Abstract
In this paper, we first discuss how the nearly exact (NE) method proposed by Moré and Sorensen [14] for solving trust region (TR) subproblems can be modified to solve large-scale "low-rank" TR subproblems efficiently. Our modified algorithm completely avoids computation of Cholesky factorizations by instead relying primarily on the Sherman-Morrison-Woodbury formula for computing inverses of "diagonal plus low-rank" type matrices. We also implement a specific version of the modified log-barrier (MLB) algorithm proposed by Polyak [17] where the generated log-barrier subproblems are solved by a trust region method. The corresponding direction finding TR subproblems are of the low-rank type and are then solved by our modified NE method. We finally discuss the computational results of our implementation of the MLB method and its comparison with a version of LANCELOT [5] based on a collection extracted from CUTEr [12] of nonlinear programming problems with simple bound constraints.
Original language | English (US) |
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Pages (from-to) | 385-411 |
Number of pages | 27 |
Journal | Mathematical Programming |
Volume | 109 |
Issue number | 2-3 |
DOIs | |
State | Published - Mar 1 2007 |
Externally published | Yes |
Keywords
- Large-scale optimization
- Limited-memory BFGS method
- Nearly exact method
- Sherman-Morrison-Woodbury formula
- Trust region method