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MAT 540 Quiz 5
1. In using rounding of a linear programming model to obtain to obtain an integer solution the
solution is
Always optimal and feasible
Sometimes optimal and feasible
Always optimal
Always feasible
Never optimal and feasible
2. 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.
Up and down
Up
Down
Up or down
3. The 3 types of integer programming models are total, 0-1, and mixed
True
False
4. In a __________integer model, some solution values for decision variables are integer and
others can be non-integer
Total
0-1
Mixed
All of the above

2. 5. In a problem involving capital budgeting applications, the 0-1 variables designate the
acceptance or rejection of the different projects.
True
False
6. The solution value (Z) to the linear programming relaxation of a minimization problem will
always be less than or equal to the optimal solution value (Z) of the integer programming
minimization proble
True
False
7. If a maximization linear programming problem consist of all less-than-or-equal-to constraints
with all positive coefficient and the objective function consists of all positive objective function
coefficient, 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.
Always, optimal
Always, non-optimal
Never, non-optimal
Sometimes, optimal
Never, optimal
8. The implicit enumeration method
Generates an optimal integer solution when no new constraints can be added to the
relaxed linear programming model
Eliminates obviously infeasible solutions and evaluates the remaining solutions to
determine which one is optimal
Is used to solve a mixed integer linear programming model
Cannot be used to solve linear programming models with multiple infeasible solutions
9. In a total integer model, some solution values for decision variables are integer and others can
be non-integer
True
False

3. 10. The branch and bound method of solving linear integer programming problems is
___________.
An integer method
A relaxation method
A graphical solution
An enumeration method
11. The linear programming relaxation contains the __________and the original constraints of
the integer programming problem, but drops all integer restrictions.
Different variables
Slack values
Objective function
Decision variables
Surplus variables
12. The branch and bound method can only be used for maximization integer programming
problems.
True
False
13. In a mixed integer model, all decision variables have integer solution values.
True
False
14. The branch and bound method of solving linear integer programming problems is an
enumeration method.
True
False
15. In a 0-1 integer model, the solution values of the decision variables are 0 to 1
True
False

4. 16. Rounding small values of decision variables to the nearest integer value causes
_____________ problems than rounding large values.
Similar
More
Fewer
None of the above
17. In a mixed integer model, some solution values for decision variables are integer and others
can be non-integer.
True
False
18. Which of the following is not an integer linear programming proble?
Pure integer
Mixed integer
0.1 integer
Continuous
19. Types of integer programming models are ___________
Total
0-1
Mixed
All of the above
20. In a total integer model, all decision variables have integer solution values
True
False