On Tue, Nov 27, 2007 at 11:07:30PM -0700, Charles R Harris wrote: > This is not a trivial problem, as you can see by googling mixed integer least > squares (MILS). Much will depend on the nature of the parameters, the number > of > variables you are using in the fit, and how exact the solution needs to be. > One > approach would be to start by rounding the coefficients that must be integer > and improve the solution using annealing or genetic algorithms to jig the > integer coefficients while fitting the remainder in the usual least square > way, > but that wouldn't have the elegance of some of the specific methods used for > this sort of problem. However, I don't know of a package in scipy that > implements those more sophisticated algorithms, perhaps someone else on this > list who knows more about these things than I can point you in the right > direction.
Would this be a good candidate for a genetic algorithm? I haven't used GA before, so I don't know the typical rate of convergence or its applicability to optimization problems. Regards Stéfan _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
