On the local and global convergence of a reduced Quasi-Newton method1

Gilbert J-C (1989). On the local and global convergence of a reduced Quasi-Newton method1. Optimization 20 (4): 421-450. DOI:10.1080/02331938908843462.

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Abstract

In optimization in Rn with m nonlinear equality constraints, we study the local convergence of reduced quasi-Newton methods, in which the updated matrix is of order n−m Furthermore, we give necessary and sufficient conditions for superlinear convergence (in one step) and we introduce a device to globalize the local algorithm, It consists in determining a step along an arc in order to decrease an exact penalty function and we give conditions so that asymptotically the step-size will be equal to one.

Item Type: Article
Uncontrolled Keywords: constrained optimization, successive quadratic programming, reduced quasi-newton method, superlinear convergence, exact penalty function, are search, step-size selection procedure, global convergence,
Research Programs: System and Decision Sciences - Core (SDS)
Depositing User: Romeo Molina
Date Deposited: 20 Apr 2016 07:30
Last Modified: 30 Aug 2016 06:52
URI: http://pure.iiasa.ac.at/12800

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