Predictor-Corrector Smoothing Newton Method, Based on a New Smoothing Function, for Solving the Nonlinear Complementarity Problem with a P 0 Function

Z.H. Huang, J. Han and Z. Chen
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Z.H. Huang: Institute of Applied Mathematics
J. Han: Institute of Applied Mathematics
Z. Chen: Suzhou University

Journal of Optimization Theory and Applications, 2003, vol. 117, issue 1, No 3, 39-68

Abstract: Abstract By smoothing a perturbed minimum function, we propose in this paper a new smoothing function. The existence and continuity of a smooth path for solving the nonlinear complementarity problem (NCP) with a P 0 function are discussed. We investigate the boundedness of the iteration sequence generated by noninterior continuation/smoothing methods under the assumption that the solution set of the NCP is nonempty and bounded. Based on the new smoothing function, we present a predictor-corrector smoothing Newton algorithm for solving the NCP with a P 0 function, which is shown to be globally linearly and locally superlinearly convergent under suitable assumptions. Some preliminary computational results are reported.

Keywords: Nonlinear complementarity problems; boundedness of iteration sequence; predictor-corrector smoothing Newton method; global linear convergence; local superlinear convergence (search for similar items in EconPapers)
Date: 2003
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Citations: View citations in EconPapers (5)

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DOI: 10.1023/A:1023648305969

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