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A note on robust descent in differentiable optimization

Jean-Pierre Dussault(Jean-Pierre.Dussault***at***USherbrooke.CA)

Abstract: In this note, we recall two solutions to alleviate the catastrophic cancellations that occur when comparing function values in descent algorithms. The automatic finite differencing approach (Dussault and Hamelin) was shown useful to trust region and line search variants. The main original contribution is to successfully adapt the line search strategy (Hager and Zhang) for use within trust region like algorithms.

Keywords: Unconstrained nonlinear optimization, descent algorithms, numerical accuracy

Category 1: Nonlinear Optimization (Unconstrained Optimization )


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Entry Submitted: 11/05/2015
Entry Accepted: 11/05/2015
Entry Last Modified: 11/05/2015

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