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Erschienen in:
2014 | OriginalPaper | Buchkapitel
DC Programming and DCA for General DC Programs
verfasst von : Hoai An Le Thi, Van Ngai Huynh, Tao Pham Dinh
Erschienen in: Advanced Computational Methods for Knowledge Engineering
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We present a natural extension of DC programming and DCA for modeling and solving general DC programs with DC constraints. Two resulting approaches consist in reformulating those programs as standard DC programs in order to use standard DCAs for their solutions. The first one is based on penalty techniques in DC programming, while the second linearizes concave functions in DC constraints to build convex inner approximations of the feasible set. They are proved to converge to KKT points of general DC programs under usual constraints qualifications. Both designed algorithms can be viewed as a sequence of standard DCAs with updated penalty (resp. relaxation) parameters.