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...
Uloženo v:
Hlavní autor: | Fernández, Eduardo |
---|---|
Další autoři: | Sanchez Solis, Julia Patricia, Rivera Zarate, Gilberto |
Médium: | Artículo |
Jazyk: | en_US |
Vydáno: |
2019
|
Témata: | |
On-line přístup: | https://doi.org/10.3846/tede.2019.9475 https://journals.vgtu.lt/index.php/TEDE/article/view/9475 |
Tagy: |
Přidat tag
Žádné tagy, Buďte první, kdo otaguje tento záznam!
|
Podobné jednotky
-
Hybrid evolutionary multi-objective optimisation using outranking-based ordinal classification methods
Vydáno: (2020) -
Interdependent Projects Selection with Preference Incorporation
Autor: Gómez, Claudia
Vydáno: (2018) -
Preference Incorporation into Many-Objective Optimization: An Ant Colony Algorithm based on Interval Outranking
Autor: Rivera Zarate, Gilberto
Vydáno: (2021) -
Robustness analysis of an outranking model parameters’ elicitation method in the presence of noisy examples
Autor: Rangel Valdes, Nelson
Vydáno: (2018) -
Hybridisation of Swarm Intelligence Algorithms with Multi-Criteria Ordinal Classification: A Strategy to Address Many-Objective Optimisation
Autor: Rivera Zarate, Gilberto
Vydáno: (2022)