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Type: Artigo de periódico
Title: Nonlinear programming algorithms using trust regions and augmented Lagrangians with nonmonotone penalty parameters
Author: Gomes, FAM
Maciel, MC
Martinez, JM
Abstract: A model algorithm based on the successive quadratic programming method for solving the general nonlinear programming problem is presented. The objective function and the constraints of the problem are only required to be differentiable and their gradients to satisfy a Lipschitz condition. The strategy for obtaining global convergence is based on the trust region approach. The merit function is a type of augmented Lagrangian. A new updating scheme is introduced for the penalty parameter, by means of which monotone increase is not necessary. Global convergence results are proved and numerical experiments are presented.
Subject: nonlinear programming
successive quadratic programming
trust regions
augmented Lagrangians
Lipschitz conditions
Country: Holanda
Editor: Elsevier Science Bv
Rights: fechado
Date Issue: 1999
Appears in Collections:Unicamp - Artigos e Outros Documentos

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