[Cbc] [CBC] Solving partially fixed MIP problem iteratively do not converge to best

[mg]

Hi John,
thanks for the fast reply.

Attached you can find a zip containing a piece of code that reproduce the
problem.
Basically int the main function I load the problem from model.lp file then
apply the strategy described in the previous mail.

The main assumptions for this strategy are:

- I know a set of variables (variables2workon array in the code) that I can
set to 1 to get a feasible (even if not really good) solution.
- Then, iteratively I try to set one of those variable to zero and resolve
the forced problem until I don't get any further improvement.
- Since those variables are in the objective function with a quite
important cost, if we reduce the number of ones in this set, we arrive
really close to the optimum.


If we solve it fully (i.e not iteratively, by setting fullsolve=true in the
code) we get an obj=381.86216, while with the iterative approach we get
obj=383.118855

I hope I have been clear enough, anyway the code is commented and should be
pretty self-explanatory.

The version of CBC is the release 2.8.9.

Thanks,

Marco


2014-02-26 12:10 GMT+01:00 mg <giunto.cardanico at gmail.com>:

> Hi John,
> thanks for the fast reply.
>
> Attached you can find a small piece of code that reproduce the problem.
> Basically int the main function I load the problem from model.lp file then
> apply the strategy described in the previous mail.
>
> The main assumptions for this strategy are:
>
> - I know a set of variables (variables2workon array in the code) that I
> can set to 1 to get a feasible (even if not really good) solution.
> - Then, iteratively I try to set one of those variable to zero and resolve
> the forced problem until I don't get any further improvement.
> - Since those variables are in the objective function with a quite
> important cost, if we reduce the number of ones in this set, we arrive
> really close to the optimum.
>
>
> If we solve it fully (i.e not iteratively, by setting fullsolve=true in
> the code) we get an obj=381.86216, while with the iterative approach we get
> obj=383.118855
>
> I hope I have been clear enough, anyway the code is commented and should
> be pretty self-explanatory.
>
> Thanks,
>
> Marco
>
>
>
>
> Anyway, the code should be commented enough.
>
>
>
>
>
>
>
> 2014-02-25 16:51 GMT+01:00 John Forrest <john.forrest at fastercoin.com>:
>
>>  Marco,
>>
>>
>> On 25/02/14 14:22, mg wrote:
>>
>>
>>
>>  I suspect that restoring only the column bounds between each
>> intermediate solve is not enough to guarantee that the problem remains
>> equal to the original...
>> should I also remove the cuts added during the intermediate steps ?
>>
>>
>> Any cuts generated will be invalid - but they may be removed anyway.
>>
>>  Something else ?
>>
>> Very likely.
>>
>> I can try and code something to reproduce problem - if you have some code
>> you can send me then I would be more likely to get around to checking
>> things out.
>>
>>  Thanks in advance,
>> Marco
>>
>>   John Forrest
>>
>>
>> _______________________________________________
>> Cbc mailing list
>> Cbc at list.coin-or.org
>> http://list.coin-or.org/mailman/listinfo/cbc
>>
>>
>
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