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Please use this identifier to cite or link to this item: https://dspace.lboro.ac.uk/2134/2381

Title: Parallelisation of genetic algorithms for the 2-page crossing number problem
Authors: He, H.
Sykora, Ondrej
Salagean, A.M.
Mäkinen, E.
Keywords: 2-page crossing number
parellel genetic algorithms
evaluation measures
Issue Date: 2007
Publisher: © Elsevier
Citation: HE et al, 2007. Parallelisation of genetic algorithms for the 2-page crossing number problem. Journal of parallel and distributed computing, 66(2), pp. 229-241
Abstract: Genetic algorithms have been applied to solve the 2-page crossing number problem successfully, but since they work with one global population, the search time and space are limited. Parallelisation provides an attractive prospect to improve the efficiency and solution quality of genetic algorithms. This paper investigates the complexity of parallel genetic algorithms (PGAs) based on two evaluation measures: Computation-time to Communication-time and Population-size to Chromosomesize. Moreover, the paper unifies the framework of PGA models with the function PGA (subpopulation size; cluster size, migration period; topology), and explores the performance of PGAs for the 2-page crossing number problem.
Description: This article is to be published in the journal, Journal of parallel and distributed computing [© Elsevier] and will also be available at: http://www.sciencedirect.com/science/journal/07437315
URI: https://dspace.lboro.ac.uk/2134/2381
ISSN: 0743-7315
Appears in Collections:Published Articles (Computer Science)

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