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Signed-off-by: B. Watson <yalhcru@gmail.com> Signed-off-by: Willy Sudiarto Raharjo <willysr@slackbuilds.org>
16 lines
807 B
Text
16 lines
807 B
Text
The Dakota toolkit provides a flexible, extensible interface between
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analysis codes and iteration methods. Dakota contains algorithms for
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optimization with gradient and nongradient-based methods; uncertainty
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quantification with sampling, reliability, stochastic expansion,
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and epistemic methods; parameter estimation with nonlinear least
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squares methods; and sensitivity/variance analysis with design of
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experiments and parameter study capabilities. These capabilities may
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be used on their own or as components within advanced strategies such
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as surrogate-based optimization, mixed integer nonlinear programming,
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or optimization under uncertainty.
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Optional dependency: openmpi (for distributed memory parallel
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capabilities)
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You can build with multiple jobs by setting the MAKEFLAGS environment
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variable.
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