Abstract
This paper engineers a new state-of-the-art Stochastic Local Search (SLS) for the Low Autocorrelation Binary Sequence (LABS) problem. The new SLS solver is obtained with white-box visualization to get insights on how an SLS can be effective for LABS; implementation improvements; and black-box parameter tuning.
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Halim, S., Yap, R.H.C., Halim, F. (2008). Engineering Stochastic Local Search for the Low Autocorrelation Binary Sequence Problem. In: Stuckey, P.J. (eds) Principles and Practice of Constraint Programming. CP 2008. Lecture Notes in Computer Science, vol 5202. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85958-1_57
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DOI: https://doi.org/10.1007/978-3-540-85958-1_57
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-85957-4
Online ISBN: 978-3-540-85958-1
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