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A nonmonotone trust-region algorithm with nonmonotone penalty parameters for constrained optimization. (English) Zbl 1059.65053
The authors consider general nonlinear programming problems in the form $$\min f(x) \quad\text{s.t. }c(x)= 0\quad\text{and }1\le x\le u.$$ For these problems, a nonmonotone trust-region algorithm with nonmonotone penalty parameters is presented. The given algorithm combines an successive quadratic programming approach with a trust-region strategy to globalize the process. The global convergence theory for the given algorithm is developed without regularity assumptions. Numerical experiments are presented.

65K05Mathematical programming (numerical methods)
90C30Nonlinear programming
90C55Methods of successive quadratic programming type
Full Text: DOI
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