Projects per year
Abstract
A direct search method for unconstrained optimization is described. The method makes use of any partial separability structure that the objective function may have. The method uses successively finer nested grids, and minimizes the objective function over each grid in turn. All grids are aligned with the coordinate directions, which allows the partial separability structure of the objective function to be exploited. This has two advantages: it reduces the work needed to calculate function values at the points required and it provides function values at other points as a free by-product. Numerical results show that using partial separability can dramatically reduce the number of function evaluations needed to minimize a function, in some cases allowing problems with thousands of variables to be solved. Results show that the algorithm is effective on strictly C 1 problems and on a class of non-smooth problems.
Original language | English |
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Pages (from-to) | 479-491 |
Number of pages | 13 |
Journal | Optimization Methods and Software |
Volume | 21 |
Issue number | 3 |
DOIs | |
Publication status | Published - 1 Jun 2006 |
Keywords
- derivative-free
- pattern search
- numerical results
- partial separability
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Projects
- 2 Active
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DFO: Derivative free numerical algorithms for optimization
TOINT, P., COLSON, B., Gratton, S., Tröltzsch, A. & RODRIGUES SAMPAIO, P.
1/03/94 → …
Project: Research
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Activities
- 2 Visiting an external academic institution
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DIEF, University of Florence
Philippe Toint (Visiting researcher)
15 Sep 2018 → 15 Oct 2018Activity: Visiting an external institution types › Visiting an external academic institution
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DIEF, University of Florence
Philippe Toint (Visiting researcher)
1 Oct 2017 → 31 Oct 2017Activity: Visiting an external institution types › Visiting an external academic institution