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Computational Optimization and Applications

, Volume 65, Issue 3, pp 699–721 | Cite as

Sequential equality-constrained optimization for nonlinear programming

  • E. G. Birgin
  • L. F. Bueno
  • J. M. Martínez
Article

Abstract

A novel idea is proposed for solving optimization problems with equality constraints and bounds on the variables. In the spirit of sequential quadratic programming and sequential linearly-constrained programming, the new proposed approach approximately solves, at each iteration, an equality-constrained optimization problem. The bound constraints are handled in outer iterations by means of an augmented Lagrangian scheme. Global convergence of the method follows from well-established nonlinear programming theories. Numerical experiments are presented.

Keywords

Nonlinear programming Sequential equality-constrained optimization Augmented Lagrangian Numerical experiments 

Notes

Acknowledgments

This work was supported by PRONEX-CNPq/FAPERJ E-26/111.449/2010-APQ1, FAPESP (Grants 2010/10133-0, 2013/03447-6, 2013/05475-7, 2013/07375-0, and 2015/02528-8), and CNPq (Grants 309517/2014-1 and 303750/2014-6).

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Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  1. 1.Department of Computer Science, Institute of Mathematics and StatisticsUniversity of São PauloSão PauloBrazil
  2. 2.Institute of Science and TechnologyFederal University of São PauloSão José dos CamposBrazil
  3. 3.Department of Applied Mathematics, Institute of Mathematics, Statistics, and Scientific ComputingState University of CampinasCampinasBrazil

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