Original scientific paper

Robust solutions to uncertain weighted least squares problems

Lei Wang ; Department of Economic Mathematics, Southwestern University of Finance and Economics, Chengdu, Sichuan, P. R. China
Nan-jing Huang ; Department of Mathematics, Sichuan University, Chengdu, Sichuan, P. R. China

Abstract

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.

Keywords

robust optimization; weighted least squares problems; robust counterpart; convex programming

Hrčak ID:

93285

URI

https://hrcak.srce.hr/93285

Publication date:

5.12.2012.

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