# 10 as long as the slope of the objective function

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10. As long as the slope of the objective function stays between the slopes of the binding constraints a. the value of the objective function won't change. b. there will be alternative optimal solutions. c. the values of the dual variables won't change. d. there will be no slack in the solution. ANS: C PTS: 1 TOP: Objective function
11. Infeasibility means that the number of solutions to the linear programming models that satisfies all constraints is PTS: 1 TOP: Alternate optimal solutions
12. A constraint that does not affect the feasible region is a PTS: 1 TOP: Feasible regions
13. Whenever all the constraints in a linear program are expressed as equalities, the linear program is said to be written in
PTS: 1 TOP: Slack variables
14. All of the following statements about a redundant constraint are correct EXCEPT a. A redundant constraint does not affect the optimal solution. b. A redundant constraint does not affect the feasible region. c. Recognizing a redundant constraint is easy with the graphical solution method. d. At the optimal solution, a redundant constraint will have zero slack. ANS: D PTS: 1 TOP: Slack variables
15. All linear programming problems have all of the following properties EXCEPT PTS: 1 TOP: Problem formulation
TRUE/FALSE 1. Increasing the right-hand side of a nonbinding constraint will not cause a change in the optimal solution. PTS: 1 TOP: Introduction
2. In a linear programming problem, the objective function and the constraints must be linear functions of the decision variables. PTS: 1 TOP: Mathematical statement of the RMC Problem
3. In a feasible problem, an equal-to constraint cannot be nonbinding. PTS: 1 TOP: Graphical solution
4. Only binding constraints form the shape (boundaries) of the feasible region. PTS: 1 TOP: Graphical solution
5. The constraint 5x 1 2x 2 0 passes through the point (20, 50). PTS: 1 TOP: Graphing lines
6. A redundant constraint is a binding constraint. PTS: 1 TOP: Slack variables
7. Because surplus variables represent the amount by which the solution exceeds a minimum target, they are given positive coefficients in the objective function. PTS: 1 TOP: Slack variables
8. Alternative optimal solutions occur when there is no feasible solution to the problem. PTS: 1 TOP: Alternative optimal solutions
9. A range of optimality is applicable only if the other coefficient remains at its original value.