[Ipopt] Lagrange multipliers for inequality (<=) constraints

[Chunhua Men]

Hi Stefan,

Thanks for your response. I think I still miss something.... I have asked a
question several months ago: all my constraints were inequality (<=) and I
wondered why I got negative "lambda" in "finalize_solution". Then I was
told that IPOPT treats all constraints as equalities with slacks...
However, in this email, I was told ip_data refer to the equality
constraints (+ slack variables), and "lambda" refer my
original inequalities (<=)?

Thanks again, Chunhua



On Mon, Nov 7, 2016 at 6:01 AM, Stefan Vigerske <stefan at math.hu-berlin.de>
wrote:

> Hi,
>
> you should read lambda directly.
> ip_data should refer to the internal representation of your problem, where
> inequality constraints have been reformulated to equality constraints (+
> slack variables), so it might not be obvious what y_c() or y_d() mean.
> You can have a look at the documentation of intermediate_callback to get
> some idea how to bring y_c() and y_d() into the TNLP space:
> http://www.coin-or.org/Ipopt/documentation/node23.html#SECTI
> ON00053410000000000000
>
> Hope that helps,
> Stefan
>
>
> On 10/28/2016 12:44 AM, Chunhua Men wrote:
>
>> Hello,
>>
>> I have a convex model with some inequality (<=)  nonlinear constraints. At
>> the end of the optimization,  I wanted to get the Lagrange multipliers for
>> each constraint. I found out there were 2 ways within
>> "finalize_solution(...)" to get them:
>> 1) read "lambda" directly;
>> 2) get from ip_data->curr()->y_d(). And I had to do some data transfer to
>> get it -  and what I did was "static_cast<const
>> Ipopt::DenseVector*>(GetRawPtr(ip_data->curr()->y_c()))".
>>
>> However, these 2 methods could not give me the completely same results. In
>> my case, there were 6 constraints: 3 of them were the same, and 3 of them
>> were not.
>>
>> Did I do anything wrong? and what is the best way to get Lagrange
>> multipliers?  BTW, I am using " limited-memory" as
>> "hessian_approximation",
>> so I could not get Lagrange multipliers from "eval_h".
>>
>> Thanks! Chunhua
>>
>>
>>
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>
> --
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