Sequential equality-constrained optimization for nonlinear programming

E. G. Birgin (), L. F. Bueno and J. M. Martínez
Additional contact information
E. G. Birgin: University of São Paulo
L. F. Bueno: Federal University of São Paulo
J. M. Martínez: State University of Campinas

Computational Optimization and Applications, 2016, vol. 65, issue 3, No 7, 699-721

Abstract: 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 (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (3)

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DOI: 10.1007/s10589-016-9849-6

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