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Descent heuristics for unconstrained minimization

Florian Jarre(jarre***at***opt.uni-duesseldorf.de)
Ania Lopez(lopez***at***opt.uni-duesseldorf.de)

Abstract: Semidefinite relaxations often provide excellent starting points for nonconvex problems with multiple local minimizers. This work aims to find a local minimizer within a certain neighborhood of the starting point and with a small objective value. Several approaches are motivated and compared with each other.

Keywords: Descent method, unconstrained minimization, local minimizer

Category 1: Global Optimization (Other )

Category 2: Nonlinear Optimization (Unconstrained Optimization )

Citation: Report, Mathematisches Institut, Universitaet Duesseldorf, August 2008.

Download: [PDF]

Entry Submitted: 08/14/2008
Entry Accepted: 09/01/2008
Entry Last Modified: 08/14/2008

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