PROXIMAL POINT ALGORITHM FOR MINIMIZATION OF DC FUNCTION

In this paper we present some algorithms for minimization of DC function (difference of two convex functions). They are descent methods of the proximal-type which use the convex properties of the two convex functions separately. We also consider an approximate proximal point algorithm. Some properti...

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Bibliographic Details
Published inJournal of computational mathematics Vol. 21; no. 4; pp. 451 - 462
Main Authors Sun, Wen-yu, Sampaio, Raimundo. J.B., Candido, M.A.B.
Format Journal Article
LanguageEnglish
Published Institute of Computational Mathematices and Scientific/Engineering Computing(ICMSEC) Chinese Academy of Sciences 01.07.2003
Subjects
Algorithms
Applied mathematics
Critical points
Eigenvalues
Iterative methods
Mathematical duality
Mathematical functions
Perceptron convergence procedure
Sufficient conditions
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ISSN0254-9409
1991-7139

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Summary:In this paper we present some algorithms for minimization of DC function (difference of two convex functions). They are descent methods of the proximal-type which use the convex properties of the two convex functions separately. We also consider an approximate proximal point algorithm. Some properties of the ∊-subdifferential and the ∊-directional derivative are discussed. The convergence properties of the algorithms are established in both exact and approximate forms. Finally, we give some applications to the concave programming and maximum eigenvalue problems.
ISSN:0254-9409
1991-7139