[Ipopt] Some suggestions to speed up code sought

Thu Nov 12 07:40:54 EST 2015

Thanks a lot for the clarification Mr. Jonathan.

> The system solved by MA97 changes each iteration, with diagonal entries
> in the (1,1) block becoming more extreme towards 0 and +infinity [give
> or take the diagonal entries of the Hessian] depending on whether the
> associated constraint is active or not. This is what I'd expect to be
> causing the singular error messages at some iterations and not at others
> - it is perfectly normal for some problems (and by singular here we mean
> effectively numerically singular rather than structurally or in exact
> arithmetic).
>
> IIRC Ipopt just takes a singular error return as a signal to increase
> regularization of the system in the (1,1) block and then tries again.
> Hence it is probably just a case of needing a patch to tell MA97 not to
> print error messages where the user can see them :P.
>
> It may be worth playing with the ma97 scaling options if you are getting
> this a lot, and see if they make any difference. There is also the
> control.small value in the ma97 interface which defines what values are
> interpreted to define a matrix as singular. However you probably need to
> comprehend the Ipopt algorithm as a whole before determining if that is
> a sensible thing to do.
>
> If your Hessian isn't changing, does that imply your problem is linear
> or quadratic? There may be better solvers for such problems than Ipopt -
> dedicated LP/QP solvers are able to better exploit the structure and/or
> deal with the degeneracy in those cases iirc.
>
> Jonathan.
>
> On 11/11/15 18:27, 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.
>>
>> 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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