A new iterative algorithm based on the inexact-restoration (IR)approach combined with the filter strategy to solve nonlinear constrainedoptimization problems is presented. The high level algorithmis suggested by Gonzaga et al. [7] but not yet implemented - theinternal algorithms are not proposed. The filter, a new concept introducedby Fletcher and Leyffer [3], replaces the merit function avoidingthe penalty parameter estimation and the difficulties related to thenondifferentiability. In the IR approach two independent phases areperformed in each iteration - the feasibility and the optimality phases.The line search filter is combined with the first one phase to generatea “more feasible” point and then it is used in the optimality phase toreach an “optimal” point.Numerical experiences with a collection of AMPL problems and aperformance comparison with IPOPT are provided.
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