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GECCO
2008
Springer

Empirical investigations on parallel competent genetic algorithms

9 years 10 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 automatically learning problem structure as gene linkage. Parallel implementation of cGAs can reduce computational cost due to the linkage learning and give us problem solving environments for a wide spectrum of real-world problems. Although some parallel cGAs have been proposed [16,18,19], the effect of the parallelizations has not been investigated enough. This paper empirically discusses the applicability and property of parallel cGAs, including a new parallel cGA, parallel D5 -GA. Categories and Subject Descriptors I.2.8 [Artificial Intelligence]: Problem Solving, Control Methods, and Search General Terms Algorithms Keywords Linkage, Parallelization
Miwako Tsuji, Masaharu Munetomo, Kiyoshi Akama
Added 09 Nov 2010
Updated 09 Nov 2010
Type Conference
Year 2008
Where GECCO
Authors Miwako Tsuji, Masaharu Munetomo, Kiyoshi Akama
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