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- W350210147 endingPage "303" @default.
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- W350210147 abstract "This chapter is the central part of the book; it is devoted to local convergence analysis of Newton-type methods for optimization with constraints. The perturbed sequential quadratic programming (SQP) framework is introduced, which allows to treat, in addition and in a unified manner, not only various modifications of SQP itself (truncated, augmented Lagrangian based versions, and second-order corrections) but also a number of other algorithms even though their iterative subproblems are very different from SQP (linearly constrained Lagragian algorithm, sequential quadratically constrained quadratic programming, inexact restoration, and a certain interior feasible directions method)." @default.
- W350210147 created "2016-06-24" @default.
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- W350210147 date "2014-01-01" @default.
- W350210147 modified "2023-09-23" @default.
- W350210147 title "Constrained Optimization: Local Methods" @default.
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- W350210147 doi "https://doi.org/10.1007/978-3-319-04247-3_4" @default.
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