |
Conference
| Conference | International Work-Conference on Artificial Neural Networks IWANN 2015 |
|---|---|
| Period | 10/06/15 → … |