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INTEGER PROGRAMMING
1.
In a mixed integer model, some solution values for decision variables are integer and others
can be noninteger.
True: In mixed integer model values for some decision variables must be integer and for
others it can be noninteger and that is why it called as mixed integer model.
2.
In a total integer model, some solution values for decision variables are integer and others
can be noninteger.
False: In total integer model, solution values of all decision variables must be integer.
3.
The branch and bound method can only be used for maximization integer programming
problems.
4.
The solution value (Z)
to the linear programming relaxation of a maximization problem
will
always be less than or equal to the optimal solution value (Z) of the integer programming
maximization problem.
False: Incase of maximization problem, the solution value to the relaxation problem will
always be greater than or equal to solution value for integer program.
5.
In a 01 integer programming problem involving a capital budgeting application where x
j
= 1,
if project j is selected, x
j
= 0, otherwise, the constraint x
1
– x
2
= 0 implies that if project 2 is
selected, project 1 can not be selected.
False: If project 2 is selected, which means x
2
= 1 and x
1
– 1 = 0. In this case to satisfy the
equality x
1
must be equal to 1 and project 1 must be selected.
6. Rounding noninteger solution values up to the nearest integer value will still result in a
feasible solution to an integer programming problem.
False: By rounding noninteger solution values to nearest integer value, the solution can
be infeasible.
7.
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This note was uploaded on 09/08/2009 for the course MATH 540 taught by Professor Gist during the Spring '09 term at Strayer.
 Spring '09
 GIST
 Math

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