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- W2005678164 abstract "In earlier proposals, the robust counterpart of conic optimization problems exhibits a lateral increase in complexity, i.e., robust linear programming problems (LPs) become second order cone problems (SOCPs), robust SOCPs become semidefinite programming problems (SDPs), and robust SDPs become NP-hard. We propose a relaxed robust counterpart for general conic optimization problems that (a) preserves the computational tractability of the nominal problem; specifically the robust conic optimization problem retains its original structure, i.e., robust LPs remain LPs, robust SOCPs remain SOCPs and robust SDPs remain SDPs, and (b) allows us to provide a guarantee on the probability that the robust solution is feasible when the uncertain coefficients obey independent and identically distributed normal distributions." @default.
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- W2005678164 date "2005-12-30" @default.
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- W2005678164 title "Tractable Approximations to Robust Conic Optimization Problems" @default.
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- W2005678164 doi "https://doi.org/10.1007/s10107-005-0677-1" @default.
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