[ANN] OpenOpt 0.27 (optimization), FuncDesigner 0.17 (auto differentiation) - OR-Exchange [closed]most recent 30 from http://www.or-exchange.com2010-07-31T00:38:41Zhttp://www.or-exchange.com/feeds/question/107http://www.creativecommons.org/licenses/by-nc/2.5/rdfhttp://www.or-exchange.com/questions/107/ann-openopt-0-27-optimization-funcdesigner-0-17-auto-differentiation[ANN] OpenOpt 0.27 (optimization), FuncDesigner 0.17 (auto differentiation)Dmitrey2009-12-16T09:44:51Z2010-04-21T21:23:34Z
<p>Hi all,
I'm glad to inform you about release of OpenOpt 0.27 (numerical
optimization framework), FuncDesigner 0.17 (CAS with automatic
differentiation, convenient modelling of linear/nonlinear functions,
can use convenient modelling for some OpenOpt optimization problems
and systems of linear/nonlinear equations, possibly sparse or
overdetermined), DerApproximator 0.17 (finite-differences derivatives
approximation, get or check user-supplied).</p>
<p>These packages are written in Python language + NumPy; license BSD allows to use it in both free and closed-code soft</p>
<p>See also changelog for details: <a href="http://openopt.org/Changelog" rel="nofollow">http://openopt.org/Changelog</a></p>
<p>Regards, D. </p>
<p>P.S. Please excuse me if the message is beyond allowed ones, I will not post those here any more in the case.</p>
http://www.or-exchange.com/questions/107/ann-openopt-0-27-optimization-funcdesigner-0-17-auto-differentiation/108#108Answer by Michael Trick for [ANN] OpenOpt 0.27 (optimization), FuncDesigner 0.17 (auto differentiation)Michael Trick2009-12-16T12:39:18Z2009-12-16T12:39:18Z<p>I think at this point the consensus is to not allow announcements in the Q&A stream. I'll think of better ways to allow these sort of things. </p>
http://www.or-exchange.com/questions/107/ann-openopt-0-27-optimization-funcdesigner-0-17-auto-differentiation/110#110Answer by Mark for [ANN] OpenOpt 0.27 (optimization), FuncDesigner 0.17 (auto differentiation)Mark2009-12-16T17:58:08Z2009-12-16T17:58:08Z<p>Is it possible to run it in IronPython (with or without IronClad)?</p>