Inverse Stochastic Linear Programming
Abstract: Inverse optimization perturbs objective function to make an initial feasible solution optimal with respect to perturbed objective function while minimizing cost of perturbation. We extend inverse optimization to two-stage stochastic linear programs. Since the resulting model grows with number of scenarios, we present two decomposition approaches for solving these problems.
Keywords: Inverse Optimization, Stochastic Programming,Decomposition Algorithms
Category 1: Stochastic Programming
Citation: Unpublished: 07-1, University of Pittsburgh, Pittsburgh PA 15261, January 2007.
Entry Submitted: 01/05/2007
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