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CEC
2007
IEEE
15 years 6 months ago
Efficient relevance estimation and value calibration of evolutionary algorithm parameters
Calibrating the parameters of an evolutionary algorithm (EA) is a laborious task. The highly stochastic nature of an EA typically leads to a high variance of the measurements. The ...
Volker Nannen, A. E. Eiben
GECCO
2006
Springer
134views Optimization» more  GECCO 2006»
15 years 5 months ago
Reference point based multi-objective optimization using evolutionary algorithms
: Evolutionary multi-objective optimization (EMO) methodologies have been amply applied to find a representative set of Pareto-optimal solutions in the past decade and beyond. Alth...
Kalyanmoy Deb, J. Sundar
IJCAI
2007
15 years 3 months ago
Relevance Estimation and Value Calibration of Evolutionary Algorithm Parameters
— Calibrating the parameters of an evolutionary algorithm (EA) is a laborious task. The highly stochastic nature of an EA typically leads to a high variance of the measurements. ...
Volker Nannen, A. E. Eiben
BMCBI
2010
164views more  BMCBI 2010»
15 years 2 months ago
Gene regulatory networks modelling using a dynamic evolutionary hybrid
Background: Inference of gene regulatory networks is a key goal in the quest for understanding fundamental cellular processes and revealing underlying relations among genes. With ...
Ioannis A. Maraziotis, Andrei Dragomir, Dimitris T...
AOSD
2009
ACM
15 years 8 months ago
Automated test data generation for aspect-oriented programs
Despite the upsurge of interest in the Aspect-Oriented Programming (AOP) paradigm, there remain few results on test data generation techniques for AOP. Furthermore, there is no wo...
Mark Harman, Fayezin Islam, Tao Xie, Stefan Wapple...