[inria-00377093, v1] Application of a simple binary genetic algorithm  to a noiseless testbed benchmark
6 Pages

[inria-00377093, v1] Application of a simple binary genetic algorithm to a noiseless testbed benchmark


Downloading requires you to have access to the YouScribe library
Learn all about the services we offer


Author manuscript, published in "Genetic and Evolutionary Computation Conference (GECCO) (2009)"Application of a simple binary genetic algorithm to anoiseless testbed benchmarkMiguel NicolauINRIA Saclay - Île-de-FranceLRI - Université Paris SudParis, Francemiguel.nicolau@lri.frABSTRACT this problem, a new breed of genetic algorithms, the so-called Messy-GAs [5] have been developed. These GAs areOne of the earliest evolutionary computation algorithms,certainly better suited for higher order problems; however,the genetic algorithm, is applied to the noise-free BBOBthey are quite complex and hard to deploy. As a result,2009 testbed. It is adapted to the continuous domain bythe simplicity of developing and applying a simple GA to aincreasing the number of bits encoding each variable, un-variety of problems remains one of its biggest strengths.til a desired resolution is possible to achieve. Good resultsThecurrentpaperthereforeadaptstheoriginal, simplebi-and scaling are obtained for separable functions, but poornaryGAtoacontinuousdomainproblem,andreportsonitsperformance is achieved on the other functions, particularlyperformance. Although not achieving stellar performance,ill-conditioned functions. Overall running times remain fastparticularly incomparison with more recentandperformingthroughout.algorithms,theresultsobtainedareneverthelessremarkable,particularly in separable functions.Categories and Subject DescriptorsG.1.6 [Numerical Analysis]: ...



Published by
Reads 13
Language English
 ˘ˇ ˆ˙˝  ˛˚ˇ ˝ ˜ ˙ !˘ !"ˇ #