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.


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    Title :

    Globally convergent exact penalty algorithms for constrained optimization


    Contributors:
    Pillo, G. (author) / Grippo, L. (author) / Lucidi, S. (author)


    Publication date :

    1986-01-01


    Size :

    10 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




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