Inferring Parameters of a Relational System of Preferences from Assignment Examples using an Evolutionary Algorithm
Most evolutionary multi-objective algorithms perform poorly in many-objective problems. They normally do not make selective pressure towards the Region of Interest (RoI), the privileged zone in the Pareto frontier that contains solutions important to a DM. Several works have proved that a priori inc...
Gespeichert in:
1. Verfasser: | Fernández, Eduardo |
---|---|
Weitere Verfasser: | Sanchez Solis, Julia Patricia, Rivera Zarate, Gilberto |
Format: | Artículo |
Sprache: | en_US |
Veröffentlicht: |
2019
|
Schlagworte: | |
Online Zugang: | https://doi.org/10.3846/tede.2019.9475 https://journals.vgtu.lt/index.php/TEDE/article/view/9475 |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
Ähnliche Einträge
-
Hybrid evolutionary multi-objective optimisation using outranking-based ordinal classification methods
Veröffentlicht: (2020) -
Interdependent Projects Selection with Preference Incorporation
von: Gómez, Claudia
Veröffentlicht: (2018) -
Preference Incorporation into Many-Objective Optimization: An Ant Colony Algorithm based on Interval Outranking
von: Rivera Zarate, Gilberto
Veröffentlicht: (2021) -
Robustness analysis of an outranking model parameters’ elicitation method in the presence of noisy examples
von: Rangel Valdes, Nelson
Veröffentlicht: (2018) -
Hybridisation of Swarm Intelligence Algorithms with Multi-Criteria Ordinal Classification: A Strategy to Address Many-Objective Optimisation
von: Rivera Zarate, Gilberto
Veröffentlicht: (2022)