1
OSCM 230
MIDTERM EXAM A (Key)
SPRING 2011
PROFESSOR DONG
1 Hour and 20 Minutes
Question
Score
True/False (10 pts)
Multiple Choice(10 pts)
1.
Excel
(10 pts)
2.
LP Formulation
(18 pts)
3.
LP Formulation
(12 pts)
4. Integer LP Formulation
(15 pts)
5. Sensitivity)
(25 pts)
Bonus
(2 pts)
Total
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2
True/False (10 pts)
1.
As long as a solution satisfies one constraint in a linear programming problem it is called a feasible
solution of the problem.
True
False
2.
A nice property of the quadratic programming model is that the local maximal is also the global
maximal.
True
False
3.
For a cost minimization integer linear programming problem, the objective function value of its LP
relaxation always provides a lower bound on the objective function value of the original problem.
True
False
4.
A convex programming model should have an objective of maximizing the value of a convex
function.
True
False
5.
In LP, if the change of the right hand side constant is within the allowable range for that constraint,
then the optimal solution will not change.
True
False
Multiple choices (10 pts)
1.
In a quadratic programming model with
n
decision variables, (
x
1
, x
2
, …, x
n
), the objective function
cannot
include terms of the form
:
a.
2
j
x
b.
i
j
x x
c.
2
i
j
x x
d.
3
2. What should we do if Solver’s message is “Solver could not find a feasible solution”?
a.
Check objective function to see if “MAX” should be “MIN,” or “MIN” should be “MAX”
b.
Check if we miss any constraints
c.
Check if we have too many constraints or conflicting constraints
d.
Check if we define too many decision variables