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

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 contin...

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Bibliographic Details
Published inLearning and Intelligent Optimization Vol. 7997; pp. 70 - 74
Main Authors Trautmann, Heike, Wagner, Tobias, Brockhoff, Dimo
Format Book Chapter
LanguageEnglish
Published Germany Springer Berlin / Heidelberg 2013
Springer Berlin Heidelberg
SeriesLecture Notes in Computer Science
Subjects
EMOA
Indicator-based selection
Multiobjective optimization
Performance assessment
Preferences
R2-indicator
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Summary: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.
ISBN:9783642449727
3642449727
ISSN:0302-9743
1611-3349
DOI:10.1007/978-3-642-44973-4_8