<div dir="ltr">Hi Tony, <div><br></div><div>Funny to get a reply from someone so close by after launching a message out to the colossal internet.</div><div><br></div><div>I wasn't warm-starting at all--that's a great suggestion. Hopefully the Lagrange multipliers won't change too much between iterations. Otherwise, there may be some problem-specific ways to guess a reasonable Lagrange multiplier here.</div><div><br></div><div>Regarding speed & algorithm choice, BFGS seems like the right fit here, and in this problem it's not really practical to compute the hessian (which is dense).</div><div>But I'll be sure to check out print_timing_statistics -- I'm new to Ipopt and haven't found these handy tools yet.</div><div><br></div><div>John</div><div><br></div><div class="gmail_extra"><br><div class="gmail_quote">On Wed, Nov 12, 2014 at 10:19 PM, Tony Kelman <span dir="ltr"><<a href="mailto:kelman@berkeley.edu" target="_blank">kelman@berkeley.edu</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex">
<div dir="ltr">
<div dir="ltr">
<div style="FONT-SIZE:12pt;FONT-FAMILY:'Calibri';COLOR:#000000">
<div>Hi John, good to see groups next door also using Ipopt.</div>
<div><font></font> </div>
<div>Generally speaking this is a pretty hard thing to do with an interior-point
method. Are you warm-starting the dual variables as well, or just the primal?
That may help, but it depends how closely related the subproblems are. I’d also
avoid doing quasi-newton hessian approximations if you have a speed-critical
application, you’ll get better convergence in most cases if you are using a
modeling tool that can provide exact Hessians. Have you looked at the breakdown
of computation time from print_timing_statistics?</div>
<div> </div>
<div>-Tony</div>
<div> </div>
<div style="FONT-SIZE:small;TEXT-DECORATION:none;FONT-FAMILY:"Calibri";FONT-WEIGHT:normal;COLOR:#000000;FONT-STYLE:normal;DISPLAY:inline">
<div style="FONT:10pt tahoma">
<div> </div>
<div style="BACKGROUND:#f5f5f5">
<div><b>From:</b> <a title="john.d.schulman@gmail.com" href="mailto:john.d.schulman@gmail.com" target="_blank">John Schulman</a> </div>
<div><b>Sent:</b> Wednesday, November 12, 2014 10:14 PM</div>
<div><b>To:</b> <a title="ipopt@list.coin-or.org" href="mailto:ipopt@list.coin-or.org" target="_blank">ipopt@list.coin-or.org</a> </div>
<div><b>Subject:</b> Re: [Ipopt] Low # iters, ensuring that solution remains
feasible</div></div></div>
<div> </div></div>
<div style="FONT-SIZE:small;TEXT-DECORATION:none;FONT-FAMILY:"Calibri";FONT-WEIGHT:normal;COLOR:#000000;FONT-STYLE:normal;DISPLAY:inline"><div><div>
<div dir="ltr">Oops, "wildly feasible" in the first paragraph should be "wildly
infeasible"</div>
<div class="gmail_extra">
<div> </div>
<div class="gmail_quote">On Wed, Nov 12, 2014 at 10:06 PM, John Schulman <span dir="ltr"><<a href="mailto:john.d.schulman@gmail.com" target="_blank">john.d.schulman@gmail.com</a>></span> wrote:<br>
<blockquote class="gmail_quote" style="PADDING-LEFT:1ex;MARGIN:0px 0px 0px 0.8ex;BORDER-LEFT:#ccc 1px solid">
<div dir="ltr">
<div>Short: </div>
<div> </div>
<div>I am calling Ipopt repeatedly to solve a series of subproblems.</div>
<div>For each subproblem, Ipopt is initialized with a feasible solution, and
max_iter is set to 50 or so. </div>
<div>The optimization terminates early, and often this intermediate solution
is wildly feasible.</div>
<div>I'm wondering if there are any settings that will ensure that the result
is nearly feasible.</div>
<div> </div>
<div>Longer:</div>
<div> </div>I am using Ipopt to solve a series of subproblems of the form
<div>minimize f(x), subject to g(x) < delta,</div>
<div>Here g is a distance function of sorts, measuring Distance(x_0,x), where
x_0 is the initialization.</div>
<div>So the the initial point x_0 is feasible.</div>
<div>x has dimension 50000 or so, so I am using hessian_approximation with
limited memory.</div>
<div>
<div> </div>
<div>I need to keep to a low number of iterations, say 50 or 100, so the
overall computation time remains reasonable.</div></div>
<div>It's not essential at all that the solution generated is optimal; I just
want to improve the objective as much as possible while remaining
feasible.</div>
<div> </div>
<div>I tried fiddling with the barrier parameters but didn't have any
luck.</div>
<div>Any suggestions?<br>Thanks in advance for your time.</div><span><font color="#888888">
<div> </div>
<div>John</div>
<div> </div>
<div> </div>
<div> </div>
<div> </div></font></span></div></blockquote></div>
<div> </div></div>
</div></div><p>
</p><hr>
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