Sensitivity analysis determines how sensitive the optimal solution is to changes made to the original linear programming model after obtaining the optimal solution. It is important because it allows analysts to check how changes to the data in the model, such as the coefficients, constraints, or variables, would affect the optimal solution and gives the model dynamic characteristics to handle potential future changes.

1. SENSITIVITY ANALYSIS Presented by :- Mini Suneja tqma2z.blogspot.com

2. Meaning of sensitivity analysis Sensitivity analysis serves as an integral part of solving linear programming model & is normally carried out after the optimal solution is obtained. It determines how sensitive the optimal solution is to making changes in the original model. It is also called POST OPTIMALITY ANALYSIS.

3. Importance of Sensitivity Analysis The analysis renders the model a dynamic characteristics that allows the analyst to check changes in the optimum solution resulting from future changes in the data of the model. It deals with the study of the changes in the optimum solution when the parameters of the problem changed.

4. Changes in the parameters includes : Changes in the coefficients of the objective function. Changes in the right hand side of the constraints. Addition of a new variable. Deletion of an existing variable Changes in the technological coefficients.

5. Bibliography Quantitative Techniques Vol I - By D.C. Jhamb