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GECCO
2005
Springer
160views Optimization» more  GECCO 2005»
14 years 1 months ago
On the complexity of hierarchical problem solving
Competent Genetic Algorithms can efficiently address problems in which the linkage between variables is limited to a small order k. Problems with higher order dependencies can onl...
Edwin D. de Jong, Richard A. Watson, Dirk Thierens
GECCO
2006
Springer
190views Optimization» more  GECCO 2006»
13 years 11 months ago
Design synthesis of microelectromechanical systems using genetic algorithms with component-based genotype representation
An automated design synthesis system based on a multi-objective genetic algorithm (MOGA) has been developed for the optimization of surface-micromachined MEMS devices. A hierarchi...
Ying Zhang, Raffi R. Kamalian, Alice M. Agogino, C...
PPSN
2004
Springer
14 years 1 months ago
Hierarchical Genetic Algorithms
Current Genetic Algorithms can efficiently address order-k separable problems, in which the order of the linkage is restricted to a low value k. Outside this class, there exist hie...
Edwin D. de Jong, Dirk Thierens, Richard A. Watson
GECCO
2008
Springer
123views Optimization» more  GECCO 2008»
13 years 9 months ago
Hierarchical evolution of linear regressors
We propose an algorithm for function approximation that evolves a set of hierarchical piece-wise linear regressors. The algorithm, named HIRE-Lin, follows the iterative rule learn...
Francesc Teixidó-Navarro, Albert Orriols-Pu...
TNN
1998
76views more  TNN 1998»
13 years 7 months ago
Multiobjective genetic algorithm partitioning for hierarchical learning of high-dimensional pattern spaces: a learning-follows-d
— In this paper, we present a novel approach to partitioning pattern spaces using a multiobjective genetic algorithm for identifying (near-)optimal subspaces for hierarchical lea...
Rajeev Kumar, Peter Rockett