Abstract In this paper we define two classes of algorithms for the solution of constrained problems. The first class is based on a continuously differentiable exact penalty function, with the additional inclusion of a barrier term. The second class is based on a similar modification performed on a continuously differentiable exact augmented Lagrangian function. In connection with these functions, an automatic adjustment rule for the penalty parameter is described, which ensures global convergence, and Newton-type schemes are proposed which ensure an ultimate superlinear convergence rate.
Globally convergent exact penalty algorithms for constrained optimization
01.01.1986
10 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
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