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SEAL
2010
Springer
13 years 4 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...
GECCO
2007
Springer
119views Optimization» more  GECCO 2007»
14 years 18 days ago
Optimising the flow of experiments to a robot scientist with multi-objective evolutionary algorithms
A Robot Scientist is a physically implemented system that applies artificial intelligence to autonomously discover new knowledge through cycles of scientific experimentation. Ad...
Emma Byrne
SAC
2002
ACM
13 years 6 months ago
An evolutionary algorithm for reducing integrated-circuit test application time
The cost for testing integrated circuits represents a growing percentage of the total cost for their production. The former strictly depends on the length of the test session, and...
Fulvio Corno, Matteo Sonza Reorda, Giovanni Squill...
HIS
2008
13 years 7 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...
EMO
2005
Springer
175views Optimization» more  EMO 2005»
13 years 12 months ago
A New Analysis of the LebMeasure Algorithm for Calculating Hypervolume
We present a new analysis of the LebMeasure algorithm for calculating hypervolume. We prove that although it is polynomial in the number of points, LebMeasure is exponential in the...
R. Lyndon While