Handling infeasibility in a large-scale nonlinear optimization algorithm |
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Authors: | Jose Mario Martínez Leandro da Fonseca Prudente |
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Institution: | 1.Department of Applied Mathematics, IMECC-UNICAMP,University of Campinas,Campinas,Brazil |
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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. |
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Keywords: | |
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