Hello all, I am in the process of evaluating SLSQP implementations from the scipy and NLOpt libraries for use in a python system I am working on.
We would like to be able to view the internal state of the SLSQP method as iterations are completed (mainly to let us do post mortems when long running optimisations fail or to let us pause/resume exactly). I see that the NLOpt SLSQP imp. has methods added to save/restore the internal state so: 1) how hard would it be to pass that information back up to the python layer (I've not used SWIG before but I imagine its not too tricky)? 2) would such a patch stand a chance of making it into the NLOpt mainline or would this approach 'break' the general nlopt api? 3) I assume here that the state being saved (together with the original problem specification) is all you need to resume a SLSQP optimisation exactly? thanks in advance, Simon _______________________________________________ NLopt-discuss mailing list [email protected] http://ab-initio.mit.edu/cgi-bin/mailman/listinfo/nlopt-discuss
