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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.

MSC:
65K05Mathematical programming (numerical methods)
90C30Nonlinear programming
90C55Methods of successive quadratic programming type
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References:
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