Basin Hopping with synched multi L-BFGS local searches. Parallel implementation in multi-CPU and GPUs
Ferreiro-Ferreiro, Ana M.,
García-Rodríguez, José A.,
Luis Souto and
Applied Mathematics and Computation, 2019, vol. 356, issue C, 282-298
In this work, a technique for improving the convergence properties (speed and reliability) of a non monotonic Basin Hopping algorithm is presented. This modification of Basin Hopping happens to be highly parallelizable and therefore the parallel implementation is shown both for multi-CPU and GPU architectures. A benchmark of classical global optimization tests is run, focussing in a number of tests in the literature that result to be particularly hard for Basin Hopping.
Keywords: Global optimization; Basin Hopping; L-BFGS; Parallel; Multi-CPU; GPU (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:apmaco:v:356:y:2019:i:c:p:282-298
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