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PPSN
2004
Springer
14 years 26 days 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
ITICSE
1997
ACM
13 years 11 months ago
A genetic algorithms tutorial tool for numerical function optimisation
The field of Genetic Algorithms has grown into a huge area over the last few years. Genetic Algorithms are adaptive methods, which can be used to solve search and optimisation pro...
Edmund K. Burke, D. B. Varley
GECCO
2006
Springer
188views Optimization» more  GECCO 2006»
13 years 11 months ago
Dominance learning in diploid genetic algorithms for dynamic optimization problems
This paper proposes an adaptive dominance mechanism for diploidy genetic algorithms in dynamic environments. In this scheme, the genotype to phenotype mapping in each gene locus i...
Shengxiang Yang
AAAI
1998
13 years 8 months ago
Optimal 2D Model Matching Using a Messy Genetic Algorithm
A Messy Genetic Algorithm is customized toflnd'optimal many-to-many matches for 2D line segment models. The Messy GA is a variant upon the Standard Genetic Algorithm in which...
J. Ross Beveridge
ICGA
1997
133views Optimization» more  ICGA 1997»
13 years 8 months ago
Messy Genetic Algorithms for Subset Feature Selection
Subset Feature Selection problems can have severalattributes which may make Messy Genetic Algorithms an appropriateoptimization method. First, competitive solutions may often use ...
L. Darrell Whitley, J. Ross Beveridge, Cesar Guerr...