A Superlinearly Convergent SSLE Algorithm for Optimization Problems with Linear Complementarity Constraints |
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Authors: | Email author" target="_blank">Jian-Ling?LiEmail author Jin-Bao?Jian |
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Institution: | (1) College of Mathematics and Informatics Science, Guangxi University, 530004 Nanning, P.R. China;(2) Department of Mathematics, Shanghai University, Baoshan, Shanghai, 200436, P.R. China |
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Abstract: | In this paper we study a special kind of optimization problems with linear complementarity constraints. First, by a generalized
complementarity function and perturbed technique, the discussed problem is transformed into a family of general nonlinear
optimization problems containing parameters. And then, using a special penalty function as a merit function, we establish
a sequential systems of linear equations (SSLE) algorithm. Three systems of equations solved at each iteration have the same
coefficients. Under some suitable conditions, the algorithm is proved to possess not only global convergence, but also strong
and superlinear convergence. At the end of the paper, some preliminary numerical experiments are reported. |
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Keywords: | algorithm complementarity constraints global convergence sequential systems of linear equations superlinear convergence |
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