That explains. Thanks so much!
--- On Tue, 6/2/09, Robert Fourer <
4er@...> wrote:
> From: Robert Fourer <
4er@...>
> Subject: [AMPL 2564] Re: FilMINT optimal solution really optimal?
> To:
ampl@..., "'x'" <
to_rent_2000@...>
> Date: Tuesday, June 2, 2009, 11:02 AM
>
>
> For answers to questions about FilMINT, see
>
>
http://www.mcs.anl.gov/~leyffer/papers/fm.pdf>
> where it is stated,
>
> ... we focus on the case where the
> functions f and g_j are
> convex, so that by relaxing the
> restriction y in Z^p, a convex
> program is formed. The techniques we
> suggest may be applied
> as a heuristic in the case that one or
> more of the functions
> are nonconvex.
>
> This suggests that FilMINT does not guarantee a global
> optimum when the
> functions are not convex. For more up-to-date
> information you can contact
> the authors.
>
> Bob Fourer
>
4er@...
>
>
> > -----Original Message-----
> > From:
ampl@...
> [mailto:
ampl@...]
>
> > On Behalf Of x [
to_rent_2000@...]
> > Sent: Monday, June 01, 2009 9:25 PM
> > To:
ampl@...
> > Subject: [AMPL 2563] FilMINT optimal solution really
> optimal?
> >
> >
> > When filMINT solver reports "Optimal solution found"
> does it really mean
> > global optimal solution?
> >
> > Does the solver assume convexity for all functions in
> the model? Where do
> > we get such info about the solver?
> >
> > For my model, the solver reports optimal solution.
> However, there are at
> > least two variables that do not have optimal values.
> What I mean is,
> > solver could have picked different values for these
> variables and have
> > gotten lower values for the objective function (this
> being a minimization
> > problem).
> >
> > Thanks in advance!
> >
>
>
>
> >
>
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