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.

中文翻译：

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ELCP全局误差界估计的改进及其应用

摘要

对于扩展线性互补问题（ELCP），我们在更温和的条件下建立了 ELCP 的全局误差界限估计。基于此，我们提出了一种平滑算法来解决该问题。该算法在没有非退化假设的情况下被证明是全局收敛和二次收敛的。本文获得的结果扩展了 ELCP 的现有结果。此外，还给出了一些数值实验结果，表明了该算法的有效性以及该方法的快速收敛性。