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2010•Shuxue de shijian yu renshiRequires access

A Trust-region Method for Nonlinear Optimization with Equations Constrained

Rongjun Chen

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Abstract

This paper proposes a new class of trust region algorithm for solving equality constrained nonlinear optimization problems.The trust region subproblem formula is presented based on augmented Lagrangian function.study the Lagrangian multiplier and penalty factor correction formula,and use the filter technique,relax the conditions of acceptance of the trail step,proof of the convergence of the algorithm.Finally,a numerical test.is reported.

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What this paper is about

This paper proposes a new class of trust region algorithm for solving equality constrained nonlinear optimization problems.The trust region subproblem formula is presented based on augmented Lagrangian function.study the Lagrangian multiplier and penalty factor correction formula,and use the filter technique,relax the conditions of acceptance of the trail step,proof of the convergence of the algorithm.Finally,a numerical test.is reported.

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Available abstract

This paper proposes a new class of trust region algorithm for solving equality constrained nonlinear optimization problems.The trust region subproblem formula is presented based on augmented Lagrangian function.study the Lagrangian multiplier and penalty factor correction formula,and use the filter technique,relax the conditions of acceptance of the trail step,proof of the convergence of the algorithm.Finally,a numerical test.is reported.

Key concepts: Trust region, Augmented Lagrangian method, Convergence (economics), Lagrangian, Multiplier (economics), Mathematical optimization, Nonlinear system, Lagrange multiplier

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