Abstract
The increasing availability of clusters of machines has allowed the fast development of pGAs [6]. Most popular parallel GAs split the whole population into separate subpopulations that are dealt with independently (islands). A sparse exchange of information among the component subalgorithms leads to a whole new class of algorithms that do not only perform faster (more steps by unit time), but that often lead to superior numerical performance [30, 106, 107].
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© 2011 Springer-Verlag Berlin Heidelberg
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Luque, G., Alba, E. (2011). Theoretical Models of Selection Pressure for Distributed GAs. In: Parallel Genetic Algorithms. Studies in Computational Intelligence, vol 367. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22084-5_4
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DOI: https://doi.org/10.1007/978-3-642-22084-5_4
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-22083-8
Online ISBN: 978-3-642-22084-5
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