Heavy-Tailed Mutation with a Regularly Varying Constraint on the Distribution Function of Its Rate

Heavy-Tailed Mutation with a Regularly Varying Constraint on the Distribution Function of Its Rate Conference Abstracts

Conference

XXIII International Conference Mathematical Optimization Theory and Operations Research
30 Jun - 6 Jul 2024 , Омск

Source

MOTOR 2024: сборник тезисов XXIII Международной конференции «Теория математической оптимизации и исследование операций», (Омск, 30 июня – 06 июля 2024 г.)
Compilation, Издательство ОмГУ. Омск.2024. 109 c. ISBN 978-5-7779-2691-3.

Output data

Year: 2024, Pages: 32 Pages count : 1

Tags

Variational inequality, ExtraGradient, Composite problem, Sliding, Minty assumption.

Authors

Eremeev Anton Valentinovich ^1,3 , Topchii Valentin Alekseevich ^1,2

Affiliations

1	Омский филиал ФГБУН «Институт математики им. С.Л. Соболева СО РАН».
2	Novosibirsk State University
3	Dostoevsky Omsk State University

We study the heavy-tailed mutation operator proposed by Doerr, Le, Makhmara, and Nguyen (GECCO 2017). The power-law assumption of mutation rate is generalizeed using regularly varying constraint on the distribution function of mutation rate. It is shown that, on the OneMax function class, the expected runtime of evolutionary algorithms with this generalized version of mutation is linear in the problem dimension.

Eremeev A.V. , Topchii V.A.
Heavy-Tailed Mutation with a Regularly Varying Constraint on the Distribution Function of Its Rate
In compilation MOTOR 2024: сборник тезисов XXIII Международной конференции «Теория математической оптимизации и исследование операций», (Омск, 30 июня – 06 июля 2024 г.). – Издательство ОмГУ., 2024. – C.32. – ISBN 978-5-7779-2691-3.

Published print:	Jul 17, 2024
Published online:	Jul 17, 2024

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