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Porovnání aproximací v úlohách stochastické a robustní optimalizace
Houda, Michal
The paper deals with two wide areas of optimization theory: stochastic and robust programming. We specialize to different approaches when solving an optimization problem where some uncertainties in constraints occur. To overcome uncertainty, we can request the solution to be feasible to all but a small part of constraints. Both approaches gives us different methods to deal with this requirement. We try to find fundamental differencies between them and illustrate the differencies on a simple numerical example.
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Aproximace stochastických a robustních optimalizačních úloh
Houda, Michal
The paper deals with two wide areas of optimization theory: stochastic and robust programming. We specialize to different approaches when solving an optimization problem where some uncertainties in constraints occur. To overcome uncertainty, we can request the solution to be feasible to all but a small part of constraints. Both approaches gives us different methods to deal with this requirement. We try to find fundamental differencies between them and illustrate the differencies on a simple numerical example.
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