Abstract
We present an iterative method for minimizing strictly convex quadratic functions over the intersection of a finite number of convex sets. The method consists in computing projections onto the individual sets simultaneously and the new iterate is a convex combination of those projections. We give convergence proofs even for the inconsistent case, i.e. when the intersection of the sets is empty.
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Work of this author was partially supported by CNPq under grant No. 301280/86-MA.
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Iusem, A.N., De Pierro, A.R. On the convergence of Han's method for convex programming with quadratic objective. Mathematical Programming 52, 265–284 (1991). https://doi.org/10.1007/BF01582891
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DOI: https://doi.org/10.1007/BF01582891