Michael Hennebry wrote on Wednesday, April 04, 2012, > On Tue, 3 Apr 2012, John Perry wrote: > >> From a previous conversation, I understand that setting upper bounds for > >> integer solutions helps the mip preprocessor find feasible solutions > >> for minimization problems that have no maximum. I can make this work > >> with the systems I'm solving right now, but I'm not sure how to set a > >> good upper bound in general. > > > > Is there a good rule of thumb for this? > > Is the corresponding max problem really unbounded?
Now that you make me think of it, it's unbounded above only in theory; the largest I could have is machine word size. (I don't mean GLPK; this has to do with the result, which is then fed into a non-LP algorithm.) I tried it just now, though, and that's also too large. If I set the maximum at 1000, I get solutions; raising it to a mere 5000 slows it down tremendously. I could loop the upper bounds from, say, 1000, but this seems so... CLUMSY. Since I'm adding constraints after having solved once already, I could also use the results from the previous solution to guess an upper bound, then go up from there when it fails. But that also seems clumsy. I guess I was hoping there might be a way of making an educated guess of the upper bounds on the variables from solutions obtained by the simplex algorithm. regards john perry -- John Perry Associate Professor Department of Mathematics, Box 5045 University of Southern Mississippi Hattiesburg MS 39406 [email protected] Let me seek you in desiring you, let me desire you in seeking you, let me find you in loving you, let me love you in finding you. - Anselm _______________________________________________ Help-glpk mailing list [email protected] https://lists.gnu.org/mailman/listinfo/help-glpk
