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Re: Solver delivers wrong answer when 2 constraints are close


From: Antti Lehtila
Subject: Re: Solver delivers wrong answer when 2 constraints are close
Date: Thu, 4 Mar 2021 17:44:07 +0200
User-agent: Mozilla/5.0 (Windows NT 6.1; WOW64; rv:60.0) Gecko/20100101 Thunderbird/60.9.1

Hi,

I think it works fully as documented, and so *per design*. Singleton rows are treated as column bounds by the preprocessor. See documentation for *npp_implied_lower*:
*---------------
*  Processing implied column lower bound l'[q] includes the following
*  cases:
*
*  1) if l'[q] < l[q] + eps, implied lower bound is redundant;
*
*  2) if l[q] + eps <= l[q] <= u[q] + eps, current column lower bound
*     l[q] can be strengthened by replacing it with l'[q]. If in this
*     case new column lower bound becomes close to current column upper
*     bound u[q], the column can be fixed on its upper bound;
*
*  3) if l'[q] > u[q] + eps, implied lower bound violates current
*     column upper bound u[q], in which case the problem has no primal
*     feasible solution. */
*---------------
The lower bound can have only a single value, but if you define multiple values for a column lower bound, they must of course be processed in some order.  In this case, the lower bound is first defined l(q)=0, then l'(q)=1, and finally l'(q)=1.0001. The third value for the bound is thus considered *redundant*, as per design, and so the second value l(q)=1 remains in effect. This is because *eps* is defined as 1e-3 + 1e-6 * fabs(q->lb)).

I guess it may be a considered a design flaw, but I think it should not be called a bug, as it is working as designed and documented.  Besides, I think one should use the Bounds section for bounds, instead of using multiple constraints for defining a single lower bound.

Best,
Antti
_______________________
On 04.03.2021 11:38, Domingo Alvarez Duarte wrote:

Testing this problem I discover that if we change the order of constraint declarations it seems to give the expected answer as stated by Thiago (what I think could be another bug).

====

/param min_bound default 0;/
/var x >= 0;

minimize y: x;/
*
*/*s.t. PART_MIN_X: x >= 1 + min_bound;*
/
/*s.t. LIM_INF_X: x >= 1;
*
/
/solve;
display min_bound;
display x; # EXPECTED RESULT: X ==  1.0001

data;
param min_bound := 1e-4;
end;/

====

Output:

====

x.val = 1.0001

====

On 3/3/21 19:19, Thiago Neves wrote:
Hi.
I've found a strange behaviour in glpk which I don't know how to fix nor how to contour it. It seems like GLPK can't distinguish constraints that differs from about 1e-4.

Follows simple examples that explain and reproduce the problem.**
*
*
*The first model gives the desired answer (x = 1.0001):*
/
param min_bound default 0;/
/var x >= 0;

minimize y: x;/
/*
s.t. PART_MIN_X: x >= 1 + min_bound;*

solve;
display min_bound;
display x; # EXPECTED RESULT: X ==  1.0001

data;
param min_bound := 1e-4;
end;
/
/_____________________________________/
/OUTPUT:/
/x.val = 1.0001/
/_____________________________________ /

*Now, if I add a second constraint "close" to the first one, the solver will deliver an answer that is actually infeasible:*

/param min_bound default 0;/
/var x >= 0;

minimize y: x;/

*s.t. LIM_INF_X: x >= 1;

*/*s.t. PART_MIN_X: x >= 1 + min_bound;*

solve;
display min_bound;
display x; # EXPECTED RESULT: X ==  1.0001

data;
param min_bound := 1e-4;
end;/
/_____________________________________/
/OUTPUT:/
x.val = 1
/_____________________________________ /

*If I change the "min_bound" parameter to 1e-2, the second model works as expected (x = 1.01):*

/param min_bound default 0;/
/
/
/var x >= 0;

minimize y: x;/
*
*
*s.t. LIM_INF_X: x >= 1;

*/*s.t. PART_MIN_X: x >= 1 + min_bound;*

solve;/
/
display x; # EXPECTED RESULT: X ==  1.01

data;
param min_bound := 1e-2;
end;/
/_____________________________________/
/OUTPUT:/
x.val = 1.01
/_____________________________________ /
/
/

Att,

*Thiago H. Neves*
(31) 98608-0666





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