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A filter line search algorithm based on an inexact Newton method for nonconvex equality constrained optimization

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Abstract

We propose an inexact Newton method with a filter line search algorithm for nonconvex equality constrained optimization. Inexact Newton’s methods are needed for large-scale applications which the iteration matrix cannot be explicitly formed or factored. We incorporate inexact Newton strategies in filter line search, yielding algorithm that can ensure global convergence. An analysis of the global behavior of the algorithm and numerical results on a collection of test problems are presented.

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Acknowledgements

The authors would like to thank two anonymous referees for their helpful comments and suggestions.

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Correspondence to Zhu-jun Wang.

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Supported in part by the National Natural Science Foundation of China under Grant No.11371253, Natural Science Foundation of Hunan Province under Grant No.2016JJ2038 and the project of Scientific Research Fund of Hunan Provincial Education Department under Grant No.14B044.

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Wang, Zj., Zhu, Dt. & Nie, Cy. A filter line search algorithm based on an inexact Newton method for nonconvex equality constrained optimization. Acta Math. Appl. Sin. Engl. Ser. 33, 687–698 (2017). https://doi.org/10.1007/s10255-017-0691-0

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  • DOI: https://doi.org/10.1007/s10255-017-0691-0

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