Dear Olaf and Jean,

I am sorry for my insufficient information on this issue.

Actually, as I am not a expert on these software, it is difficult for me to
resolve it immediately.

First of all, I will try to resolve it by using knitro based on your paper
and knitro manual.

If it is difficult, I will try to change the solver to IPOPT/PARDISO with
parallel bitwise reproducible functionality.

Thank you very much for your valuable comments.

best regards,

Teiji

2017-05-30 19:54 GMT+09:00 MAEGHT Jean <[email protected]>:

> Dear Olaf,
> I don't agree with your analysis. The results shown by Teiji are
> deterministic. He made 2 series of 3 runs and the 2 series are identical.
> Jean
>
> >> 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
>
> -----Message d'origine-----
> De : [email protected] [mailto:bounce-121567438-
> [email protected]] De la part de Olaf Schenk
> Envoyé : mardi 30 mai 2017 11:57
> À : MATPOWER discussion forum <[email protected]>
> Objet : Re: Different results at repeated execution
>
> 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/knitromatla
> > bReference.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 : [email protected]
> > [mailto:[email protected]] De la part de Olaf
> > Schenk Envoyé : lundi 29 mai 2017 09:51 À : MATPOWER discussion forum
> > <[email protected]>; Drosos Kourounis <[email protected]>;
> > Kardoš Juraj <[email protected]> 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: [email protected]              **  http://www.ics.inf.usi.ch
> >
> >
> >
> >
> > "Ce message est destiné exclusivement aux personnes ou entités
> auxquelles il est adressé et peut contenir des informations privilégiées ou
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> >
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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: [email protected]              **  http://www.ics.inf.usi.ch
>
>
>
>
> "Ce message est destiné exclusivement aux personnes ou entités auxquelles
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> l'indiquer par retour, de ne pas le transmettre et de procéder à sa
> destruction.
>
> This message is solely intended for the use of the individual or entity to
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