R2-EMOA: Focused Multiobjective Search Using R2-Indicator-Based Selection

Trautmann H, Wagne T, Brockhoff D


Abstract
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.



Publication type
Conference Paper

Peer reviewed
Yes

Publication status
Published

Year
2013

Conference
Learning and Intelligent Optimization Conference 7

Venue
Catania, Italy

Editor
Trautmann H, Wagner T, Brockhoff D

Start page
70

End page
74

Number of pages
24

Volume
7997

Title of series
Lecture Notes in Computer Science

Language
English