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GECCO
2007
Springer
212views Optimization» more  GECCO 2007»
14 years 14 days ago
An experimental analysis of evolution strategies and particle swarm optimisers using design of experiments
The success of evolutionary algorithms (EAs) depends crucially on ļ¬nding suitable parameter settings. Doing this by hand is a very time consuming job without the guarantee to ļ¬...
Oliver Kramer, Bartek Gloger, Andreas Goebels
GECCO
2009
Springer
103views Optimization» more  GECCO 2009»
13 years 11 months ago
Using performance fronts for parameter setting of stochastic metaheuristics
In this work, we explore the idea that parameter setting of stochastic metaheuristics should be considered as a multiobjective problem. The so-called ā€œperformance frontsā€ pres...
Johann Dréo
WSC
2000
13 years 7 months ago
Simulation optimization of stochastic systems with integer variables by sequential linearization
Discrete-event simulation is widely used to analyse and improve the performance of manufacturing systems. The related optimization problem often includes integer design variables ...
S. J. Abspoel, L. F. P. Etman, J. Vervoort, J. E. ...
GECCO
2010
Springer
165views Optimization» more  GECCO 2010»
13 years 8 months ago
Evolving robust controller parameters using covariance matrix adaptation
In this paper, the advantages of introducing an additional amount of tests when evolving parameters for speciļ¬c purposes is discussed. A set of optimal PID-controller parameters...
Gerulf K. M. Pedersen, Martin V. Butz
BMCBI
2006
239views more  BMCBI 2006»
13 years 6 months ago
Applying dynamic Bayesian networks to perturbed gene expression data
Background: A central goal of molecular biology is to understand the regulatory mechanisms of gene transcription and protein synthesis. Because of their solid basis in statistics,...
Norbert Dojer, Anna Gambin, Andrzej Mizera, Bartek...