Exam 5: What-If Analysis for Linear Programming

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A parameter analysis report can be used to easily investigate the changes in any number of data cells.

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Variable cells Cell Name Final Value Reduced Cost Objective Coefficient Allowable Increase Allowable Decrease \ \ 6 Activity 1 0 425 500 1+30 425 \ \ 6 Activity 2 27.5 0.0 300 500 300 \ \ Activity 3 0 250 400 1+30 250 Constraints Cell Name Final Value Shadow Price Constraint R.H. Side Allowable Increase Allowable Decrease \ \ 2 Benefit A 110 0 60 50 1+3 \ \ 3 Benefit B 110 75 110 1+30 46 mathrm E \ 4 Benefit C 137.5 0 80 57.5 1+30 If the objective coefficients of Activity 2 and Activity 3 are both decreased by $100, then:

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An optimal solution is only optimal with respect to a particular mathematical model that provides only a representation of the actual problem.

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A chance constraint I. Replaces the right-hand side with the minimum value. II. Allows the objective function coefficients to be replaced with random numbers. III. Ensures that the chance constraint will never be violated. IV. Can be used to model a soft constraint which can be violated at times.

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Variable cells Cell Name Final Value Reduced Cost Objective Coefficient Allowable Increase Allowable Decrease \ \ 6 Activity 1 0 425 500 1+30 425 \ \ 6 Activity 2 27.5 0.0 300 500 300 \ \ Activity 3 0 250 400 1+30 250 Constraints Cell Name Final Value Shadow Price Constraint R.H. Side Allowable Increase Allowable Decrease \ \ 2 Benefit A 110 0 60 50 1+3 \ \ 3 Benefit B 110 75 110 1+30 46 mathrm E \ 4 Benefit C 137.5 0 80 57.5 1+30 If the coefficient of Activity 2 in the objective function changes to $100, then:

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Variable cells Cell Name Final Value Reduced Cost Objective Coefficient Allowable Increase Allowable Decrease \ \ 6 Activity 1 0 425 500 1+30 425 \ \ 6 Activity 2 27.5 0.0 300 500 300 \ \ Activity 3 0 250 400 1+30 250 Constraints Cell Name Final Value Shadow Price Constraint R.H. Side Allowable Increase Allowable Decrease \ \ 2 Benefit A 110 0 60 50 1+3 \ \ 3 Benefit B 110 75 110 1+30 46 mathrm E \ 4 Benefit C 137.5 0 80 57.5 1+30 If the right-hand side of Resource C is increased by 40, and the right-hand side of Resource B is decreased by 20, then:

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If the optimal solution will remain the same over a wide range of values for a particular coefficient in the objective function, then management will want to take special care to narrow this estimate down.

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To determine if an increase in an objective function coefficient will lead to a change in final values for decision variables, an analyst can do which of the following? I. Compare the increase in the objective function coefficient to the allowable decrease. II. Compare the increase in the objective function coefficient to the allowable increase. III. Rerun the optimization to see if the final values change.

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A shadow price reflects which of the following in a maximization problem?

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Variable cells Cell Name Final Value Reduced Cost Objective Coefficient Allowable Increase Allowable Decrease \ \ 6 Activity 1 0 425 500 1+30 425 \ \ 6 Activity 2 27.5 0.0 300 500 300 \ \ Activity 3 0 250 400 1+30 250 Constraints Cell Name Final Value Shadow Price Constraint R.H. Side Allowable Increase Allowable Decrease \ \ 2 Benefit A 110 0 60 50 1+3 \ \ 3 Benefit B 110 75 110 1+30 46 mathrm E \ 4 Benefit C 137.5 0 80 57.5 1+30 If the coefficient for Activity 2 in the objective function changes to $400, then the objective function value:

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Activity 1 has an objective function coefficient allowable increase of 30. Activity 2 has an objective function coefficient allowable increase of 60. If both activities objective function coefficient increases by 20, what will happen to the final values in the optimal solution?

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Note: This question requires access to Solver. In the following linear programming problem, how much would the firm be willing to pay for an additional 5 units of Resource A? Maximize P=3x+15yP = 3 x + 15 y subject to 2x+4y12\quad 2 x + 4 y \leq 12 (Resource A) 5x+2y105 x + 2 y \leq 10 (Resource B) and x0,y0\quad x \geq 0 , y \geq 0 .

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The Solver report that shows the allowable ranges for objective function coefficients, allowable ranges for constraint right-hand sides, and shadow prices is called the

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In robust optimization, what is meant by the term "soft constraint"?

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When even a small change in the value of a coefficient in the objective function can change the optimal solution, the coefficient is called:

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