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| author |   Lorenzo Trevisan | 2017-09-23 17:12:38 +0200 |
|---|---|---|
| committer |   David Spencer | 2017-09-23 17:12:38 +0200 |
| commit | 2b3ebf402315496abda7d4fddcd659cad301ca8e (patch) | |
| tree | df63ab9fc04bece63d2a19398a6ac011cd570880 /academic/dakota/README | |
| parent | 1d1d7530a824742c368a4770dd14d93e7433e6ad (diff) | |
| download | slackbuilds-2b3ebf402315496abda7d4fddcd659cad301ca8e.tar.gz | |
academic/dakota: Added (optimization toolkit).
Signed-off-by: David Spencer <idlemoor@slackbuilds.org>
Diffstat (limited to 'academic/dakota/README')
| -rw-r--r-- | academic/dakota/README | 12 |
1 files changed, 12 insertions, 0 deletions
diff --git a/academic/dakota/README b/academic/dakota/README new file mode 100644 index 0000000000..01d05fcdec --- /dev/null +++ b/academic/dakota/README @@ -0,0 +1,12 @@ +The Dakota toolkit provides a flexible, extensible interface between +analysis codes and iteration methods. Dakota contains algorithms for +optimization with gradient and nongradient-based methods; uncertainty +quantification with sampling, reliability, stochastic expansion, and +epistemic methods; parameter estimation with nonlinear least squares +methods; and sensitivity/variance analysis with design of experiments +and parameter study capabilities. These capabilities may be used on +their own or as components within advanced strategies such as +surrogate-based optimization, mixed integer nonlinear programming, or +optimization under uncertainty. + +Optional dependency: openmpi |