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| 1 | |
A two variable linear programming problem cannot be solved by the simplex method. |
| | A) | True |
| | B) | False |
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| 2 | |
A two variable linear programming problem can only be solved by the simplex method. |
| | A) | True |
| | B) | False |
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| 3 | |
If the sale of first 10 units of a product gives a profit of $10.00 per unit and every additional unit sold gives a profit of $15.00 per unit, the situation can not be modeled easily as a linear program. |
| | A) | True |
| | B) | False |
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| 4 | |
SUMPRODUCT command of excel can be used for multiplying elements of two arrays of unequal lengths, though it is usually used for arrays of equal length. |
| | A) | True |
| | B) | False |
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| 5 | |
In using Solver package for solving a linear programming problem, the decision variables are assigned to ____ cells. |
| | A) | target |
| | B) | changing |
| | C) | constraint |
| | D) | variable |
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| 6 | |
In using Solver package for solving a linear programming problem, the objective function expression and its value is defined in ____ cells. |
| | A) | target |
| | B) | changing |
| | C) | constraint |
| | D) | variable |
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| 7 | |
Problem A is a given formulation of a linear program with an optimal solution. Problem B is a formulation obtained by multiplying the objective function of Problem A by a positive constant and leaving all other things unchanged. Problems A and B will have |
| | A) | the same optimal solution and same objective function value. |
| | B) | the same optimal solution but different objective function values. |
| | C) | different optimal solutions but same objective function value. |
| | D) | different optimal solutions and different objective function values. |
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| 8 | |
Problem A is a given formulation of a linear program with an optimal solution. Problem B is a formulation obtained by adding a constant to the objective function of Problem A and leaving all other things unchanged. Problems A and B will have |
| | A) | the same optimal solution and same objective function value. |
| | B) | the same optimal solution but different objective function values. |
| | C) | different optimal solutions but same objective function value. |
| | D) | different optimal solutions and different objective function values. |
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| 9 | |
Problem A is a given formulation of a linear program with an optimal solution and its constraint 1 is ≤ type. Problem B is a formulation obtained from Problem A by replacing the ≤ constraint by an equality constraint and leaving all other things unchanged. Problems A and B will have |
| | A) | the same optimal solution and same objective function value. |
| | B) | the same optimal solution but different objective function values. |
| | C) | different optimal solutions but same objective function value. |
| | D) | same or different solution profile depending on the role of the constraints in the solutions. |
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| 10 | |
In formulating a coffee blending problem, where there are three types of coffee beans and the objective is to find a recipe to make 1 pound of blended coffee that satisfies a set of properties at least cost. The decision variables are X1, X2, X3 representing pounds (actually fractional pounds) of coffee beans used per pound of blended coffee. One of the constraints of the problem will be |
| | A) | X1 + X2 + X3 < 1.0. |
| | B) | X1 + X2 + X3 > 1.0. |
| | C) | X1 + X2 + X3 = 1.0. |
| | D) | no such constraint is required |
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| 11 | |
In formulating a coffee blending problem, where there are three types of coffee beans and the objective is to find a recipe to make 1 pound of blended coffee that satisfies a set of properties at least cost. The decision variables are X1, X2, X3 representing pounds (actually fractional pounds) of coffee beans used per pound of blended coffee. Suppose that bitterness is a property measured as an index from 1 to 6, and that the bitterness of a blend is given by the weighted average (using the weight fraction of each beans in the blend as the weight) of the bitterness of individual beans going into the blend. Suppose that the bitterness indexes for the three beans are respectively 2, 4 and 5. It is desired to have blend with bitterness in the range 3 to 4.5. The appropriate constraint/s will be: |
| | A) | 2X1 + 4X2 + 5X3 ≥ 3.0. |
| | B) | 2X1 + 4X2 + 5X3 ≤ 4.5. |
| | C) | 2X1 + 4X2 + 5X3 ≥ 3.0 and 2X1 + 4X2 + 5X3 ≤ 4.5. |
| | D) | The constraints are not correct since weights are not correctly represented. |
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| 12 | |
In formulating a coffee blending problem, where there are three types of coffee beans and the objective is to find a recipe to make 1 pound of blended coffee that satisfies a set of properties at least cost. The decision variables are X1, X2, X3 representing pounds (actually fractional pounds) of coffee beans used per pound of blended coffee. Suppose that it is required to produce 200 pounds of coffee using this formulation. the appropriate constraint/s given the definition of the problem and decision variables will be: |
| | A) | X1 + X2 + X3 = 200. |
| | B) | 200X1 + 200X2 + 200X3 > 200. |
| | C) | 200X1 + 200X2 + 200X3 < 200. |
| | D) | X1 + X2 + X3 = 1.0 and multiply the answer by 200 to blend 200 pounds. |
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