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A filter-trust-region method for simple-bound constrained optimization. (English) Zbl 1169.90458
Summary: We propose a filter-trust-region algorithm for solving nonlinear optimization problems with simple bounds. It extends the technique of N. I. M. Gould and the authors [SIAM J. Optim. 16, No. 2, 341–357 (2005; Zbl 1122.90074)] designed for unconstrained optimization problems. The two main ingredients of the method are a filter-trust-region algorithm and a gradient-projection method. The algorithm is shown to be globally convergent to at least one first-order critical point. Numerical experiments on a large set of problems are also reported.

MSC:
90C30 Nonlinear programming
65K05 Numerical mathematical programming methods
90C26 Nonconvex programming, global optimization
90C06 Large-scale problems in mathematical programming
Software:
CUTEr; Filtrane; SifDec; TRON
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