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Research Article

An improvement on the global error bound estimation for ELCP and its applications

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Pages 644-670 | Received 16 Apr 2021, Accepted 17 Apr 2021, Published online: 03 May 2021
 

Abstract

For the extended linear complementarity problem (ELCP), we establish a global error bound estimation for ELCP under milder condition. Based on this, we propose a smoothing algorithm for solving the problem. The algorithm is shown to be globally convergent and quadratically convergent rate without nondegenerate assumption. The result obtained in this paper extend the existing ones for the ELCP. Moreover, some numerical experimental results are presented, and indicate that the validity of the algorithm, as well as the rapid convergence of the method.

AMS Subject Classifications:

Acknowledgments

This work was supported by the Natural Science Foundation of China (Nos. 11671228, 11801309), the Domestic Visiting Scholar Project for the Outstanding Young Teacher of Shandong Provincial Universities (2013) and the Applied Mathematics Enhancement Program of Linyi University.

Additional information

Funding

This work was supported by the Natural Science Foundation of China (Nos. 11671228, 11801309), the Domestic Visiting Scholar Project for the Outstanding Young Teacher of Shandong Provincial Universities (2013) and the Applied Mathematics Enhancement Program of Linyi University.

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