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HIS
2008
15 years 1 months ago
Evaluating Ranking Composition Methods for Multi-Objective Optimization of Knowledge Rules
Most symbolic classifiers aim at building sets of rules with good coverage and precision. While this is suitable for most applications, they tend to neglect other desirable proper...
Rafael Giusti, Gustavo E. A. P. A. Batista, Ronald...
SIU
2002
97views more  SIU 2002»
14 years 11 months ago
Problem Generators for Rectangular packing problems
Abstract. In order to verify and test the performance of new packing algorithms relative to existing algorithms, test problems are needed. The scope of published test instances for...
E. Hopper, B. C. H. Turton
EMO
2009
Springer
155views Optimization» more  EMO 2009»
15 years 6 months ago
An Improved Version of Volume Dominance for Multi-Objective Optimisation
Abstract. This paper proposes an improved version of volume dominance to assign fitness to solutions in Pareto-based multi-objective optimisation. The impact of this revised volum...
Khoi Le, Dario Landa Silva, Hui Li
SEAL
2010
Springer
14 years 9 months 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...
IJCNN
2006
IEEE
15 years 5 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