Linear optimization: Sensibility analysis 3

Basic

The sensitivity analysis is concerned with the effects and changes in the output data to the optimal solution. You can also ask this question a little differently: to what extent can size change without affecting the essential properties of the solution? Finding the optimal solution to a linear programming model is important, but one can derive the Sensitivity Analysis important additional information from the linear model ( but there are much more information that can be read from an analysis .) There is a tremendous amount of sensitivity information, or information about what happens when data values are changed. Other analysises you could only use under the condition that a constancy of the output data is given. However, such a stability of the output data does not exist in reality. That is a problem because you usually can not modify any data simultaneously, only one size while keeping constant all the other ("ceteris paribus") is changed and asked: In what area can the size in question vary, without this, the solution loses its validity? By "valid" here are the qualitative characteristics of a solution and not understood quantitatively. A solution is qualitatively different (structural) only by another if at least one pivot operation is needed to establish admissibility and / or optimality again if it was lost in the change.