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GECCO
2008
Springer
120views Optimization» more  GECCO 2008»
15 years 3 months ago
A robust evolutionary framework for multi-objective optimization
Evolutionary multi-objective optimization (EMO) methodologies, suggested in the beginning of Nineties, focussed on the task of finding a set of well-converged and well-distribute...
Kalyanmoy Deb
GECCO
2006
Springer
161views Optimization» more  GECCO 2006»
15 years 5 months ago
An empirical investigation of how and why neutrality affects evolutionary search
The effects of neutrality on evolutionary search have been considered in a number of interesting studies, the results of which, however, have been contradictory. Some researchers ...
Edgar Galván López, Riccardo Poli
ICANNGA
2009
Springer
212views Algorithms» more  ICANNGA 2009»
15 years 8 months ago
Evolutionary Regression Modeling with Active Learning: An Application to Rainfall Runoff Modeling
Many complex, real world phenomena are difficult to study directly using controlled experiments. Instead, the use of computer simulations has become commonplace as a feasible alte...
Ivo Couckuyt, Dirk Gorissen, Hamed Rouhani, Eric L...
CEC
2010
IEEE
15 years 3 months ago
Learning-assisted evolutionary search for scalable function optimization: LEM(ID3)
Inspired originally by the Learnable Evolution Model(LEM) [5], we investigate LEM(ID3), a hybrid of evolutionary search with ID3 decision tree learning. LEM(ID3) involves interleav...
Guleng Sheri, David Corne
GECCO
2007
Springer
194views Optimization» more  GECCO 2007»
15 years 8 months ago
Hybrid coevolutionary algorithms vs. SVM algorithms
As a learning method support vector machine is regarded as one of the best classifiers with a strong mathematical foundation. On the other hand, evolutionary computational techniq...
Rui Li, Bir Bhanu, Krzysztof Krawiec