Dear Jean,
I think that Teiji is referring to the problem that if you use the
multiple-threaded version of KNITRO you will have different solutions
even in the case of using the same initial starting point.
Regards,
Olaf
On 30.05.2017 11:50, MAEGHT Jean wrote:
Dear Teiji,
Knitro is using interior point methods.
Interior point method are known to have bad properties regarding initial point
(=if you start an interior point solver with an initial point which is already
an optimal point, the solver will not figure it out and may even behave worse
than starting from a dummy initial point).
But still, many times if you have a good guess or a good initial point, the
solver may behave better.
When you run your series of OPFs, the result is used as initial point for the
next OPF. This may explain different behavior of the solver.
Implicit question: why are optimal values different?
1/ as OPF is a non convex problem, you only get a local minimum, so maybe you
don't have the same local minimum each time
2/ stopping criteria are using tolerances; maybe within the tolerances you
used, there are several solutions.
For fine tuning of Knitro, you can see how we did in this paper:
https://arxiv.org/abs/1603.01533
page 4, section V.A.
knitro matlab documentation:
https://www.artelys.com/tools/knitro_doc/3_referenceManual/knitromatlabReference.html
If you force V and theta to zero in your case before each run, you wshould
always get the same result.
Best regards,
--
Jean Maeght
RTE - R&D Division
-----Message d'origine-----
De : bounce-121566163-75398...@list.cornell.edu
[mailto:bounce-121566163-75398...@list.cornell.edu] De la part de Olaf Schenk
Envoyé : lundi 29 mai 2017 09:51
À : MATPOWER discussion forum <matpowe...@list.cornell.edu>; Drosos Kourounis
<kouro...@usi.ch>; Kardoš Juraj <juraj.kar...@usi.ch>
Objet : Re: Different results at repeated execution
Hi Teiji,
I suggest to use an optimizer that has parallel bitwise reproducible
functionality.
KNITRO is not able to give you identical results, but the IPOPT/PARDISO
5.0 binaries offers this functionality. You can it use the binaries under "Matpower
Libraries" on
http://www.pardiso-project.org/#download
Best,
Olaf Schenk
On 27.05.2017 13:12, Teiji Ponishi wrote:
Hi all,
I use MATPOWER 5.1, and knitro as a optimization solver.
When I run the MATPOWER repeatedly, the values of objective function
can be slightly reduced as follows:
1st 8740.2
2nd 8731.9
3rd 8728.3
But, after MATLAB was restarted, the same values of objective function
can be obtained.
1st 8740.2
2nd 8731.9
3rd 8728.3
< MATLAB is shutdown and restarted >
4th 8740.2
5th 8731.9
6th 8728.3
How do I obtain same results of MATPOWER without restarting MATLAB ?
Best,
Teiji
--
Prof. Dr. Olaf Schenk
Advanced Computing Laboratory
Institute of Computational Science
Università della Svizzera italiana ** Switzerland
Via Giuseppe Buffi 13 ** 6900 Lugano
Phone: +41 (0) 79 368 22 81 ** Fax.: +41 (0)58 666 45 36
Email: olaf.sch...@usi.ch ** http://www.ics.inf.usi.ch
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Prof. Dr. Olaf Schenk
Advanced Computing Laboratory
Institute of Computational Science
Università della Svizzera italiana ** Switzerland
Via Giuseppe Buffi 13 ** 6900 Lugano
Phone: +41 (0) 79 368 22 81 ** Fax.: +41 (0)58 666 45 36
Email: olaf.sch...@usi.ch ** http://www.ics.inf.usi.ch
