Interior-Point Methods for Nonconvex Nonlinear Programming: Complementarity Constraints
Hande Y. Benson (hyurttanprinceton.edu)
Abstract: In this paper, we present the formulation and solution of optimization problems with complementarity constraints using an interior-point method for nonconvex nonlinear programming. We identify possible difficulties that could arise, such as unbounded faces of dual variables, linear dependence of constraint gradients and initialization issues. We suggest remedies. We include encouraging numerical results on the MacMPEC test suite of problems.
Keywords: interior-point methods, large-scale optimization, nonlinear programming, complementarity constraints
Category 1: Nonlinear Optimization (Constrained Nonlinear Optimization )
Category 2: Complementarity and Variational Inequalities
Citation: ORFE 02-02. Department of Operations Research and Financial Engineering, Princeton University, Princeton, NJ, 08544. July 2002.
Entry Submitted: 07/25/2002
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