Abstract
Randomized search heuristics, among them evolutionary algorithms, are applied to problems whose structure is not well understood, as well as to hard problems in combinatorial optimization to get near-optimal solutions. We present a new approach implementing simple parallel evolutionary algorithms by relational methods. Populations are represented as relations which are implicitly encoded by (reduced, ordered) binary decision diagrams. Thereby, the creation and evaluation is done in parallel, which increases efficiency considerably.
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Kehden, B., Neumann, F., Berghammer, R. (2006). Relational Implementation of Simple Parallel Evolutionary Algorithms. In: MacCaull, W., Winter, M., Düntsch, I. (eds) Relational Methods in Computer Science. RelMiCS 2005. Lecture Notes in Computer Science, vol 3929. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11734673_13
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DOI: https://doi.org/10.1007/11734673_13
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-33339-5
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