Parallel Space Decomposition of the Mesh Adaptive Direct Search Algorithm

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dc.contributor.authorAudet, Charlesen_US
dc.contributor.authorDennis, J.E. Jr.en_US
dc.contributor.authorLe Digabel, Sébastienen_US
dc.date.accessioned2018-06-18T17:58:15Zen_US
dc.date.available2018-06-18T17:58:15Zen_US
dc.date.issued2007-11en_US
dc.date.noteNovember 2007en_US
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.en_US
dc.format.extent30 ppen_US
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>.en_US
dc.identifier.digitalTR07-15en_US
dc.identifier.urihttps://hdl.handle.net/1911/102078en_US
dc.language.isoengen_US
dc.titleParallel Space Decomposition of the Mesh Adaptive Direct Search Algorithmen_US
dc.typeTechnical reporten_US
dc.type.dcmiTexten_US
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