Intelligent use of upper and lower bounds on variables can help make LINGO’s solution search as efficient as possible. Supplying good bounds can keep LINGO from wasting time searching regions unlikely to yield good solutions. For example, suppose you know that, even though the feasible range for a particular variable is between 1 and 100, it is highly improbable the optimal value is outside the range to 50 to 75. In this case, using the @BND function to specify a lower bound of 50 and an upper bound of 75 could significantly reduce solution times.

Bounding can also help keep the solution search clear of mathematically troublesome areas like undefined regions. For example, if you have a constraint with the term 1/X, it may be helpful to add a lower bound on X so it does not get close to 0.