<div dir="ltr">Hi Stefan,<div><br></div><div>Thank you for your quick response!  A follow up question: if I start with an infeasible solution, is it possible that I get trapped in a locally optimal solution *just* outside the feasible region (assuming such solutions exist)?<div><br></div><div>Victor</div></div></div><div class="gmail_extra"><br><div class="gmail_quote">On Mon, Sep 12, 2016 at 10:47 AM, Stefan Vigerske <span dir="ltr"><<a href="mailto:stefan@math.hu-berlin.de" target="_blank">stefan@math.hu-berlin.de</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex">Hi,<br>
<br>
if you provide a feasible starting point, I would imagine that nonconvexity of the objective function outside of the feasible area doesn't matter.<br>
<br>
Stefan<div><div class="h5"><br>
<br>
<br>
On 09/12/2016 04:36 PM, Victor Wu wrote:<br>
</div></div><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div><div class="h5">
Hello,<br>
<br>
I have a nonlinear problem where the objective function is non-convex in<br>
general, but is convex over the (convex) feasible region of interest (thus,<br>
theoretically I have a convex problem).  Do you have any recommendations on<br>
how I should represent the objective (i.e., write the objective in its<br>
original non-convex form and enforce my feasible region or do something<br>
else) in IpOpt?  My concern is whether IpOpt would reach the<br>
*theoretically* global minimizer and if it depends on my implementation.<br>
<br>
Thank you,<br>
Victor Wu<br>
<br>
<br>
<br></div></div>
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<br>
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