Robust solutions to uncertain weighted least squares problems ∗
نویسندگان
چکیده
Robust optimization is a rapidly developing methodology for handling optimization problems affected by non-stochastic uncertain-but-bounded data perturbations. In this paper, we consider the weighted least squares problems where the coefficient matrices and vector belong to different uncertain bounded sets. We introduce the robust counterparts of these problems and reformulate them as the tractable convex optimization problems. Two kinds of approaches for solving the robust counterpart of weighted least squares problems with ellipsoid uncertainty sets are also given. AMS subject classifications: 90C34, 90C05, 90C20
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