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Projected-Search Methods for Box-Constrained Optimization

Michael Ferry
UCSD

Abstract:

We survey several commonly-used quasi-Newton methods and line-search algorithms for unconstrained and box-constrained optimization and consider their underlying strategies. By taking advantage of an implicit similarity in two existing algorithms, we develop a method for box-constrained optimization that includes a new way to compute a search direction and a new line-search algorithm. On a collection of standardized problems, this method is over 35% faster than the leading comparable alternative.

Tuesday, April 12, 2011
11:00AM AP&M 2402