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Stability measures of optimal solution of LP problems with regards to the target function
 Sůra, Jan ; Pelikán, Jan (advisor) ; Sokol, Ondřej (referee)
Real-world systems usually contain some degree of natural uncertainty, their parameters are more or less variable. When seeking optimal solution, optimization models often disregard this variability and consider parameters of the model to be constant. This thesis focuses on methods of post-optimization analysis. Thorough post-optimization analysis should be a part of every optimization process of systems with variable parameters. Post-optimization analysis can identify parameters whose variability poses the greatest threat to the systems performance. This thesis describes some of the basic post-optimization methods and then a new method based on interval arithmetics is formulated.
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