MULTIPLE CHOICE 1. An integrality condition indicates that some (or all) of the a. RHS values for constraints must be integer b. objective function coefficients must be integer c. constraint coefficients must be integer d. decision variables must be integer 2. Variables which are not required to assume strictly integer values are referred to as a. strictly non-integer. b. continuous. c. discrete. d. infinite. 3. One approach to solving integer programming problems is to ignore the integrality conditions and solve the problem with continuous decision variables. This is referred to as a. quickest solution method. b. LP satisficing. c. LP relaxation. d. LP approximation. 4. How is an LP problem changed into an ILP problem? a. by adding constraints that the decision variables be non-negative. b. by adding integrality conditions. c. by adding discontinuity constraints. d. by making the RHS values integer. 5. The LP relaxation of an ILP problem a. always encompasses all the feasible integer solutions to the original ILP problem. b. encompasses at least 90% of the feasible integer solutions to the original ILP problem. c. encompasses different set of feasible integer solutions to the original ILP problem. d. will not contain the feasible integer solutions to the original ILP problem. 6. The objective function value for the ILP problem can never a. be as good as the optimal solution to its LP relaxation. b. be as poor as the optimal solution to its LP relaxation. c. be worse than the optimal solution to its LP relaxation. d. be better than the optimal solution to its LP relaxation. 7. For maximization problems the optimal objective function value to the LP relaxation provides what for the optimal objective function value of the ILP problem? a. An upper bound. b. A lower bound. c. An alternative optimal solution. d. An additional constraint for the ILP problem. 8. For minimization problems the optimal objective function value to the LP relaxation provides what for the optimal objective function value of the ILP problem? a. An upper bound. b. A lower bound. c. An alternative optimal solution. d. An additional constraint for the ILP problem. 9. In the B & B algorithm B & B stands for a. Brooks and Baker b. Best Bound c. Best Branch d. Branch and Bound 10. The B & B algorithm solves ILP problems a. by solving for each variable separately. b. by solving for the integer variables first. c. by solving a series of LP problems. d. by solving smaller ILP problems.
