A filter inexact-restoration method for nonlinear programming
A new iterative algorithm based on the inexact-restoration (IR) approach combined with the filter strategy to solve nonlinear constrained optimization problems is presented. The high level algorithm is suggested by Gonzaga et al. [7] but not yet implemented - the internal algorithms are not proposed...
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| Formato: | article |
| Idioma: | eng |
| Publicado em: |
2008
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| Texto completo: | http://hdl.handle.net/1822/16571 |
| País: | Portugal |
| Oai: | oai:repositorium.sdum.uminho.pt:1822/16571 |
| Resumo: | A new iterative algorithm based on the inexact-restoration (IR) approach combined with the filter strategy to solve nonlinear constrained optimization problems is presented. The high level algorithm is suggested by Gonzaga et al. [7] but not yet implemented - the internal algorithms are not proposed. The filter, a new concept introduced by Fletcher and Leyffer [3], replaces the merit function avoiding the penalty parameter estimation and the difficulties related to the nondifferentiability. In the IR approach two independent phases are performed in each iteration - the feasibility and the optimality phases. The line search filter is combined with the first one phase to generate a “more feasible” point and then it is used in the optimality phase to reach an “optimal” point. Numerical experiences with a collection of AMPL problems and a performance comparison with IPOPT are provided. |
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