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Interior-Point l_2 Penalty Methods for Nonlinear Programming with Strong Global Convergence Properties

Lifeng Chen (lc2161***at***columbia.edu)
Donald Goldfarb (gold***at***ieor.columbia.edu)

Abstract: We propose two line search primal-dual interior-point methods that approximately solve a equence of equality constrained barrier subproblems. To solve each subproblem, our methods apply a modified Newton method and use an $\ell_2$-exact penalty function to attain feasibility. Our methods have strong global convergence properties under standard assumptions. Specifically, if the penalty parameter remains bounded, any limit point of the iterate sequence is either a KKT point of the barrier subproblem, or a Fritz-John (FJ) point of the original problem that fails to satisfy the Mangasarian-Fromovitz constraint qualification (MFCQ); if the penalty parameter tends to infinity, there is a limit point that is either an infeasible FJ point of the inequality constrained feasibility problem (an infeasible stationary point of the infeasibility measure if slack variables are added) or a FJ point of the original problem at which the MFCQ fails to hold. Numerical results are given that illustrate these outcomes.

Keywords: constrained optimization, nonlinear programming, primal-dual interior-point, global convergence, penalty-barrier method, modified Newton

Category 1: Nonlinear Optimization

Citation: CORC TR-2004-08, Columbia University

Download: [Postscript][PDF]

Entry Submitted: 05/27/2005
Entry Accepted: 05/27/2005
Entry Last Modified: 05/27/2005

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