A penalty-free method for equality constrained optimization

Zhongwen Chen; Songqiang Qiu; Yujie Jiao

doi:10.3934/jimo.2013.9.391

Article Contents

2013, Volume 9, Issue 2: 391-409. Doi: 10.3934/jimo.2013.9.391

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A penalty-free method for equality constrained optimization

1.
School of Mathematics Science, Soochow University, Suzhou, 215006

Received: September 2011

Revised: January 2013

Published: April 2013

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Abstract

A penalty-free method is introduced for solving nonlinear programming with nonlinear equality constraints. This method does not use any penalty function, nor a filter. It uses trust region technique to compute trial steps. By comparing the measures of feasibility and optimality, the algorithm either tries to reduce the value of objective function by solving a normal subproblem and a tangential subproblem or tries to improve feasibility by solving a normal subproblem only. In order to guarantee global convergence, the measure of constraint violation in each iteration is required not to exceed a progressively decreasing limit. Under usual assumptions, we prove that the given algorithm is globally convergent to first order stationary points. Preliminary numerical results on CUTEr problems are reported.

Keywords:

Nonlinear equality-constrained optimization,
penalty-free method,
trust region,
global convergence.

Mathematics Subject Classification: Primary: 65K05; Secondary: 90C26, 90C30.

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