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GECCO
2005
Springer

Genetic algorithms using low-discrepancy sequences

10 years 5 months ago
Genetic algorithms using low-discrepancy sequences
The random number generator is one of the important components of evolutionary algorithms (EAs). Therefore, when we try to solve function optimization problems using EAs, we must carefully choose a good pseudo-random number generator. In EAs, the pseudorandom number generator is often used for creating uniformly distributed individuals. As the low-discrepancy sequences allow us to create individuals more uniformly than the random number sequences, we apply the low-discrepancy sequence generator, instead of the pseudo-random number generator, to EAs in this study. The numerical experiments show that the low-discrepancy sequence generator improves the search performances of EAs. Categories and Subject Descriptors I.2.8 [Artificial Intelligence]: Problem Solving, Control Methods, and Search—Heuristic methods General Terms Algorithms Keywords Genetic algorithm, Random number generator, Pseudo-random number sequence, Low-discrepancy sequence
Shuhei Kimura, Koki Matsumura
Added 29 Jun 2010
Updated 29 Jun 2010
Type Conference
Year 2005
Where GECCO
Authors Shuhei Kimura, Koki Matsumura
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