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2004•Journal of Mathematical Research and ExpositionRequires access

A Trust-region Algorithm for Nonlinear Constrained Optimization Problem

Shuzi Zhou

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Abstract

This paper presents a new trust-region algorithm for general nonlinear constrained optimization problems. Certain equivalent KKT conditions of the problems are derived. Global convergence of the algorithm to a first-order KKT point is established under mild conditions on the trial steps. Numerical example is also reported.

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What this paper is about

This paper presents a new trust-region algorithm for general nonlinear constrained optimization problems. Certain equivalent KKT conditions of the problems are derived. Global convergence of the algorithm to a first-order KKT point is established under mild conditions on the trial steps. Numerical example is also reported.

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Available abstract

This paper presents a new trust-region algorithm for general nonlinear constrained optimization problems. Certain equivalent KKT conditions of the problems are derived. Global convergence of the algorithm to a first-order KKT point is established under mild conditions on the trial steps. Numerical example is also reported.

Key concepts: Karush–Kuhn–Tucker conditions, Trust region, Convergence (economics), Mathematical optimization, Mathematics, Nonlinear system, Optimization problem, Point (geometry)

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