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Seminaire MASCOTTE
The Recoverable Robust Knapsack Problem with $Gamma$-Scenarios

par Manuel Kutschka (University of Aachen)


Date :13/12/11
Time :11:00
Location :Galois Coriolis


Ă‚' Recoverable robustness has been recently introduced to deal with uncertainties in optimization problems. This two-stage approach allows a limited change of a first-stage decision after the realization of all uncertain parameters is known. In this talk, we study the Recoverable Robust Knapsack Problem where the uncertainty of the item weights is defined implicitly following the $Gamma$-robustness approach of Bertsimas and Sim. We describe a polynomial-sized compact ILP formulation of this problem, investigate valid inequalities for the corresponding polytope of feasible solutions, and present preliminary computational results.

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