[Ipopt] Ipopt Digest, Vol 38, Issue 14
Xiaoming Yu
xiaoming.yu at mscsoftware.com
Wed Feb 27 19:56:41 EST 2008
Hi Damien :
Hello Damien:
In our typical problems, N (design varaibles) is about in a range 1,000 - 10,000 and M (constraints) is 10,000 - 100,000. The Jacobian is 100% dense but the Hessians are diagonal. How you think?
Thanks,
Xiaoming
-----Original Message-----
From: ipopt-bounces at list.coin-or.org [mailto:ipopt-bounces at list.coin-or.org] On Behalf Of Damien Hocking
Sent: Wednesday, February 27, 2008 4:40 PM
To: ipopt at list.coin-or.org
Subject: Re: [Ipopt] Ipopt Digest, Vol 38, Issue 14
Xiaoming,
How large is the dense matrix? Most sparse solvers will solve dense
problems of moderate size, but they're not as efficient.
Damien
-----Original Message-----
From: ipopt-bounces at list.coin-or.org [mailto:ipopt-bounces at list.coin-or.org]
On Behalf Of Xiaoming Yu
Sent: Wednesday, February 27, 2008 4:34 PM
To: Carl Laird; ZhangWeizhong
Cc: ipopt at list.coin-or.org
Subject: Re: [Ipopt] Ipopt Digest, Vol 38, Issue 14
Hi Dr. Wächter and Carl :
For engineering problems, many design cases have 100% dense jacobian. Using
IPOPT existing sparsity structure of jacobia requires more computer memory.
I know IPOPT is designed for the sparsity structure of large NLP. Do you
have a plan to provide another interface for dense jacobian (so, the user
can select for either sparsity or dense structure)? Do you expect we can
save meaningful computer memory by using dense jacobian structure? Is it too
difficult to make such changes?
Thanks,
Xiaoming
-----Original Message-----
From: ipopt-bounces at list.coin-or.org [mailto:ipopt-bounces at list.coin-or.org]
On Behalf Of Carl Laird
Sent: Wednesday, February 27, 2008 3:20 PM
To: ZhangWeizhong
Cc: ipopt at list.coin-or.org
Subject: Re: [Ipopt] Ipopt Digest, Vol 38, Issue 14
Hello Weizhong Zhang,
The method eval_jac_g is called by Ipopt for two purposes. The first
is to retrieve the sparsity structure of the matrix (where will the
non-zeros be). Note, that this structure is fixed throughout the
optimization and cannot change. The second purpose is to return the
values of the jacobian at a certain point. Ipopt will call eval_jac_g
many times to evaluate the jacobian at different points as it solves
the problem.
Therefore, the first time that Ipopt calls eval_jac_g it will be to
retrieve the sparsity structure. For this purpose, it does not need
any values, it just wants to know where the non-zeros will be so it
can reserve the appropriate memory and data structures. Therefore,
when you give Ipopt the sparsity structure, you should include every
(i,j) that may ever have a nonzero value, even if they may be zero at
the initial point. For this call, Ipopt will have valid pointers for
iRow and jCol, but NULL for x since it does not care about the actual
values of the jacobian, but only the structure.
The second time (and every time thereafter) that Ipopt calls
eval_jac_g, it will be to retrieve the values of the jacobian at a
particular point x. Here, Ipopt will give NULL pointers for iRow and
jCol, but a valid pointer in x. During these calls, return the
derivatives in the "values" array using the same order that you
specified iRow/jCol in the first call.
I hope this helps,
Cheers,
Carl.
2008/2/27 ZhangWeizhong <greatzwz at hotmail.com>:
>
> Hi, anyone can help me about my problem?
>
> For eval_jac_g(Index n, const Number* x, bool new_x, Index m, Index
nele_jac, Index* iRow, Index *jCol, number* values ).
> In IPOPT manual p21
> " If iRow and jCol arguments are not NULL, then IPOPT wants your to fill
in the sparsity structure of the Jacobian(the row and column indices only).
At this time, the x argument and the values argument will be NULL"
>
> I do not understand the following two questions according to the manual
p21.
> How can x be null at any situation? The values are the nonzero elements
in the jacobian of the constraint functions, how can be null when we specify
the locations of the nonzero elements?
>
> Thank you.
>
>
> The attachment is the results from my running program.
>
>
>
> I used "derivative checker" to run my program, the result is in the
following:
> "......
> * jac_g [ 96, 151] = 0.0000000000000000e+00 ~
1.8756734988301105e+03 [ 1.000e+00]
> * jac_g [ 98, 151] = 0.0000000000000000e+00 ~
1.9164490083767305e+03 [ 1.000e+00]
> * jac_g [ 100, 151] = 0.0000000000000000e+00 ~
1.9572245150811796e+03 [ 1.000e+00]
>
> Derivative checker detected 935 error(s).
>
> Number of nonzeros in equality constraint Jacobian...: 1000
> Number of nonzeros in inequality constraint Jacobian.: 0
> Number of nonzeros in Lagrangian Hessian.............: 0
>
> *** Error from MA27AD *** IFLAG = 1 IERROR = 958
> The index of a matrix is out of range.
