There are set and get methods for tolerances, for example,
`double primalTolerance()` and
`setPrimalTolerance(double)`. Assuming that one has a
minimization problem, an individual variable is deemed primal feasible if it
is less than the tolerance referred to by these methods below its lower bound
and less than it above its upper bound. Similarly for dual tolerances, a
variable is deemed to be dual feasible if its reduced cost is greater than
minus the tolerance or its distance to the upper bound is less than primal
tolerance and the reduced cost is less than plus the tolerance or the distance
to lower bound is less than primal tolerance. In short, this is complementarity
conditions adadpted for tolerances and simple lower and upper bounds.(Note
that the above was stated as for minimization; signs are reversed for
maximization.)