Your question is not mathematically clear enough for me to understand it. Try asking it in math notation.
On Wed, Aug 15, 2018, 10:05 AM Joao Pedro <[email protected]> wrote: > Hello, > > I'm currently trying to model a large scale school timetabling problem. My > current objective function tries to maximize the set of teacher preferences > allocated in the final solution. But, there is a problem, every course has > a specific shift that it happens but sometimes that are classes that needs > to be taken in another shift. > > For example, the engineers can mainly take classes in the morning but > sometimes that are classes that needs to be taken in the afternoon. This > situation happens with a specif set of courses in which the total sum of > daily classes on a week exceeds the total possible number of classes on a > week. > > I'm trying to model this situation: > > An objective function that maximizes the teachers preferences - > (minus)*(weight)*a soft constraint that allows these specific courses to > take classes outside their main shift. > > I mean: If a a course that only takes classes in the morning happens to > have some clases in the afternoon, this can be done but it will cause a > penalty to be added in the objective function. > > The problem is that it doesn't seems to be working, the model just > allocates a lot of classes in this extra shifts independent of the weight > that i put in the soft constraint, it seems like it's somehow better to > have this penalties instead of avoiding them as much as possible. > > What could be possible to change? > _______________________________________________ > Help-glpk mailing list > [email protected] > https://lists.gnu.org/mailman/listinfo/help-glpk >
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