On 15 October 2013 16:43, Steven G. Johnson <[email protected]> wrote:

>
> On Oct 15, 2013, at 9:40 AM, MM <[email protected]> wrote:
> > 1. Can nlopt be used for such a problem?
>
> Yes, it sounds like a standard nonlinear-constrained optimization problem.
>
> > 2. Can the problem be simplified to dealing just with f2 and f3?
>
> I don't see how you can possibly remove your objective f1 from the problem.
>

Just to make sure I expressed myself correctly here: f1 is simply = f2/f3.
In order of priority, I want to maximize f1, then maximize f2 with
f2>=min2, and minimize f3<=min3, if there is such a solution(s)

I could formulate the problem as:    maximize f2 and minimize f3 (this may
be a Pareto frontier), and then choose the point on this frontier that
gives the max f2/f3

Thanks,

> Ultimately, I am not looking for the absolute max of f1(X) in the
> feasible region,
> > I am looking for the "ball" or "hypercube" of length E in each
> dimension, inside the feasible region, such that the average of f1(X) over
> that hypercube is maximum.
>
> This sounds like it is just a change of objective.  Instead of your
> objective being f1, it would be the mean of f1 over a ball of diameter E
> centered at X.
>
>
Just to clarify
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