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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 \[ \min f(x) \quad\text{s.t. }c(x)= 0\quad\text{and }1\leq x\leq u. \] 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.

MSC:

65K05 Numerical mathematical programming methods
90C30 Nonlinear programming
90C55 Methods of successive quadratic programming type
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