R2-EMOA: Focused Multiobjective Search Using R2-Indicator-Based Selection
Zusammenfassung
An indicator-based evolutionary multiobjective optimization algorithm (EMOA) is introduced which incorporates the contribution to the unary R2-indicator as the secondary selection criterion. First experiments indicate that the R2-EMOA accurately approximates the Pareto front of the considered continuous multiobjective optimization problems. Furthermore, decision makers’ preferences can be included by adjusting the weight vector distributions of the indicator which results in a focused search behavior.
Zitieren als
Trautmann, H., Wagne, T., & Brockhoff, D. (2013). R2-EMOA: Focused Multiobjective Search Using R2-Indicator-Based Selection. In Proceedings of the Learning and Intelligent Optimization Conference 7, Catania, Italy, 70–74.Details
Publikationstyp
Forschungsartikel in Sammelband (Konferenz)
Begutachtet
Ja
Publikationsstatus
Veröffentlicht
Jahr
2013
Konferenz
Learning and Intelligent Optimization Conference 7
Konferenzort
Catania, Italy
Herausgeber
Trautmann H, Wagner T, Brockhoff D
Erste Seite
70
Letzte Seite
74
Anzahl der Seiten
24
Band
7997
Reihe
Lecture Notes in Computer Science
Sprache
Englisch