On the Use of Direct Search Methods for Stochastic Optimization

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dc.contributor.authorTrosset, Michael W.en_US
dc.date.accessioned2018-06-18T17:48:14Zen_US
dc.date.available2018-06-18T17:48:14Zen_US
dc.date.issued2000-06en_US
dc.date.noteJune 2000en_US
dc.description.abstractWe examine the conventional wisdom that commends the use of directe search methods in the presence of random noise. To do so, we introduce new formulations of stochastic optimization and direct search. These formulations suggest a natural strategy for constructing globally convergent direct search algorithms for stochastic optimization by controlling the error rates of the ordering decisions on which direct search depends. This strategy is successfully applied to the class of generalized pattern search methods. However, a great deal of sampling is required to guarantee convergence with probability one.en_US
dc.format.extent14 ppen_US
dc.identifier.citationTrosset, Michael W.. "On the Use of Direct Search Methods for Stochastic Optimization." (2000) <a href="https://hdl.handle.net/1911/101949">https://hdl.handle.net/1911/101949</a>.en_US
dc.identifier.digitalTR00-20en_US
dc.identifier.urihttps://hdl.handle.net/1911/101949en_US
dc.language.isoengen_US
dc.titleOn the Use of Direct Search Methods for Stochastic Optimizationen_US
dc.typeTechnical reporten_US
dc.type.dcmiTexten_US
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