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CEC
2005
IEEE
15 years 3 months ago
Linear genetic programming using a compressed genotype representation
This paper presents a modularization strategy for linear genetic programming (GP) based on a substring compression/substitution scheme. The purpose of this substitution scheme is t...
Johan Parent, Ann Nowé, Kris Steenhaut, Ann...
GECCO
2000
Springer
138views Optimization» more  GECCO 2000»
15 years 1 months ago
Time Complexity of genetic algorithms on exponentially scaled problems
This paper gives a theoretical and empirical analysis of the time complexity of genetic algorithms (GAs) on problems with exponentially scaled building blocks. It is important to ...
Fernando G. Lobo, David E. Goldberg, Martin Pelika...
BMCBI
2011
14 years 1 months ago
A hierarchical Bayesian network approach for linkage disequilibrium modeling and data-dimensionality reduction prior to genome-w
Background: Discovering the genetic basis of common genetic diseases in the human genome represents a public health issue. However, the dimensionality of the genetic data (up to 1...
Raphael Mourad, Christine Sinoquet, Philippe Leray
GECCO
2006
Springer
157views Optimization» more  GECCO 2006»
15 years 1 months ago
gLINC: identifying composability using group perturbation
We present two novel perturbation-based linkage learning algorithms that extend LINC [5]; a version of LINC optimised for decomposition tasks (oLINC) and a hierarchical version of...
David Jonathan Coffin, Christopher D. Clack
GECCO
2008
Springer
103views Optimization» more  GECCO 2008»
14 years 11 months ago
Empirical investigations on parallel competent genetic algorithms
This paper empirically investigates parallel competent genetic algorithms (cGAs) [4]. cGAs, such as BOA [21], LINCGA [15], D5 -GA [28], can solve GA-difficult problems by automati...
Miwako Tsuji, Masaharu Munetomo, Kiyoshi Akama