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Week 9 Quiz 5:
1. In a _______ integer model, some solution values for decision variables are integer and others can be non-integer.
a. total b. 0 – 1 c. mixed d. all of the above
2. In a total integer model, some solution values for decision variables are integer and others can be non-integer. TRUE/FALSE
3. In a problem involving capital budgeting applications, the 0-1 variables designate the acceptance or rejection of the different projects. TRUE/FALSE
4. If a maximization linear programming problem consist of all less-than-or-equal-to constraints with all positive coefficients and the objective function consists of all positive objective function coefficients, then rounding down the linear programming optimal solution values of the decision variables will ______ result in a(n) _____ solution to the integer linear programming problem.
A) always, optimal
B) always, non-optimal
C) never, non-optimal
D) sometimes, optimal
E) never, optimal
5. The branch and bound method of solving linear integer programming problems is an enumeration method. TRUE/FALSE
6. In a mixed integer model, all decision variables have integer solution values.
TRUE/FALSE
7. For a maximization integer linear programming problem, feasible solution is ensured by rounding _______ non-integer solution values if all of the constraints are less-than -or equal- to type.
A) up and down
B) up
C) down
D) up or down
8. In a total integer model, all decision variables have integer solution values. TRUE/FALSE
9. The 3 types of integer programming models are total, 0 - 1, and mixed. TRUE/FALSE
10. The branch and bound method of solving linear integer programming problems is _______.
A) an integer method
B) a relaxation method
C) a graphical solution
D) an enumeration method
11. The linear programming relaxation contains the _______ and the original constraints of the integer programming problem, but drops all integer
1. In a _______ integer model, some solution values for decision variables are integer and others can be non-integer.
a. total b. 0 – 1 c. mixed d. all of the above
2. In a total integer model, some solution values for decision variables are integer and others can be non-integer. TRUE/FALSE
3. In a problem involving capital budgeting applications, the 0-1 variables designate the acceptance or rejection of the different projects. TRUE/FALSE
4. If a maximization linear programming problem consist of all less-than-or-equal-to constraints with all positive coefficients and the objective function consists of all positive objective function coefficients, then rounding down the linear programming optimal solution values of the decision variables will ______ result in a(n) _____ solution to the integer linear programming problem.
A) always, optimal
B) always, non-optimal
C) never, non-optimal
D) sometimes, optimal
E) never, optimal
5. The branch and bound method of solving linear integer programming problems is an enumeration method. TRUE/FALSE
6. In a mixed integer model, all decision variables have integer solution values.
TRUE/FALSE
7. For a maximization integer linear programming problem, feasible solution is ensured by rounding _______ non-integer solution values if all of the constraints are less-than -or equal- to type.
A) up and down
B) up
C) down
D) up or down
8. In a total integer model, all decision variables have integer solution values. TRUE/FALSE
9. The 3 types of integer programming models are total, 0 - 1, and mixed. TRUE/FALSE
10. The branch and bound method of solving linear integer programming problems is _______.
A) an integer method
B) a relaxation method
C) a graphical solution
D) an enumeration method
11. The linear programming relaxation contains the _______ and the original constraints of the integer programming problem, but drops all integer