Engineering Stochastic Local Search for the Low Autocorrelation Binary Sequence Problem

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.

• Type: Conference
• Year: 2008
• Where: CP
• Authors: Steven Halim, Roland H. C. Yap, Felix Halim
• Keywords: Artificial Intelligence, Autocorrelation Binary Sequence, CP 2008, Stochastic Local Search, White-box Visualization