mathematical models programming software
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It is well known that many reformulations of an MPEC model as a standard NLP model or as a parameterized sequence of NLP models exist. Some of these reformulations have been around for decades, others are quite recent. Given an MPEC model, it is likely that there exists a reformulation strategy and NLP solver that will find an MPEC solution. Unfortunately, it is not always clear a priori what that reformulation strategy is, and manual experiments with different reformulations are very time-consuming.The NLPEC solver automates the process of model reformulation. NLPEC reformulates the original MPEC as an NLP (using one of 23 different reformulation strategies), solves the resulting NLP, and translates the results back for return as an MPEC solution. Some of the reformulations involve a parameterized sequence of NLP models, with a penalty parameter going to zero; this sequence of models is constructed and run by NLPEC. A number of options exist to influence the initial points used by the NLP solvers and the construction of the NLP sequence in the case of parameterized NLP models
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