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Convergence of a Penalty Method for Mathematical Programming with Complementarity Constraints

Xinmin Hu (xinmin***at***ms.unimelb.edu.au)
Daniel Ralph (danny.ralph***at***jims.cam.ac.uk)

Abstract: We adapt the convergence analysis of smoothing (Fukushima and Pang) and regularization (Scholtes) methods to a penalty framework for mathematical programs with complementarity constraints (MPCCs), and show that the penalty framework shares similar convergence properties to these methods. Moreover, we give sufficient conditions for a sequence generated by the penalty framework to be attracted to a B-stationary point of the MPCC.

Keywords: MPEC, MPCC, complementarity constraints, penalty methods, B-stationarity, linear independence constraint qualification

Category 1: Nonlinear Optimization (Constrained Nonlinear Optimization )

Category 2: Complementarity and Variational Inequalities

Citation: Department of Mathematics and Statistics, The University of Melbourne, Vic 3010, Australia

Download: [Postscript][Compressed Postscript]

Entry Submitted: 09/02/2002
Entry Accepted: 09/02/2002
Entry Last Modified: 09/09/2002

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