Improved Branch-and-Bound for Low Autocorrelation Binary Sequences

The Low Autocorrelation Binary Sequence problem has applications in telecommunications, is of theoretical interest to physicists, and has inspired work by many optimisation researchers because of its difficulty. For many years it was considered unsuitable for solution by metaheuristics because of its search space topology, but in recent years metaheuristics have found long high-quality sequences. However, complete search has not progressed since a parallel branch-and-bound method of 1996. In this paper we find four ways of improving branch-and-bound, leading to a tighter relaxation, faster convergence to optimality and better scalability. We also extend known optimality results for skew-symmetric sequences from length 73 to 89.