Reference no: EM132258792
1. In using Excel® to solve linear programming problems, the objective cell represents the:
a. total cost of the model
b. decision variables
c. value of the objective function
d. constraints
2. In using Excel® to solve linear programming problems, the decision variable cells represent the:
a. value of the objective function
b. total cost of the model
c. constraints
d. decision variables
3. The additivity property of linear programming implies that the contribution of any decision variable to the objective is of/on the levels of the other decision variables.
a. the sum
b. dependent
c. conditional
d. independent
4. The divisibility property of linear programming means that a solution can have both:
a. linear and nonlinear relationships
b. positive and negative values
c. revenue and cost information in the model
d. integer and noninteger levels of an activity
5. Every linear programming problem involves optimizing a:
a. linear function subject to several linear constraints
b. linear regression model subject to several linear constraints
c. linear function subject to several non-linear constraints
d. non-linear function subject to several linear constraints
6. Which of the following statements about Integer Programming are true?
A) With integer programming, the feasible region becomes a collection of points.
B) IP and MILP are very similar, both force all decision variables to be integers.
C) An integer programming solution is usually better than a linear programming solution for the same problem.
D) Mass enumeration consists of finding the value of the objective function for each feasible solution.
E) Finding the optimal solution for an IP problem can be achieved by solving it as an LP problem and then round the solution to be an integer.
F) None of the above.