A Sequential Linear Constraint Programming Algorithm For NlP

Roger Fletcher

    Research output: Contribution to journalArticle

    8 Citations (Scopus)

    Abstract

    A new method for nonlinear programming (NLP) using sequential linear constraint programming (SLCP) is described. Linear constraint programming (LCP) subproblems are solved by a new code using a recently developed spectral gradient method for minimization. The method requires only first derivatives and avoids having to store and update approximate Hessian or reduced Hessian matrices. Globalization is provided by a trust region filter scheme. Open source production quality software is available. Results on a large selection of CUTEr test problems are presented and discussed and show that the method is reliable and reasonably efficient.

    Original languageEnglish
    Pages (from-to)772-794
    Number of pages23
    JournalSIAM Journal on Optimization
    Volume22
    Issue number3
    DOIs
    Publication statusPublished - 2012

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