@inproceedings{c743b36a7ee54358af7038e9a9945bea,
title = "Theoretical and empirical study of the (1 + (?, ?)) Ea on the leadingones problem",
abstract = "In this work we provide a theoretical and empirical study of the (1 + (?, ?)) EA on the LeadingOnes problem. We prove an upper bound of O(n2) fitness evaluations on the expected runtime for all population sizes ? < n. This asymptotic bound does not depend on the parameter ?. We show via experiments that the value of ? has a small influence on the runtime (less than a factor of two). The value of ? that optimizes the runtime is small relative to n. We propose an extension of the existing (1 + (?, ?)) EA by using different population sizes in the mutation and in the crossover phase of the algorithm and show via experiments that this modification can outperform the original algorithm by a small constant factor.",
keywords = "Crossover, Runtime Analysis, Theory",
author = "Vitalii Karavaev and Denis Antipov and Benjamin Doerr",
note = "Publisher Copyright: {\textcopyright} 2019 Copyright held by the owner/author(s). Publication rights licensed to ACM.; 2019 Genetic and Evolutionary Computation Conference, GECCO 2019 ; Conference date: 13-07-2019 Through 17-07-2019",
year = "2019",
month = jul,
day = "13",
doi = "10.1145/3319619.3326910",
language = "English",
series = "GECCO 2019 Companion - Proceedings of the 2019 Genetic and Evolutionary Computation Conference Companion",
publisher = "Association for Computing Machinery, Inc",
pages = "2036--2039",
booktitle = "GECCO 2019 Companion - Proceedings of the 2019 Genetic and Evolutionary Computation Conference Companion",
}