Geodesic
The ``one-fifth rule'' with rollbacks for self-adjustment of the population size in the $(1 + (\lambda,\lambda))$ genetic algorithm
Modelirovanie i analiz informacionnyh sistem, Tome 27 (2020) no. 4, pp. 488-508

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Self-adjustment of parameters can significantly improve the performance of evolutionary algorithms. A notable example is the $(1 + (\lambda,\lambda))$ genetic algorithm, where adaptation of the population size helps to achieve the linear running time on the OneMax problem. However, on problems which interfere with the assumptions behind the self-adjustment procedure, its usage can lead to the performance degradation. In particular, this is the case with the “one-fifth rule” on problems with weak fitness-distance correlation. We propose a modification of the “one-fifth rule” in order to have less negative impact on the performance in the cases where the original rule is destructive. Our modification, while still yielding a provable linear runtime on OneMax, shows better results on linear function with random weights, as well as on random satisfiable MAX-3SAT problems.
Keywords: parameter adaptation, linear functions
Mots-clés : $(1 + (\lambda,\lambda))$ GA, MAX-3SAT. 
@article{MAIS_2020_27_4_a8,
     author = {A. O. Bassin and M. V. Buzdalov and A. A. Shalyto},
     title = {The ``one-fifth rule'' with rollbacks for self-adjustment of the population size in the $(1 + (\lambda,\lambda))$ genetic algorithm},
     journal = {Modelirovanie i analiz informacionnyh sistem},
     pages = {488--508},
     publisher = {mathdoc},
     volume = {27},
     number = {4},
     year = {2020},
     language = {ru},
     url = {http://geodesic.mathdoc.fr/item/MAIS_2020_27_4_a8/}
}
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A. O. Bassin; M. V. Buzdalov; A. A. Shalyto. The ``one-fifth rule'' with rollbacks for self-adjustment of the population size in the $(1 + (\lambda,\lambda))$ genetic algorithm. Modelirovanie i analiz informacionnyh sistem, Tome 27 (2020) no. 4, pp. 488-508. http://geodesic.mathdoc.fr/item/MAIS_2020_27_4_a8/