> Please check your implementation of the Jabobian and Hessian
matrices.Exception of type: FATAL_ERROR_IN_LINEAR_SOLVER in file
"IpStdAugSystemSolver.cpp" at line 219:
> Exception message: A fatal error occured in the linear solver.
>
> EXIT: Some uncaught Ipopt exception encountered.
>
>
> *** The problem FAILED!"
>
> By valgrind:
> ==20844== 128199 errors in context 40 of 40:
> ==20844== Conditional jump or move depends on uninitialised value(s)
>
>
>
> ----------------------------------------
> > From: ipopt-request at list.coin-or.org
> > Subject: Ipopt Digest, Vol 38, Issue 14
> > To: ipopt at list.coin-or.org
> > Date: Wed, 27 Feb 2008 12:00:02 -0500
> >
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> > Today's Topics:
> >
> > 1. Re: Ipopt Digest, Vol 38, Issue 8 (ZhangWeizhong)
> >
> >
> > ----------------------------------------------------------------------
> >
> > Message: 1
> > Date: Tue, 26 Feb 2008 16:51:45 -0500
> > From: ZhangWeizhong
> > Subject: Re: [Ipopt] Ipopt Digest, Vol 38, Issue 8
> > To: ZhangWeizhong
> > Cc: ipopt at list.coin-or.org
> > Message-ID:
> > Content-Type: text/plain; charset="gb2312"
> >
> >
> > Hi,all:
> > Do we must supply "values" in eval_jac_g manually because IPOPT
can not provide these automatically?
> > It seems that we do not have to provide the values(just index of
the jacobian matrix is fine) to NAG.
> > The two differences between NAG and IPOPT now for me are
> > 1. IPOPT needs to be provided with the derivative of the
objective function, which is not required in NAG.
> > 2. IPOPT needs to be provided with the jacobian of the
constraints manually, in NAG, just the structure of the jacobian is needed.
> > Am I right for these?
> > Thank you.
> > Weizhong Zhang
> >
> >
> > ----------------------------------------
> >> From: greatzwz at hotmail.com
> >> To: stefan at math.hu-berlin.de
> >> Subject: RE: [Ipopt] Ipopt Digest, Vol 38, Issue 8
> >> Date: Tue, 26 Feb 2008 15:21:14 -0500
> >>
> >>
> >> Hi,Stefan:
> >> Thank you so much for your help.
> >> I think now I may know where the problem is.
> >> It is in
> >> eval_jac_g(Index n, const Number* x, bool new_x, Index m, Index
nele_jac, Index* iRow, Index *jCol, Number* values).
> >>
> >> I have supplied iRow, jCol, but the values for the Jacobian of
the constraints at the point x were not provided, I assumed it will be zero
which is defined as the same as in NAG.
> >>
> >> I will check that, thank you so much.
> >> Weizhong Zhang
> >>
> >>
> >>
> >>
> >>
> >> ----------------------------------------
> >>> Date: Tue, 26 Feb 2008 20:37:23 +0100
> >>> From: stefan at math.hu-berlin.de
> >>> To: ipopt at list.coin-or.org
> >>> CC: greatzwz at hotmail.com
> >>> Subject: Re: [Ipopt] Ipopt Digest, Vol 38, Issue 8
> >>>
> >>> Hi,
> >>>
> >>> ZhangWeizhong wrote:
> >>>> hI, all: Now the problem is " Invalid number in NLP function or
derivative detected" And number of iteration is "0" Can anyone give
me any suggestions?
> >>>
> >>> Probably your code that computes function values and jacobian returns
an
> >>> invalid number.
> >>> From the valgrind message you send I would guess that you might not
set
> >>> all values in the arrays that Ipopt provides you when it asks for a
> >>> function or jacobian evaluation.
> >>>
> >>> You should make sure that you implemented the evaluation routines
> >>> eval_f, eval_grad_f, eval_g, and eval_jac_g such that you return
correct
> >>> numbers in obj_value, grad_f, g, and values, repectively.
> >>> E.g., in the eval_jac_g routine make sure that you have set all
nele_jac
> >>> entries of values and did not leave some out.
> >>> Also you should not assume that values array is initialized with
0'th.
> >>>
> >>> Adding some printf's in your evaluation routines that tell which
values
> >>> you return to Ipopt should help to find the problem.
> >>>
> >>> (Andreas, you could make this error message a bit clearer by at least
> >>> telling whether it was a function value or a gradient :-).)
> >>>
> >>> Best,
> >>> Stefan
> >>>
> >>>
> >>> --
> >>> Stefan Vigerske
> >>> Humboldt University Berlin, Numerical Mathematics
> >>> http://www.math.hu-berlin.de/~stefan
> >>
> >> _________________________________________________________________
> >> ????? MSN ??????????
> >> http://mobile.msn.com.cn/
> >
> > _________________________________________________________________
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> >
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> > End of Ipopt Digest, Vol 38, Issue 14
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--
Carl D. Laird
Assistant Professor,
Artie McFerrin Department of Chemical Engineering,
Texas A&M University
Ph: (979) 458-4514
Email: carl.laird at tamu.edu
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