[Couenne] Lower/Upper bounds variables

[Luca Mencarelli]

Dear Pietro,

Thanks for the answer. Yes, I agree with you. Maybe I didn't explain
myself well,
but the point is that I will like to retrieve the values corresponding to
-283,
since I'm developing a feasibility recovering heuristic based on the DUAL
bound.

Best,
Luca

-- 
Luca Mencarelli
PhD Candidate at LIX, Ecole Polytechnique
91128 Palaiseau CEDEX, France
Office: 2072 (Bâtiment Alan Turing, second floor)
LIX e-mail address: mencarelli at lix.polytechnique.fr
INRIA e-mail address:  luca.mencarelli at inria.fr


> Dear Luca,
>
> I tried the following AMPL script:
>
> model nonlinear_w_cont.mod
> data mnck_instance_0.dat
> write gdis;
> option solver couenne;
> solve;
> display sigmoid_p;
>
> The output I get from the script shows a DUAL bound of -283 and a
> PRiMAL bound of -214 when stopping couenne after 20 seconds. The dual
> bound does not refer to a solution as it is simply a lower bound on
> the optimal solution. The primal bound instead refers to a feasible
> solution. Indeed when printing the only variables appearing in the
> objective, their sum seems roughly equal to 214.
>
> Since Couenne generally refers to minimization problems, the lower
> bound is the dual bound and the upper bound the primal one. in the
> case of a maximization (which you correctly reformulate as a min
> problem) the upper bound is a dual and the lower bound is a primal
> bound. Hence Couenne reports the solution found that refers to the
> primal bound.
>
> When re-running Couenne on the dis.nl saved by the script, the same
> thing happens, then the dis.sol file contains, from lines 39 onward,
> the same solution found by the script, which again sums up to about
> 214. I'm running stable/0.4, but it really seems like I can't
> reproduce your problem. What solution are you getting?
>
> Regards,
> Pietro
>
>
>
>
>
> On Wed, Jun 3, 2015 at 5:23 PM, Luca Mencarelli
> <mencarelli at lix.polytechnique.fr> wrote:
>> Dear Pietro,
>>
>> I've done other experiments with the code, but I cannot retrieve
>> the values of the decision variables corresponding to the Upper Bound
>> provided by Couenne.
>>
>> Thanks very much. Best regards,
>> Luca
>>
>>> Dear Pietro,
>>>
>>> I attach the model and the output files. I get an upper_bound =
>>> -210.89,
>>> while the upper bound provided by Couenne (version 0.4.8) is -286.95.
>>> The original problem is a maximization one.
>>>
>>> Thanks again. Best,
>>> Luca
>>>
>>> --
>>> Luca Mencarelli
>>> PhD Candidate at LIX, Ecole Polytechnique
>>> 91128 Palaiseau CEDEX, France
>>> Office: 2072 (Bâtiment Alan Turing, second floor)
>>> LIX e-mail address: mencarelli at lix.polytechnique.fr
>>> INRIA e-mail address:  luca.mencarelli at inria.fr
>>>
>>>
>>>
>>>> Hi Luca,
>>>>
>>>> this should not happen, it might be a bug. Can you send me the model
>>>> (a .nl file should suffice)? I suspect the constant term of the
>>>> objective function might be ignored. Also, what version of Couenne are
>>>> you using?
>>>>
>>>> Pietro
>>>>
>>>> On Mon, May 18, 2015 at 4:55 PM, Luca Mencarelli
>>>> <mencarelli at lix.polytechnique.fr> wrote:
>>>>> Dear Pietro,
>>>>>
>>>>> First of thanks very much for the answer. However in the .sol file I
>>>>> found
>>>>> the same values as the one I obtain via the display command. But when
>>>>> I
>>>>> recompute
>>>>> the objective function with these values, it is less than the upper
>>>>> bound
>>>>> provided
>>>>> by Couenne.
>>>>>
>>>>> Best,
>>>>> Luca
>>>>>
>>>>> --
>>>>>
>>>>> Luca Mencarelli
>>>>> PhD Candidate at LIX, Ecole Polytechnique
>>>>> 91128 Palaiseau CEDEX, France
>>>>> Office: 2072 (Bâtiment Alan Turing, second floor)
>>>>> LIX e-mail address: mencarelli at lix.polytechnique.fr
>>>>> INRIA e-mail address:  luca.mencarelli at inria.fr
>>>>>
>>>>>
>>>>>
>>>>>> Hi Luca,
>>>>>>
>>>>>> when Couenne stops before closing the gap, the best feasible MINLP
>>>>>> solution found (if any) is saved in a file with the same name as the
>>>>>> input file but with extension .sol (which is the format read by
>>>>>> AMPL).
>>>>>> So the answer is yes for the upper bound if at least one solution is
>>>>>> found.
>>>>>>
>>>>>> However, this does not make much sense for the lower bound, given
>>>>>> that
>>>>>> it's obtained by a relaxation of the MINLP (and would hence be
>>>>>> infeasible) and is related to the whole branch-and-bound search tree
>>>>>> rather than a specific subproblem. Hence no solution is available
>>>>>> for
>>>>>> the lower bound.
>>>>>>
>>>>>> Hope this helps,
>>>>>> Pietro
>>>>>>
>>>>>>
>>>>>> On Mon, May 18, 2015 at 11:05 AM, Luca Mencarelli
>>>>>> <mencarelli at lix.polytechnique.fr> wrote:
>>>>>>> Hi,
>>>>>>>
>>>>>>> If Couenne did not succeed in solving a problem to optimality, it's
>>>>>>> possible to
>>>>>>> retrieve the values of the decision variables corresponding to the
>>>>>>> lower
>>>>>>> and to
>>>>>>> the upper bounds provided by the solver?
>>>>>>>
>>>>>>> Thanks. Best,
>>>>>>> Luca
>>>>>>>
>>>>>>> --
>>>>>>> Luca Mencarelli
>>>>>>> PhD Candidate at LIX, Ecole Polytechnique
>>>>>>> 91128 Palaiseau CEDEX, France
>>>>>>> Office: 2072 (Bâtiment Alan Turing, second floor)
>>>>>>> E-mail address: mencarelli at lix.polytechnique.fr
>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>>
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>>>>>>> Couenne mailing list
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>>>>>>> http://list.coin-or.org/mailman/listinfo/couenne
>>>>>>
>>>>>
>>>>>
>>>>
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>>
>