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GECCO
2005
Springer
160views Optimization» more  GECCO 2005»
15 years 7 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»
15 years 5 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...
104
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PPSN
2004
Springer
15 years 7 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»
15 years 2 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»
15 years 1 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