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ICGA
1997
133views Optimization» more  ICGA 1997»
13 years 11 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...
CORR
2004
Springer
168views Education» more  CORR 2004»
13 years 9 months ago
Estimating Genome Reversal Distance by Genetic Algorithm
Sorting by reversals is an important problem in inferring the evolutionary relationship between two genomes. The problem of sorting unsigned permutation has been proven to be NP-ha...
Andy Auyeung, Ajith Abraham
ASPDAC
2004
ACM
118views Hardware» more  ASPDAC 2004»
14 years 3 months ago
Fast and efficient voltage scheduling by evolutionary slack distribution
- To minimize energy consumption by voltage scaling in design of heterogeneousreal-time embeddedsystems, it is necessary to perfom two distinct tasks: task scheduling (TS) and volt...
Bita Gorjiara, Pai H. Chou, Nader Bagherzadeh, Meh...
MICAI
2005
Springer
14 years 3 months ago
Hybrid Particle Swarm - Evolutionary Algorithm for Search and Optimization
Particle Swarm Optimization (PSO) technique has proved its ability to deal with very complicated optimization and search problems. Several variants of the original algorithm have b...
Crina Grosan, Ajith Abraham, Sangyong Han, Alexand...
GECCO
2009
Springer
131views Optimization» more  GECCO 2009»
14 years 2 months ago
Application of a simple binary genetic algorithm to a noiseless testbed benchmark
One of the earliest evolutionary computation algorithms, the genetic algorithm, is applied to the noise-free BBOB 2009 testbed. It is adapted to the continuous domain by increasin...
Miguel Nicolau