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Handling infeasibility in a large-scale nonlinear optimization algorithm

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Autor(es):
Martinez, Jose Mario ; Prudente, Leandro da Fonseca
Número total de Autores: 2
Tipo de documento: Artigo Científico
Fonte: NUMERICAL ALGORITHMS; v. 60, n. 2, p. 15-pg., 2012-06-01.
Resumo

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. (AU)

Processo FAPESP: 06/53768-0 - Métodos computacionais de otimização
Beneficiário:José Mário Martinez Perez
Modalidade de apoio: Auxílio à Pesquisa - Temático