Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/68571
Type: Artigo de periódico
Title: Handling infeasibility in a large-scale nonlinear optimization algorithm
Author: Martinez, JM
Prudente, LD
Abstract: Practical Nonlinear Programming algorithms may converge to infeasible points. It is sensible to detect this situation as quickly as possible, in order to have time to change initial approximations and parameters, with the aim of obtaining convergence to acceptable solutions in further runs. In this paper, a recently introduced Augmented Lagrangian algorithm is modified in such a way that the probability of quick detection of asymptotic infeasibility is enhanced. The modified algorithm preserves the property of convergence to stationary points of the sum of squares of infeasibilities without harming the convergence to KKT points in feasible cases.
Subject: Augmented lagrangians
Nonlinear programming
Algorithms
Numerical experiments
Country: Holanda
Editor: Springer
Rights: fechado
Identifier DOI: 10.1007/s11075-012-9561-2
Date Issue: 2012
Appears in Collections:Artigos e Materiais de Revistas Científicas - Unicamp

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