Linear optimization: Sensibility analysis 1: Unterschied zwischen den Versionen
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== Theory == | == Theory == | ||
| − | The term "sensibilitätsanalyse" was derived from the original english term sensitivity analysis by Müller-Merbach [Operations Research] in 1992. Sensibility analysis is the retranslation of that. These two terms are being used equally. | + | The german term "sensibilitätsanalyse" was derived from the original english term sensitivity analysis by Müller-Merbach [Operations Research] in 1992. Sensibility analysis is the retranslation of that. These two terms are being used equally. |
After having found an optimal solution for a linear optimization problem by the means of the Simplex algorithm, one can use the sensibility analysis to see, how much the initial solution can change, without changing the structure of the optimal solution. | After having found an optimal solution for a linear optimization problem by the means of the Simplex algorithm, one can use the sensibility analysis to see, how much the initial solution can change, without changing the structure of the optimal solution. | ||
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<!--In particular, you can see --> | <!--In particular, you can see --> | ||
| − | === Non basic variables === | + | === Non basic variable change === |
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| + | By the found interval of non basic variables, you can see the robustness of the optimal solution, concerning the change of the restrictions. | ||
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| + | === basic variable change === | ||
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| + | By the interval of basic variables, you can see the robustness of the optimal solution, concerning the change of the objective function. | ||
== Example == | == Example == | ||
Version vom 27. Juni 2013, 17:15 Uhr
Besetzt H&S
Inhaltsverzeichnis
Theory
The german term "sensibilitätsanalyse" was derived from the original english term sensitivity analysis by Müller-Merbach [Operations Research] in 1992. Sensibility analysis is the retranslation of that. These two terms are being used equally.
After having found an optimal solution for a linear optimization problem by the means of the Simplex algorithm, one can use the sensibility analysis to see, how much the initial solution can change, without changing the structure of the optimal solution. In other words you can see, the robustness of your optimal programm regarding the change of the objective function or constraints.
Non basic variable change
By the found interval of non basic variables, you can see the robustness of the optimal solution, concerning the change of the restrictions.
basic variable change
By the interval of basic variables, you can see the robustness of the optimal solution, concerning the change of the objective function.
