A Nonmonotone Smoothing Newton Algorithm for Weighted Complementarity Problem

Jingyong Tang () and Hongchao Zhang ()
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Jingyong Tang: Xinyang Normal University
Hongchao Zhang: Louisiana State University

Journal of Optimization Theory and Applications, 2021, vol. 189, issue 3, No 1, 679-715

Abstract: Abstract The weighted complementarity problem (denoted by WCP) significantly extends the general complementarity problem and can be used for modeling a larger class of problems from science and engineering. In this paper, by introducing a one-parametric class of smoothing functions which includes the weight vector, we propose a smoothing Newton algorithm with nonmonotone line search to solve WCP. We show that any accumulation point of the iterates generated by this algorithm, if exists, is a solution of the considered WCP. Moreover, when the solution set of WCP is nonempty, under assumptions weaker than the Jacobian nonsingularity assumption, we prove that the iteration sequence generated by our algorithm is bounded and converges to one solution of WCP with local superlinear or quadratic convergence rate. Promising numerical results are also reported.

Keywords: Smoothing Newton algorithm; Jacobian nonsingularity; Superlinear/quadratic convergence; Weighted complementarity problem; Symmetric cone; 90C25; 90C33; 65Y20 (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (2)

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DOI: 10.1007/s10957-021-01839-6

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