[Coin-ipopt] Best ipopt options for fast QCP solution?

[Frank J. Iannarilli]

Hi,


I'm using IPOPT, via NEOS-AMPL interface, to solve a 
quadratically-constrained program (QCP).  Since the non-linearity of my 
problem is relatively simple compared to the heavier lifting that IPOPT is 
designed to handle, I surmise there may be options to increase the 
execution speed. Presently, I accept all the default settings.


Here's my problem statement:

==============================================
Decision variables: x[i], deviation[i]; continuous, >=0, <=bigX
                  : w[j]; continuous, >=0, <=1

min: deviation[i];  % linear objective

s.t.
   % Quadratic LAD constraints:

   -deviation[i] <= Sum{j} (a[i,j]*x[i%j]-b[i])*w[j];

   Sum{j} (a[i,j]*x[i%j]-b[i])*w[j] <= deviation[i];

   %%% the notation x[i%j] is shorthand for indexing
   %%% as some (unstated) function of i and j

   % GUB on w[j]
   sum{j} w[j] = 1;
===============================================


Does the NEOS-AMPL interface provide all the derivative/Hessian info to 
IPOPT?

I am willing to run IPOPT locally, if necessary, to obtain the wider array 
of options than available thru the AMPL interface.

Thanks in advance for your suggestions!



Frank J. Iannarilli, franki at aerodyne.com
Aerodyne Research, Inc., 45 Manning Rd., Billerica, MA 01821 USA
www.aerodyne.com/cosr/cosr.html