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Global and local convergence of a nonmonotone trust region algorithm for equality constrained optimization. (English) Zbl 1186.90112

Summary: This paper presents a nonmonotone trust region algorithm for equality constrained optimization problems. Under certain conditions, we obtain not only the global convergence in the sense that every limit point is a stationary point but also the one step superlinear convergence rate. Numerical tests are also given to show the efficiency of the proposed algorithm.

MSC:

90C30 Nonlinear programming
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