Michael The technique you described of relaxing all but 1-2 days and fixing the integer part sounds interesting. Are there any published works implenting the technique. I am also working on a timetabling/student enrollment problem at my college.
On Wed, Jun 13, 2018, 9:50 AM Michael Hennebry < [email protected]> wrote: > On Tue, 12 Jun 2018, João Pedro de Sá Moreira wrote: > > > I?m currently working on a timetable model that is supposed to deal if a > pretty big number of variables. > > > > On initial tests i can see it takes a fair time to get to a LP solution > (about 30m) and then it starts to work on finding the optimal integer > solution. > > > > The problem is that in this part, it takes about 5h working on analyzing > the whole tree, but the strange thing is that it keeps showing the same > value every iteration it does until it gets to the end of the tree. The > value it shows is the same value that can be seen when it finds the lp > solution, does it means that the LP solution was the optimal since the > beginning? Am i able to interrupt the execution and take a look at this > solution? Or is there a way to speed it up a little bit? > > I suspect the problem is a lot of near-equivalent solutions. > Best-first can be truly horrible on some such things. > Try depth-first. > > If you have what amounts to 40 loosely connected subproblems, > each with five nearly optimal solutions. > Best-first could grind away for a very long time. > > Another possibility is to do the problem in stages. > For the first stage, > require only the first two days' variables to be integer. > For the second stage, > fix the first day's integers from the first stage > and require only the second and third days' variables to be integer. > > If you know the problem has a solution, > how do you know? > That might provide a mechanism for getting a solution. > _______________________________________________ > Help-glpk mailing list > [email protected] > https://lists.gnu.org/mailman/listinfo/help-glpk >
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