An improvement on the global error bound estimation for ELCP and its applications. (15th June 2021) - Sun, Hongchun; Wang, Yiju; Li, Shengjie; Sun, Min
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.