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Self adaptive island GA

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dc.contributor.author Takashima, Eiichi en
dc.contributor.author Murata, Yoshihiro en
dc.contributor.author Shibata, Naoki en
dc.contributor.author Ito, Minoru en
dc.date.accessioned 2017-01-10T07:31:56Z en
dc.date.available 2017-01-10T07:31:56Z en
dc.date.issued 2003 en
dc.identifier.uri http://hdl.handle.net/10061/11374 en
dc.description CEC '03 : IEEE Congress on Evolutionary Computation , Dec 8-12, 2003 , Canberra, Australia en
dc.description.abstract Exploration efficiency of GAs largely depends on parameter values. But, it is hard to manually adjust these values. To cope with this problem, several adaptive GAs which automatically adjust parameters have been proposed. However, most of the existing adaptive GAs can adapt only a few parameters at the same time. Although several adaptive GAs can adapt multiple parameters simultaneously, these algorithms require extremely large computation costs. In this paper, we propose self adaptive island GA (SAIGA) which adapts four parameter values simultaneously while finding a solution to a problem. SAIGA is a kind of island GA, and it adapts parameter values using a similar mechanism to meta-GA. Throughout our evaluation experiments, we confirmed that our algorithm outperforms a simple GA using De Jong's rational parameters, and has performance close to a simple GA using manually tuned parameter values. en
dc.language.iso en en
dc.publisher IEEE en
dc.rights Copyright c 2003 IEEE Computer Society Washington, DC, USA en
dc.subject genetic algorithms en
dc.subject problem solving en
dc.subject search problems en
dc.subject combinatorial optimization en
dc.subject exploration efficiency en
dc.subject problem solving en
dc.subject rational parameters en
dc.subject self adaptive island GA en
dc.subject Approximation algorithms en
dc.subject Computational efficiency en
dc.subject Costs en
dc.subject Genetic mutations en
dc.subject Indium tin oxide en
dc.subject Information science en
dc.title Self adaptive island GA en
dc.type.nii Conference Paper en
dc.textversion Author en
dc.identifier.volume 2 en
dc.identifier.spage 1072 en
dc.identifier.epage 1079 en
dc.relation.doi 10.1109/CEC.2003.1299787 en
dc.identifier.NAIST-ID 73292302 en
dc.identifier.NAIST-ID 22740047 en

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