Parallel Space Decomposition of the Mesh Adaptive Direct Search Algorithm

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dc.contributor.authorAudet, Charles
dc.contributor.authorDennis, J.E. Jr.
dc.contributor.authorLe Digabel, Sébastien
dc.date.accessioned2018-06-18T17:58:15Z
dc.date.available2018-06-18T17:58:15Z
dc.date.issued2007-11
dc.date.noteNovember 2007
dc.description.abstractThis paper describes a Parallel Space Decomposition (PSD) technique for the Mesh Adaptive Direct Search (MADS) algorithm. MADS extends Generalized Pattern Search for constrained nonsmooth optimization problems. The objective here is to solve larger problems more efficiently. The new method (PSD-MADS) is an asynchronous parallel algorithm in which the processes solve problems over subsets of variables. The convergence analysis based on the Clarke calculus is essentially the same as for the MADS algorithm. A practical implementation is described and some numerical results on problems with up to 500 variables illustrate advantages and limitations of PSD-MADS.
dc.format.extent30 pp
dc.identifier.citationAudet, Charles, Dennis, J.E. Jr. and Le Digabel, Sébastien. "Parallel Space Decomposition of the Mesh Adaptive Direct Search Algorithm." (2007) <a href="https://hdl.handle.net/1911/102078">https://hdl.handle.net/1911/102078</a>.
dc.identifier.digitalTR07-15
dc.identifier.urihttps://hdl.handle.net/1911/102078
dc.language.isoeng
dc.titleParallel Space Decomposition of the Mesh Adaptive Direct Search Algorithm
dc.typeTechnical report
dc.type.dcmiText
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