Abstract
In this paper, a projected gradient trust region algorithm for solving nonlinear equality systems with convex constraints is considered. The global convergence results are developed in a very general setting of computing trial directions by this method combining with the line search technique. Close to the solution set this method is locally Q-superlinearly convergent under an error bound assumption which is much weaker than the standard nonsingularity condition.
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Supported by the National Natural Science Foundation of China (10871130), the Research Fund for the Doctoral Program of Higher Education of China (20093127110005), and the Scientific Computing Key Laboratory of Shanghai Universities.
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Jia, Cx., Zhu, Dt. Projected gradient trust-region method for solving nonlinear systems with convex constraints. Appl. Math. J. Chin. Univ. 26, 57–69 (2011). https://doi.org/10.1007/s11766-011-1956-7
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DOI: https://doi.org/10.1007/s11766-011-1956-7