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
Research article in proceedings (conference)
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