Electronic Computing Equipment Schemes Elements Placement Based on Hybrid Intelligence Approach

Gladkov, Leonid A.; Gladkova, Nadezhda V.; Leiba, Sergey

doi:10.1007/978-3-319-18503-3_4

Cited by 8 publications

(1 citation statement)

References 4 publications

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“…Эволюционные алгоритмы применяются для решения множества практических задач, таких как составление расписаний в промышленности [15,16], оптимизация разводки печатных плат [17][18][19][20], построение систем управления [21][22][23][24][25][26][27], сегментирование изображений [28], а также приближенного решения других задач комбинаторной [29][30][31][32] и вещественной оптимизации [33][34][35].…”

Section: Introductionunclassified

The “One-Fifth Rule” with Rollbacks for Self-Adjustment of the Population Size in the (1 + (λ, λ)) Genetic Algorithm

Bassin

Buzdalov

Shalyto

2021

Aut. Control Comp. Sci.

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Self-adjustment of parameters can signi cantly improve the performance of evolutionary algorithms. A notable example is the (1 + ( , )) 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-h rule" on problems with weak tness-distance correlation. We propose a modi cation of the "one-h rule" in order to have less negative impact on the performance in the cases where the original rule is destructive. Our modi cation, while still yielding a provable linear runtime on OneMax, shows be er results on linear function with random weights, as well as on random satis able MAX-3SAT problems.

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