Chapter 07 – Using Binary Integer Programming to Deal with Yes-or-No Decisions
True / False Questions
1. Binary integer programming problems are those where all the decision variables restricted
to integer values are further restricted to be binary variables.
2. Binary variables are variables whose only possible values are 0 or 1.
3. Variables whose only possible values are 0 and 1 are called integer variables.
4. A problems where all the variables are binary variables is called a pure BIP problem.
5. Binary variables are best suited to be the decision variables when dealing with yes-or-no
decisions.
6. A BIP problem considers one yes-or-no decision at a time with the objective of choosing
the best alternative.
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7. The algorithms available for solving BIP problems are much more efficient than those for
linear programming which is one of the advantages of formulating problems this way.
8. If choosing one alternative from a group excludes choosing all of the others then these
alternatives are called mutually exclusive.
9. The constraint x1 + x2 + x3 3 in a BIP represents mutually exclusive alternatives.
10. It is possible to have a constraint in a BIP that excludes the possibility of choosing none of
the alternatives available.
11. A yes-or-no decision is a mutually exclusive decision if it can be yes only if a certain
other yes-or-no decision is yes.
12. The constraint x1 x2 in a BIP problem means that alternative 2 cannot be selected unless
alternative 1 is also selected.
13. BIP can be used in capital budgeting decisions to determine whether to invest a certain
amount.
Chapter 07 – Using Binary Integer Programming to Deal with Yes-or-No Decisions
14. BIP can be used to determine the timing of activities.
15. An auxiliary binary variable is an additional binary variable that is introduced into a
model to represent additional yes-or-no decisions.
16. A linear programming formulation is not valid for a product mix problem when there are
setup costs for initiating production.
17. The Excel sensitivity report can be used to perform sensitivity analysis for integer
programming problems.
18. Solver Table can be used to perform sensitivity analysis for integer programming
problems.
Multiple Choice Questions
19. Binary integer programming problems can answer which types of questions?
