The general problem is not computationally tractable. You can trying stochastic algorithms, like simulated annealing or genetic programmig, but results depend on the problem. There is no point in computing derivatives in that case either.
On Sunday, August 18, 2013, Ajo Fod wrote: > Looks like Joptimizer is restricted to solving convex problems. > > My application is to minimize a generic non-linear function with linear > constraints. Know of anything that does it? > > -Ajo > > > On Thu, Aug 15, 2013 at 5:48 PM, Konstantin Berlin > <kber...@gmail.com<javascript:;> > >wrote: > > > There would be an advantage, true. I don't know if commons has one > > (doesn't look like it). You can also try http://www.joptimizer.com/ > > > > On Thu, Aug 15, 2013 at 4:59 PM, Ajo Fod <ajo....@gmail.com<javascript:;>> > wrote: > > > Hello, > > > > > > Is'nt there an advantage to being able to compute the Jacobian of the > > > gradient precisely at a point? > > > > > > If so, is there a class that uses the Jacobian instead of estimating > the > > > jacobian from the last few iteration as > > NonLinearConjugateGradientOptimizer > > > does? > > > > > > Thanks, > > > -Ajo > > > > --------------------------------------------------------------------- > > To unsubscribe, e-mail: dev-unsubscr...@commons.apache.org<javascript:;> > > For additional commands, e-mail: dev-h...@commons.apache.org<javascript:;> > > > > >
