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|Title:||Tractable approximations to robust conic optimization problems|
|Citation:||Bertsimas, D., Sim, M. (2006). Tractable approximations to robust conic optimization problems. Mathematical Programming 107 (1-2) : 5-36. ScholarBank@NUS Repository. https://doi.org/10.1007/s10107-005-0677-1|
|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.|
|Source Title:||Mathematical Programming|
|Appears in Collections:||Staff Publications|
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