Sequential equality-constrained optimization for nonlinear programming

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2016
Autores
Birgin, E. G.
Bueno, Luis Felipe [UNIFESP]
Martinez, J. M.
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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.
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Computational Optimization And Applications. New York, v. 65, n. 3, p. 699-721, 2016.
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