Hopping between distant basins

Maldon Goodridge (), John Moriarty (), Jure Vogrinc () and Alessandro Zocca ()
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Maldon Goodridge: Queen Mary University of London
John Moriarty: Queen Mary University of London
Jure Vogrinc: University of Warwick
Alessandro Zocca: Vrije Universiteit Amsterdam

Journal of Global Optimization, 2022, vol. 84, issue 2, No 9, 465-489

Abstract: Abstract We present and numerically analyse the Basin Hopping with Skipping (BH-S) algorithm for stochastic optimisation. This algorithm replaces the perturbation step of basin hopping (BH) with a so-called skipping mechanism from rare-event sampling. 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.

Keywords: Basin hopping; Stochastic optimisation; Skipping sampler; Rare events; Markov chains; 65K10; 90C26 (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s10898-022-01153-z

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