Because the auxiliary variable y must be either 0 or 1, this formulation guarantees that
one of the original constraints must hold while the other is, in effect, eliminated. This new
set of constraints would then be appended to the other constraints in the overall model to
give a pure or mixed IP problem (depending upon whether the xj are integer or continuous
variables).
This approach is related directly to our earlier discussion about expressing combinatorial
relationships in terms of questions that must be answered yes or no. The combinatorial
relationship involved concerns the combination of the other constraints of the model
with the first of the two alternative constraints and then with the second. Which of these
two combinations of constraints is better (in terms of the value of the objective function
that then can be achieved)? To rephrase this question in yes-or-no terms, we ask two complementary
questions:
1. Should x1 4x2 16 be selected as the constraint that must hold?
2. Should 3x1 2x2 18 be selected as the constraint that must hold?
Because exactly one of these questions is to be answered affirmatively, we let the binary
terms y and 1 y, respectively, represent these yes-or-no decisions. Thus, y 1 if the answer is yes to the first question (and no to the second), whereas 1 y 1 (that is, y 0)
if the answer is yes to the second question (and no to the first). Since y 1 y 1 (one
yes) automatically, there is no need to add another constraint to force these two decisions
to be mutually exclusive. (If separate binary variables y1 and y2 had been used instead to
represent these yes-or-no decisions, then an additional constraint y1 y2 1 would have
been needed to make them mutually exclusive.)
A formal presentation of this approach is given next for a more general case.