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Dear Liding Xu,<br>
<br>
the lazy bound can (and often should) be equal to the upper bound of
a variable. But this is not what this assert ensures. This assert
should make sure that no upper bound for this variable is set in the
LP solver (third part of the assert) unless the upper bound of the
variable is lower than the lazy bound (second part; e.g., if in your
case a variable is fixed to 0) or SCIP is in diving mode (first
part; since diving mode can change the objective function, the lazy
bounds need to be ensured explicitly). What value does
"col->flushedub" have when the assert comes up?<br>
<br>
Best,<br>
Gerald<br>
<br>
<div class="moz-cite-prefix">Am 02.07.19 um 09:09 schrieb liding xu:<br>
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<div>Dear scip team,</div>
<div> I have a set of binary variables x_i such that they are
in constraint \sum_{i} x_i = 1. So I set lazy bound on x_i to
1.0. However, when a x_i becomes 1, the scip report error "
updateLazyBounds: Assertion `lp->divinglazyapplied ||
SCIPsetIsLT(set, col->ub, col->lazyub) ||
(col->flushedub == SCIPlpiInfinity(lp->lpi))' failed"
in file "src/scip/lp.c:12176:". <br>
</div>
<div> I test that because SCIPsetIsLT(set, col->ub,
col->lazyub) fails which is in my test case '1.0 < 1.0'.
Why the lazy bound cannot equal to the upper bound of binary
variable?</div>
<div><br>
</div>
<div>Best regards,</div>
<div>Liding XU<br>
</div>
<div> <br>
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