What is sensitivity analysis in operations research?
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Sensitivity analysis examines how the optimal solution of an optimization model changes in response to variations in the input parameters, such as objective coefficients, constraint coefficients, and right-hand side values. It helps decision-makers understand the robustness of the solution.
Sensitivity analysis in operations research is a method used to assess how the variation in the output of a mathematical model, such as a Linear Programming (LP) problem, can be attributed to changes in its input parameters. It involves examining the effects of alterations in coefficients of the objective function, right-hand side values of constraints, and other parameters on the optimal solution.
Sensitivity analysis in operations research is a technique used to determine how changes in input values, such as costs or resource availability, affect the outcome of a model or decision. It helps identify which variables have the most impact on results, allowing decision-makers to understand risks and make more informed choices based on different scenarios.