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Local Feasible QP-Free Algorithms for the Constrained Minimization of SC1 Functions

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Abstract

We consider the problem of minimizing an SC1 function subject to inequality constraints. We propose a local algorithm whose distinguishing features are that: (a) a fast convergence rate is achieved under reasonable assumptions that do not include strict complementarity at the solution; (b) the solution of only linear systems is required at each iteration; (c) all the points generated are feasible. After analyzing a basic Newton algorithm, we propose some variants aimed at reducing the computational costs and, in particular, we consider a quasi-Newton version of the algorithm.

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Authors and Affiliations

  1. Dipartimento di Informatica e Sistemistica, Università di Roma–La Sapienza, Rome, Italy

    F. Facchinei (Professor)

  2. Istituto di Analisi dei Sistemi ed Informatica, CNR, Rome, Italy

    C. Lazzari (Postdoctoral Fellow)

Authors
  1. F. Facchinei
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  2. C. Lazzari
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Facchinei, F., Lazzari, C. Local Feasible QP-Free Algorithms for the Constrained Minimization of SC1 Functions. Journal of Optimization Theory and Applications 119, 281–316 (2003). https://doi.org/10.1023/B:JOTA.0000005447.36961.29

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  • DOI: https://doi.org/10.1023/B:JOTA.0000005447.36961.29

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