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

Heike Trautmann 1 Tobias Wagner 2 Dimo Brockhoff 3
1 Statistics Department
TU - Technische Universität Dortmund [Dortmund]
2 Institute of Machining Technology
TU - Technische Universität Dortmund [Dortmund]
3 DOLPHIN - Parallel Cooperative Multi-criteria Optimization
LIFL - Laboratoire d'Informatique Fondamentale de Lille, Inria Lille - Nord Europe
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.
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Communication dans un congrès
Learning and Intelligent OptimizatioN Conference (LION 7), Jan 2013, Catania, Italy. 7997, pp.70-74, 2013, Lecture Notes in Computer Science. 〈10.1007/978-3-642-44973-4_8〉
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Heike Trautmann, Tobias Wagner, Dimo Brockhoff. R2-EMOA: Focused Multiobjective Search Using R2-Indicator-Based Selection. Learning and Intelligent OptimizatioN Conference (LION 7), Jan 2013, Catania, Italy. 7997, pp.70-74, 2013, Lecture Notes in Computer Science. 〈10.1007/978-3-642-44973-4_8〉. 〈hal-00807901〉

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