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On the implementation of reduced gradient methods

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IFIP Lecture Notes in Computer Science (LNCS)
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Disciplines
  • Computer Science

Abstract

Until now, the implementation of reduced gradient methods had to be improvised empirically, since procedures for the truncation of the inner iterations, in the feasibility restoration stage, have not been analyzed with respect to convergence of the overall algorithm. This paper presents an implementation of one reduced gradient method. While retaining all the attractive features of the classical reduced gradient methods, this implementation incorporates, explicitly, efficient procedures for truncating the inner iterations to a finite number. In the paper, we present the properties of the restoration subalgorithm and we prove the convergence of the new algorithm under fairly general assumptions.Full Text at Springer, may require registration or fee

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