Prof. Johnson, Thanks for your quick response!
At 7:31 on Wednesday, June 27 2012, Steven G. Johnson wrote: > On Jun 26, 2012, at 9:50 PM, Matt Peddie wrote: > > I had a look at slsqp.c from nlopt-2.2.4, but it looks like adding > > it myself would be a pretty serious undertaking. Note that unlike > > in [1], I'm not optimizing functions of millions of variables; my > > application is closer to 100. > > You wouldn't want to add it to SLSQP, as that is designed to be a > quasi-Newton code that estimates the Hessian, and it is also very > messy code as you can see. I had figured I'd replace the estimate with the analytic one, but I really don't know how the code works. Fair enough. > I have recently played with adding an MMA-like algorithm that allows > you to pass in an approximate Hessian as a preconditioner, which could > in principle exploit an exact Hessian if you supply it. On the other > hand, I can only prove convergence if the preconditioner is positive > semi-definite, so if your Hessian does not have this property it may > cause problems. Would the new MMA-like algorithm support nonlinear equality constraints? I'm not looking for something that can take a Hessian just so I can have the fun of passing it one; since automatic differentiation gives me the Hessian without any extra work on my part, I wondered whether I could easily put it to use. SLSQP will probably do fine as it is. Thanks for making this superb code. Matt _______________________________________________ NLopt-discuss mailing list [email protected] http://ab-initio.mit.edu/cgi-bin/mailman/listinfo/nlopt-discuss
