A Note on Smoothing Mathematical Programs with Equilibrium Constraints
نویسنده
چکیده
Mathematical programs with equilibrium constrains (MPECs) in which the constraints are defined by a parametric variational inequality are considered. Recently, nonlinear programming solvers have been used to solve MPECs. Smoothing algorithms have been very successful. In this note, a smoothing approach based on neural network function to solve MPECs is proposed. The performance of the proposed smoothing approach on as set of well-known problems is tested. A very useful and efficient tool for practitioners to solve not only MPEC problems but also more general class of MPECs is provided.
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