Traversing non-convex regions

Michael Bartholomew-Biggs, Salah Beddiaf, Stephen Kane

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    This paper considers a method for dealing with non-convex objective functions in optimization problems. It uses the Hessian matrix and combines features of trust-region techniques and continuous steepest descent trajectory-following in order to construct an algorithm which performs curvilinear searches away from the starting point of each iteration. A prototype implementation yields promising results
    Original languageEnglish
    Pages (from-to)387-407
    JournalAdvanced Modeling and Optimization
    Issue number2
    Publication statusPublished - 2013


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