[SCIP] Issue with tolerance
Oliver Zier
ozier at MPA-Garching.MPG.DE
Thu Mar 12 09:41:30 CET 2020
Hi,
Thank you for your reply. SCIPlpiIsOptimal returns 0 which is not optimal
I think.
I am using a heuristic to add more columns to the model in scip_farkas and
exporting
the LP file using SCIPwriteTransProblem I checked again the LP optimal
solution from
scip and it is actually higher than the primal bound (current primal bound is
41.0857 but it is not optimal yet). But I thought that in this case it
would try to
run scip_redcost again? Can I use SCIPlpiGetInternalStatus to detect these
cases? I
can't find any documentation about the internal status.
Here is the log I got from lpinfo
CPXPARAM_Simplex_DGradient 2
CPXPARAM_Simplex_PGradient 2
CPXPARAM_Read_Scale 1
CPXPARAM_Simplex_Tolerances_Feasibility 1.0000000000000001e-05
CPXPARAM_TimeLimit 6987.626158
CPXPARAM_Barrier_ConvergeTol 1e-10
CPXPARAM_Simplex_DGradient 2
CPXPARAM_Simplex_PGradient 2
CPXPARAM_Read_Scale 1
CPXPARAM_Simplex_Tolerances_Feasibility 1.0000000000000001e-05
CPXPARAM_TimeLimit 6987.6253960000004
CPXPARAM_Barrier_ConvergeTol 1e-10
CPXPARAM_Simplex_DGradient 2
CPXPARAM_Simplex_PGradient 2
CPXPARAM_Read_Scale 1
CPXPARAM_Simplex_Tolerances_Feasibility 1.0000000000000001e-05
CPXPARAM_TimeLimit 6987.6248720000003
CPXPARAM_Barrier_ConvergeTol 1e-10
Reinitializing dual norms . . .
Iteration log . . .
Iteration: 1 Scaled dual infeas = 0.000000
Iteration: 2 Dual objective = -979.591133
Markowitz threshold set to 0.1
Iteration: 24 Dual objective = 50.110505
Removing shift (1).
CPXPARAM_Simplex_DGradient 2
CPXPARAM_Simplex_PGradient 2
CPXPARAM_Read_Scale 1
CPXPARAM_Simplex_Tolerances_Feasibility 1.0000000000000001e-05
CPXPARAM_TimeLimit 6987.6225100000001
CPXPARAM_Barrier_ConvergeTol 1e-10
Initializing dual steep norms . . .
In case if there is no way to force scip to start redcost again with my
heuristic
solution, I have been looking at the Farkas pricing. In the documentation,
it is
said that "PRICERFARKAS callback would call this function with a zero
objective
function and the Farkas vector" but shouldn't we try to maximize the
Farkas vector
and cut off if this is <= 0? I tried to implement Farkas with the max obj
function
but it doesn't seem to resolve the issue so I think my understanding of
this is
wrong.
Best,
Oliver
> Dear Oliver,
>
> it's really hard to say what is happening without more details. In
> general, the solving process in CPLEX when solving the LP within SCIP
> can be different to when running CPLEX alone, because within SCIP, CPLEX
> will restart from the basis of the last LP / LP at the parent node,
> tolerances might be different, some settings (presolving and scaling)
> might be different and so forth.
>
>
>> I am using SCIPlpiIsOptimal and SCIPlpiGetInternalStatus to check the LP
>> solver status when SCIP returns infeasible and I got sometimes
>>
>> for SCIPlpiIsOptimal and 1566399830 for SCIPlpiGetInternalStatus. What
>> is
>> SCIPlpiGetInternalStatus?
>
> SCIPlpiGetInternalStatus is the internal status code that the LP solver
> returned. What do you sometimes get for SCIPlpiIsoptimal? Is the LP
> really infeasible or was the cutoff bound reached, i.e., the LP was was
> above the primal bound, if you already found a solution? This is of
> course different to a stand-alone solve of the LP with CPLEX.
>
>
>> I am turning off these plugin in SCIP
>>
>> SCIP_CALL( SCIPsetIntParam(scip,"presolving/maxrestarts",0) );
>> SCIP_CALL( SCIPsetIntParam(scip,"propagating/rootredcost/freq",-1)
>> );
>> SCIP_CALL( SCIPsetIntParam(scip, "propagating/maxroundsroot", 0) );
>> SCIP_CALL( SCIPsetIntParam(scip, "separating/maxroundsroot", 0) );
>> SCIP_CALL( SCIPsetIntParam(scip, "separating/maxrounds", 0) );
>> SCIP_CALL( SCIPsetIntParam(scip, "presolving/maxrounds", 0) );
>> Is it enough or should I turn off something else? It would be great if
>> you
>> give me some idea how to debug this as CPLEX Studio returns an optimal
>> solution so I don't really have any idea what I should check? Thank you
>> in
>> advance
>
> That should be ok. In general, if you problem is numerically
> challenging, it may happen that you get different results with slightly
> different starting conditions or paramters. You could check the Farkas
> coefficients within PRICERFARKAS (which you will need to implement,
> anyway), which should give you a linear combination of the constraints
> that prove the infeasibility. So you might be able to verify the
> infeasibility or see whether the combination of constraints is perhaps
> slightly infeasible, so that you could claim both results within
> tolerances.
>
> By the way: How did you write the problem to an LP file?
>
> I would not turn off the primal and dual feasibility checks. They should
> make SCIP numerically more stable, because an LP solution that does not
> pass these checks is not accepted, but the LP is optimized again with
> different settings.
>
> By the way, to get some more info of what is happening within CPLEX, you
> might want to set display/lpinfo to TRUE and send the output to the list
> if it is not too long.
>
> Best,
> Gerald
>
>
>>
>> Best,
>>
>> Oliver
>>
>>
>>> Hi all,
>>>
>>> I am implementing branch and price using SCIP with Cplex as the LP
>>> solver.
>>> During pricing, I saw some instances in which SCIP returns that the
>>> problem is infeasible and enters Farkas. However when I exported the
>>> problem to an lp file and solved it with CPLEX studio, I got a feasible
>>> solution. I guessed this is because of tolerance so I was playing
>>> around
>>> with it but I can't find any numbers that work for all. I have some
>>> constraints with big M in model. Do you have any suggestions about what
>>> I
>>> should pay attention to? I am currently using
>>> SCIP_CALL( SCIPsetRealParam(scip, "numerics/feastol", 1e-5) );
>>> SCIP_CALL( SCIPsetRealParam(scip, "numerics/lpfeastol", 1e-6) );
>>> SCIP_CALL( SCIPsetRealParam(scip, "numerics/dualfeastol", 1e-5) );
>>> Also I tried to turn off lp/checkprimfeas and lp/checkdualfeas and it
>>> helps in some cases but I am not sure if it would cause any other
>>> issue.
>>> Would you recommend to use the feasibility check or not in this case?
>>>
>>> Best wishes,
>>> Oliver
>>>
>>>
>>>
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>>>
>>
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