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EMO
2006
Springer
107views Optimization» more  EMO 2006»
15 years 6 months ago
Designing Multi-objective Variation Operators Using a Predator-Prey Approach
In this paper, we propose a new conceptual method for the design, investigation, and evaluation of multi-objective variation operators for evolutionary multi-objective algorithms. ...
Christian Grimme, Joachim Lepping
141
Voted
WABI
2004
Springer
106views Bioinformatics» more  WABI 2004»
15 years 8 months ago
Suboptimal Local Alignments Across Multiple Scoring Schemes
Abstract. Sequence alignment algorithms have a long standing tradition in bioinformatics. In this paper, we formulate an extension to existing local alignment algorithms: local ali...
Morris Michael, Christoph Dieterich, Jens Stoye
131
Voted
GECCO
2007
Springer
156views Optimization» more  GECCO 2007»
15 years 8 months ago
Techniques for highly multiobjective optimisation: some nondominated points are better than others
The research area of evolutionary multiobjective optimization (EMO) is reaching better understandings of the properties and capabilities of EMO algorithms, and accumulating much e...
David W. Corne, Joshua D. Knowles
144
Voted
IJCNN
2006
IEEE
15 years 8 months ago
Generalization Improvement in Multi-Objective Learning
— Several heuristic methods have been suggested for improving the generalization capability in neural network learning, most of which are concerned with a single-objective (SO) l...
Lars Gräning, Yaochu Jin, Bernhard Sendhoff
151
Voted
SEAL
2010
Springer
15 years 14 days ago
Dominance-Based Pareto-Surrogate for Multi-Objective Optimization
Abstract. Mainstream surrogate approaches for multi-objective problems build one approximation for each objective. Mono-surrogate approaches instead aim at characterizing the Paret...
Ilya Loshchilov, Marc Schoenauer, Michèle S...