  We present the Basin Hopping with Skipping (BH-S) algorithm for stochastic
optimisation, which replaces the perturbation step of basin hopping (BH) with a
so-called skipping proposal from the rare-event sampling literature. Empirical
results on benchmark optimisation surfaces demonstrate that BH-S can improve
performance relative to BH by encouraging non-local exploration, that is, by
hopping between distant basins.
