On the convergence of the DFP algorithm for unconstrained optimization when there are only two variables View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2000-04

AUTHORS

M.J.D. Powell

ABSTRACT

Let the DFP algorithm for unconstrained optimization be applied to an objective function that has continuous second derivatives and bounded level sets, where each line search finds the first local minimum. It is proved that the calculated gradients are not bounded away from zero if there are only two variables. The new feature of this work is that there is no need for the objective function to be convex. More... »

PAGES

281-301

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s101070050115

DOI

http://dx.doi.org/10.1007/s101070050115

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1026919178


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