Re: MODELING A OBJECTIVE FUNCTION WITH SOFT CONSTRAINTS.

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?
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