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Stability and Robustness: Reliability in the World of Uncertainty

Stability and Robustness: Reliability in the World of Uncertainty

Stability and Robustness: Reliability in the World of Uncertainty

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Classical approachKouvelis P. <strong>and</strong> Yu G. (1997). Robust discrete optimization <strong>and</strong> itsapplications. Kluwer Academic Publishers, Norwell, M.A.A comprehensive treatment <strong>of</strong> <strong>the</strong> state <strong>of</strong> <strong>the</strong> art (up to 1997) <strong>in</strong>robust discrete optimization <strong>and</strong> extensive references arepresented <strong>in</strong> this work. However, <strong>the</strong>re still are more open problemsthan solved ones. Most <strong>of</strong> <strong>the</strong> known results correspond toscenario-represented models <strong>of</strong> uncerta<strong>in</strong>ty, i.e. where <strong>the</strong>re existsa f<strong>in</strong>ite number <strong>of</strong> possible scenarios each <strong>of</strong> which is givenexplicitly by list<strong>in</strong>g <strong>the</strong> correspond<strong>in</strong>g values <strong>of</strong> parameters. It isshown that most classical polynomially solvable comb<strong>in</strong>atorialoptimization problems loose this nice property <strong>and</strong> become NPhard<strong>in</strong> a robust version with scenario-represented uncerta<strong>in</strong>ty.16/04/2009 Yury Nikul<strong>in</strong>, Sensitivity analysis 6

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