On the genotype compression and expansion for evolutionary algorithms in the continuous domain (CROSBI ID 722195)
Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Planinić, Lucija ; Đurasević, Marko ; Mariot, Luca ; Jakobović, Domagoj ; Picek, Stjepan ; Coello Coello, Carlos
engleski
On the genotype compression and expansion for evolutionary algorithms in the continuous domain
This paper investigates the influence of genotype size on evolutionary algorithms' performance. We consider genotype compression (where genotype is smaller than phenotype) and expansion (genotype is larger than phenotype) and define different strategies to reconstruct the original variables of the phenotype from both the compressed and expanded genotypes. We test our approach with several evolutionary algorithms over three sets of optimization problems: COCO benchmark functions, modeling of Physical Unclonable Functions, and neural network weight optimization. Our results show that genotype expansion works significantly better than compression, and in many scenarios, outperforms the original genotype encoding. This could be attributed to the change in the genotype-phenotype mapping introduced with the expansion methods: this modification beneficially transforms the domain landscape and alleviates the search space traversal.
Continuous space search ; Bio-inspired approaches
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Podaci o prilogu
1208-1216.
2021.
objavljeno
10.1145/3449726.3463169
Podaci o matičnoj publikaciji
GECCO '21: Proceedings of the Genetic and Evolutionary Computation Conference Companion
Podaci o skupu
Genetic and Evolutionary Computation Conference
predavanje
10.07.2021-14.07.2021
Lille, Francuska