Quiz 5

Which of the following equations represents the requirement of having to produce at least 5 chairs (C) for every table (T) produced? A) 5T ≤ C B) 5T ≥ C C) 5C ≤ T D) 5C ≥ T E) 5C - T ≥ 0

A) 5T ≤ C

In the LP problem with constraints 2X + Y ≤ 200, X + 2Y ≤ 200, and X, Y ≥ 0, which of the following (X,Y) points *cannot* be the optimal solution? A) (0,0) B) (0,200) C) (0,100) D) (100,0) E) Can't tell, depends on the Objective Function

B) (0,200); plug it in

If the optimum solution calls for mixing three-parts of X1 to two-parts of X2, then the mix is _____ of X1 and ______ of X2. A) 30%; 20% B) 60%; 40% C) 40%; 60% D) 2/5; 3/5 E) Both C and D

B) 60%; 40%

If one changes the contribution rates of the Decision Variables in the Objective Function of a LP problem, then _______. A) The feasible region will change B) The slope of the Isoprofit or Isocost line will change C) The optimal solution to the LP is sure to no longer be optimal D) All of the above E) None of the above

B) The slope of the Isoprofit or Isocost line will change

Consider the following LP problem: Maximize: 10X + 30Y Subject to: X + 2Y ≤ 80 8X + 16Y ≤ 640 4X + 2Y ≥ 100 X, Y ≥ 0 Which of the following is true? A) There is no feasible solution B) There is a redundant constraint C) There are multiple optimal solutions D) This problem can't be solved graphically E) None of the above

B) There is a redundant constraint

The simultaneous equation method is _____. A) An alternative to the corner point method B) Useful only in minimization methods C) An algebraic means for solving the intersection of two or more constraint equations D) Useful only when more than two product variables exist in a product mix problem E) None of the above

C) An algebraic means for solving the intersection of two or more constraint equations

Consider the following LP problem: Maximize: 5X + 6Y Subject to: 4x + 2y ≤ 420 1x + 2y ≤ 120 All variables ≥ 0 Which of the following (x,y) points is in the feasible region? A) (30,60) B) (105,5) C) (0,210) D) (100,10) E) None of the above

D) (100,10)

(T/F): Any linear programming problem can be solved using the graphical solution procedure

False

(T/F): In some instances, an infeasible solution may be the optimum found by the corner point method

False

(T/F): "Sensitivity Analysis", in Linear Programming, studies how much a coefficient of the Objective Function can change before causing a change in the solution

True

(T/F): Any time that the slope of the Objective Function is parallel to a constraint, it creates the possibility of multiple solutions

True

(T/F): In a linear programming problem, the "Feasible Region" is the set of solution points that satisfy all of the constraints simultaneousl.

True

(T/F): The solution to a Linear Programming problem must always lie on a constraint

True