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Type: Conference paper
Title: Runtime analysis of evolutionary diversity optimization and the vertex cover problem
Author: Gao, W.
Pourhassan, M.
Neumann, F.
Citation: Proceedings of the Companion Publication of the 2015 Genetic and Evolutionary Computation Conference, 2015 / Silva, S., Esparcia-Alcázar, A. (ed./s), pp.1395-1396
Publisher: ACM
Issue Date: 2015
ISBN: 9781450334884
Conference Name: Companion Publication of the 2015 Annual Conference on Genetic and Evolutionary Computation (GECCO Companion '15) (11 Jul 2015 - 15 Jul 2015 : Madrid, Spain)
Editor: Silva, S.
Esparcia-Alcázar, A.
Statement of
Wanru Gao, Mojgan Pourhassan, Frank Neumann
Abstract: Using evolutionary algorithms to generate a diverse set of solutions where all of them meet a given quality criteria has gained increasing interest in recent years. In order to gain theoretical insights on the working principle of populationbased evolutionary algorithms for this kind of diversity optimization a first runtime analysis has been presented by Gao and Neumann [1] on the example problems OneMax and LeadingOnes. We continue this line of research and examine the diversity optimization process of population-based evolutionary algorithms on complete bipartite graphs for the classical vertex cover problem.
Keywords: Combinatorial optimization, diversity, theory
Description: Extended Abstract
Rights: © 2015 Copyright held by the owner/author(s). Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the owner/author(s).
DOI: 10.1145/2739482.2764668
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