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On the global convergence of interior-point nonlinear programming algorithms

Gabriel Haeser (ghaeser***at***gmail.com)

Abstract: Carathéodory's lemma states that if we have a linear combination of vectors in R^n, we can rewrite this combination using a linearly independent subset. This result has been successfully applied in nonlinear optimization in many contexts. In this work we present a new version of this celebrated theorem, in which we obtained new bounds for the size of the coefficients in the linear combination and we provide examples where these bounds are useful. We show how these new bounds can be used to prove that the internal penalty method converges to KKT points, and we prove that the hypothesis to obtain this result cannot be weakened. The new bounds also provides us some new results of convergence for the quasi feasible interior point l_2-penalty method of Chen and Goldfarb

Keywords: Nonlinear Programming; Constraint Qualifications; Interior Point Methods

Category 1: Nonlinear Optimization

Category 2: Nonlinear Optimization (Constrained Nonlinear Optimization )


Download: [PDF]

Entry Submitted: 06/30/2009
Entry Accepted: 06/30/2009
Entry Last Modified: 03/21/2010

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