[Ipopt] Some suggestions to speed up code sought

[Stefan Vigerske]

Hi,

On 11/11/2015 07:27 PM, jmogali at andrew.cmu.edu wrote:
> Hi,
>       Yes, this is despite setting Hessian as constant. On reading the
> function description for ReOptimizeTNLP(), it turns out that all they
> are expecting is the non zero structure of the matrices to be the
> same and nothing about the actual values. So, logically they would
> need to recompute the Hessian.

I think I understood this wrong before.
hessian_constant just means, that during one call of (Re)OptimizeTNLP, 
the Hessian should be requested only once (not sure if that also holds 
if Ipopt goes into restoration mode). But for each new call to 
(Re)OptimizeTNLP, it is ok that the Hessian is reevaluated. I think 
there is not much to gain when reusing also the Hessian values from a 
previous (Re)OptimizeTNLP call.

Stefan

>
> Regarding the MA97 throwing error messages, I feel it is rather strange. I
> would like to hear your take on the matter.
> So the Hessian and Jacobian are constant throughout the lifespan of my
> program. When I call ReOptimizeTNLP() at each iteration of my program, it
> is only at some iterations that MA97 displays that error message. I find
> that strange, since either I would expect that every time ReOptimizeTNLP()
> is called, MA97 should have displayed that message or never display it at
> all. If you have any insights into the matter, can you please share your
> take on why it is happening.
>
> PS-: I have thoroughly checked my implementation, if indeed the hessian
> and jacobian I provide is changing. Nothing seems to be wrong in my code.
>
> Thanks,
> Jayanth
>
>> Hi,
>>
>> On 11/11/2015 04:52 AM, jmogali at andrew.cmu.edu wrote:
>>> Hi,
>>>        @Stefan -: Thanks for letting me know the ReOptimizeTNLP() option.
>>> Also warm start has significantly improved the timings.
>>>
>>> However, I observe that Hessian is being recalculated when
>>> ReOptimizeTNLP() executes. I know that this has been included for
>>> generality. I would like to however exploit the fact that throughout the
>>> lifespan of my program, the Hessian I provide remains a constant. Is
>>> there
>>> any way I can make IPOPT exploit this fact ?
>>
>> Even if you set the mentioned hessian_constant option?
>>
>>> On a side note, the MA97 solver is being used to solve the KKT matrix
>>> right ?
>>
>> Yes, I would think so.
>> To see what exactly is solved there, see (13) in the implementation
>> paper (http://www.optimization-online.org/DB_HTML/2004/03/836.html).
>>
>> Stefan
>>
>>>
>>> Thanks,
>>> Jayanth
>>>
>>>> Hi,
>>>>
>>>> if the structure of the Jacobian and Hessian do not change, have you
>>>> considered using ReOptimizeTNLP() instead of OptimizeTNLP()?
>>>> I haven't checked, but likely that will avoid calls that get the
>>>> problem
>>>> structure (n, m, sparsity pattern).
>>>>
>>>> There are also option to tell Ipopt that the Jacobian and the Hessian
>>>> are constant (jac_c_constant, jac_d_constant, hessian_constant):
>>>> http://www.coin-or.org/Ipopt/documentation/node43.html#SECTION000114070000000000000
>>>>
>>>> The TNLP is mostly implemented by you, while Ipopt only defines the
>>>> interface. From the Ipopt point-of-view, it should be save to reuse the
>>>> TNLP object.
>>>>
>>>> MA97 error -7 means that the matrix passed to MA97 is singular. See
>>>> http://www.hsl.rl.ac.uk/specs/hsl_ma97.pdf for a full documentation of
>>>> MA97.
>>>>
>>>> Stefan
>>>>
>>>> On 11/09/2015 03:35 AM, jmogali at andrew.cmu.edu wrote:
>>>>> Hi,
>>>>>         I would like to have some suggestions to speed up my code. I
>>>>> run
>>>>> my
>>>>> code in a loop where at each iteration I call the function
>>>>> OptimizeTNLP(); however I create a single TNLP object that calls
>>>>> OptimizeTNLP at each iteration. After every iteration, I change the
>>>>> objective function I am optimizing by a little.
>>>>>
>>>>> 1. The structure of the hessian is constant across iterations, is
>>>>> there
>>>>> a
>>>>> way to make IPOPT avoid calling eval_h with values=null be passed to
>>>>> my
>>>>> program at every iteration ?
>>>>> On a similar note, my Jacobian is a constant
>>>>> for all iterations, is there a way to make IPOPT avoid calling
>>>>> eval_jac_g
>>>>> , get_bounds_info for every iteration ?
>>>>>
>>>>> Please note that in the above question, by iterations I am NOT
>>>>> referring
>>>>> to those when IPOPT executes OptimizeTNLP().
>>>>>
>>>>> 2. Is it safe to reuse the TNLP object between iterations?
>>>>>
>>>>> 3. I sometimes get the message "Error return from ma97_factor. Error
>>>>> flag
>>>>> =  -7" , does this mean the KKT matrix is singular ?
>>>>>
>>>>> Thanks,
>>>>> Jayanth
>>>>>
>>>>> _______________________________________________
>>>>> Ipopt mailing list
>>>>> Ipopt at list.coin-or.org
>>>>> http://list.coin-or.org/mailman/listinfo/ipopt
>>>>>
>>>>
>>>>
>>>> --
>>>> http://www.gams.com/~stefan
>>>>
>>>
>>>
>>
>>
>> --
>> http://www.gams.com/~stefan
>>
>
>


-- 
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