Sensitivity analysis in linear programming is used to:
A) Determine the degree that the constraints vary.
B) Test the accuracy of the parameters in a model.
C) Develop the technical matrix used to determine the optimal solution.
D) Determine whether and how the optimal decision would change in response to changes in the parameters in the model.
E) Develop objective function coefficients.

Question

Quizplus · Accepted Answer

Sensitivity analysis in linear programming is used to determine whether and how the optimal decision would change in response to changes in the parameters in the model. By analyzing the impact of changes in the input parameters on the optimal solution and its associated values, decision-makers can acquire a greater understanding of the problem and make more informed decisions. Sensitivity analysis does not involve developing the technical matrix or objective function coefficients, which are determined during the formulation of the LP model. It also does not test the accuracy of the parameters in a model, which is done during the validation stage.

Sensitivity Analysis in Linear Programming Is Used To